jackson, clement linus...metformin loaded silver nanoparticles were synthesized using ecofriendly...
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JACKSON, CLEMENT LINUS
(PG/Ph.D/11/59509)
ECOFRIENDLY SYNTHESIS OF METFORMIN LOADED SILVER NANOPARTICLES USING NATURAL POLYMERS AND SYNTHESISED STARCH AS STABILIZING AGENTS
FACULTY OF PHARMACY
DEPARTMENT OF PHARMACEUTICAL TECHNOLOGY AND INDUSTRIAL PHARMACY
Paul Okeke
Digitally Signed by: Content manager’s Name DN : CN = Webmaster’s name O= University of Nigeria, Nsukka OU = Innovation Centre
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ECOFRIENDLY SYNTHESIS OF METFORMIN LOADED SILVER NANOPARTICLES USING NATURAL POLYMERS AND SYNTHESISE D STARCH
AS STABILIZING AGENTS
BY
JACKSON, CLEMENT LINUS (PG/Ph.D/11/59509)
DEPARTMENT OF PHARMACEUTICAL TECHNOLOGY AND INDUSTRIAL PHARMACY,
UNIVERSITY OF NIGERIA, NSUKKA
JULY, 2015
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ECOFRIENDLY SYNTHESIS OF METFORMIN LOADED SILVER NANOPARTICLES USING NATURAL POLYMERS AND SYNTHESISE D STARCH
AS STABILIZING AGENTS
BY
JACKSON, CLEMENT LINUS B.Pharm., M.Pharm. (PG/PhD/11/59509)
A THESIS SUBMITTED TO THE DEPARTMENT OF PHARMACEUTICAL TECHNOLOGY AND INDUSTRIAL
PHARMACY FOR THE AWARD OF DOCTOR OF PHILOSOPHY (PhD) DEGREE OF THE UNIVERSITY OF NIGERIA, NSUKKA
SUPERVISOR: PROF S. I. OFOEFULE
DEPARTMENT OF PHARMACEUTICAL TECHNOLOGY AND INDUSTRIAL PHARMACY
JULY, 2015
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TITLE PAGE
ECOFRIENDLY SYNTHESIS OF METFORMIN LOADED SILVER
NANOPARTICLES USING NATURAL POLYMERS AND SYNTHESISE D STARCH
AS STABILIZING AGENTS.
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CERTIFICATION
Jackson, Clement Linus, a postgraduate student in the Department of Pharmaceutical
Technology and Industrial Pharmacy with Registration. Number PG /Ph.D / 11/ 59509, has
satisfactorily completed the requirements for award of the degree of Doctor of Philosophy
(Ph.D) in Pharmaceutical Technology and Industrial Pharmacy. The work embodied in this
thesis is original and has not been submitted in part or full for any other diploma or degree of
this or any other University.
…………………. ………………….. Prof. S. I. Ofoefule Prof. S.I. Ofoefule (Supervisor) (Head of department)
Date: …………………… Date: …………………..
Prof. G. C. Onunkwo (Co - Supervisor)
Date: ……………………
………………………….. External Examiner
Date: ………………..
DEDICATION
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The skills acquired in this research work are dedicated to God Almighty who is the source of
all wisdom, power and excellence. I give Him all the glory.
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ACKNOWLEDGEMENT
I sincerely acknowledge and appreciate God for His Mercies and faithfulness
throughout the period of my studies and thereafter.
I am grateful to my Supervisor and Mentor Prof. S. I. Ofoefule for his patience, support and
encouragement. May the Good Lord reward you.
I appreciate Prof. G.C. Onunkwo, my Co-Supervisor. I thank also, all the Staff of the
Department of Pharmaceutical Technology and Industrial Pharmacy for their support and
kindness. Special thanks to all the Technical Staff of Pharmaceutical Technology and Raw
Materials Development, NIPRD, Abuja.
My special gratitude also goes to members of my family, especially my lovely Wife, Mrs.
Liberty Jackson and blessed children, Jael and David.
Clement Jackson
2015
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TABLE OF CONTENTS
Title page....................................................................................................................i
Certification................................................................................................................ii
Dedication................................................................................................................. iii
Acknowledgement......................................................................................................iv
Table of contents.........................................................................................................v
Lists of Tables............................................................................................................ ix
List of figures............................................................................................................ x
Abstract..................................................................................................................... xii
CHAPTER ONE: INTRODUCTION
1.1 Nanoscience.................................................................................................. 2
1.2 Nanotechnology............................................................................................. 2
1.3 Nanomedicine ............................................................................................... 2
1.4 Nanoparticles..................................................................................................3
1.4.1 Methods of Preparation of Nanoparticles..................................................... 5
1.5. Silver nanoparticles...................................................................................... 9
1.5.1 Synthesis of silver nanoparticles .................................................................. 10
1.5.2 Reducing agents in the synthesis of silver nanoparticles………………… 27
1.5.3 Stabilizing agents in the synthesis of silver nanoparticles………………… 29
1.6 Why eco friendly (green) synthesis? ............................................................30
1.7 Characterisation of silver nanoparticles........................................................ 31
1.8 Metformin HCl............................................................................................ 35
1.9 Polymers use in this research ...................................................................... 35
1.9.1 Guar Gum..................................................................................................... 35
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1.9.2 Xanthan Gum .............................................................................................. 37
1.9.3 Starch .......................................................................................................... 37
1.9.4 Sodium Alginate .......................................................................................... 38
1.10 Objectives of Study...................................................................................... 39
CHAPTER TWO: MATERIALS AND METHODS
2.1 Materials..................................................................................................... 40
2.2 Preparation of silver nitrate ......................................................................... 40
2.3 Synthesis of AMS ....................................................................................... 40
2.4 Synthesis of Silver nanoparticles using Azadirachta indica extract… ……. 41
2.5 Characterisation of silver nanocomposites……………………………….. 41
2.5.1 UV vis spectroscopy of silver nanocomposites…………………………… 41
2.5.2 Determination of Percent yield of nanoparticles …………………………...43
2.5.3 Entrapment efficiency and loading capacity……………………………….. 43
2.5.4 Determination of Particle Size and Polydispersity Index …………………. 43
2.5.5 Differential Scanning Calorimetry and Thermogravimetric analysis …….. 44
2.5.6 Morphological Studies of nanocomposites using SEM ………………….. 44
2.6. In vitro Drug Release Studies …………………………………………….. 44
2.6.1 In vitro release kinetic evaluation ………………………………………. 45
2.7 Antimicrobial Studies of nanocomposites………………………………… 45
2.7.1 Microorganisms used ……………………………………………… ………46
2.7.2 Drugs. ……………………………………………………………………. .46
2.7.3. Preparation of Stock Samples Suspension …………………………………. 46
2.7.4 Preparation of innoculum………………………………………………… 46
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2.7.5 Determination of Minimum Inhibitory Concentration …………………… 47
2.8 Oral glucose loading animal model…………………………………………47
2.8.1 Experimental animals …………………………………………………… 48
2.8.2 Effects of nanocomposites on glucose loaded hyperglycemic rats ……… 48
CHAPTER THREE: RESULTS AND DISCUSSIONS
3.1 UV – vis Spectroscopy………………………………. …… …………….. 50
3.2 Percentage yield of nanocomposites ………………………………………… 50
3.3 Entrapment efficiency and loading capacity …………………………………. 51
3.4 Differential Scanning Calorimetry …………………………………………… 57
3.5 Thermogravimetric Analysis ………………………………………………… 65 3.6 Determination of Particle size and Polydispersity Index ……………………. 69 3.7: Morphological Studies …………………………………………………… 74 3.8 Drug Release Profiles ……………………………………………………….. 77
3.9 Time for 50 % of Drug to be released in SGF (T50)………………………….. 81 3.10 Time for 50 % of Drug to be released in SIF (T50)………………………….. 94 3.11 Time for 25 % and 75% of Drug to be released in SGF (T25 and T75 )………. 96 3.12 Time for 25 % and 75% of Drug to be released in SIF (T25 and T75 )…… … 98 3.13 Maximum Release……………………………………………………………. 100 3.13.1 Maximum Release in SGF ………………………………………………… 100 3.13.2 Maximum Release in SIF………………………………………………….. 102 3.14 Kinetics and Mechanism of Release ……………………………………… 105 3.15 Statistical Comparison of the Release Profiles of Nanocomposites using
Multiple Time Points Dissolution………………………………………… 110 3.16 Comparison of nanocomposites using Similarity Factor (F2) ………………115 3.17: Antimicrobial Studies ……………………………………………………….. 119
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3.18: Effect of nanocomposites in glucose loaded hyperglycemic rats …………… 127
CHAPTER FOUR: CONCLUSION
Conclusion ……………………………………………………………………. 127
REFERENCES 128
APPENDICES 148
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List of Tables
Table 1. Composition of Nanocomposites………………………………………… 42
Table 2. Percentage yield of nanocomposites ………,…………………………… 56
Table 3 Entrapment efficiency and loading capacity of nanocomposites …. ………58
Table 4: Mean Particle Size and PDI of nanocomposites ………………………. 72 Table 5. Release Parameters for Metformin nanocomposites…………………….. 106 Table 6. Kinetics and Mechanism of release for Metformin nanoparticles ……….. 108
Table 7 Minimum inhibitory concentration (MIC) of nanocomposites………… 122
Table 8 Effect of nanocomposites in glucose loaded hyperglycemic rats ………. 126
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LIST OF FIGURES
Fig. 1: UV -vis of AMS5%NANOmet …………………………………………… 52
Fig. 2: UV -vis of GG5%NANOmet …………………………………………….. 53
Fig 3: UV-vis of NaALG5%NANOmet ………………………………………… 54
Fig 4: UV-vis of XG5%NANOmet ……………………………………………… 55
Fig 5: Thermogram of AMS5%NANOmet ……………………………………… 60
Fig 6: Thermogram of GG3%NANOmet ………………………………………… 61
Fig 7: Thermogram of GG5%NANOmet ……………………………………… 62
Fig 8: Thermogram of XG5%NANOmet ………………………………………… 63
Fig 9: Thermogram of NaALGG5%NANOmet ………………………………… 64
Fig 10: Thermogravimetric analysis (TGA) of guar Gum ………………………… 66
Fig 11: Thermogravimetric analysis (TGA) of xanthan Gum ……………………. 67
Fig 12: Thermogravimetric analysis (TGA) of Sodium alginate ………………… 68
Fig 13: Comparison of mean particle sizes of nanocomposites…………………… 73
Fig 14: SEM for Modified Starch (AMS) …………………………………………. 75
Fig 15: SEM for AMS1%NANOmet ………………………………………………76
Fig 16: Release profiles of GG1%NANOmet …………………………………… 82
Fig 17: Release profiles of GG3%NANOmet…………………………………… 83
Fig 18; Release profile of GG5%NANOmet ………………………………………84
Fig 19: Release profiles of AMS1%NANOmet ……………………………………85
Fig 20; Release profiles of AMS3%NANOmet…………………………………… 86
Fig 21; Release profile of AMS5%NANOmet ………………………………87
Fig 22: Release profiles of NaALG1%NANOmet ……………………………….. 88
Fig 23; Release profiles of NaALG3%NANOmet………………………………… 89
Fig 24; Release profile of NaALG5%NANOmet ………………………………90
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Fig 25: Release profiles of XG1%NANOmet ……………………………………. 91
Fig 26; Release profiles of XG3%NANOmet………………………………………92
Fig 27; Release profile of XG5%NANOmet …………………………………….. 93
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ABSTRACT
Metformin loaded silver nanoparticles were synthesized using ecofriendly method with
extract of Azadiractha indica as reducing agent and two natural polymers; guar gum and
xanthan gum, Sodium alginate, and a semi- synthetic polymer (AMS) as stabilizing agents.
Twelve batches of nanoparticles were synthesized. Nanocomposites synthesized from AMS
were designated as AMS 1% NANOmet, AMS3% NANOmet and AMS5% NANOmet. Guar
gum stabilized nanoparticles were designated as GG1% NANOmet, GG3% NANOmet and
GG5% NANOmet while Xanthan gum nanocomposites were coded as XG1% NANOmet,
XG3% NANOmet and XG5% NANOmet respectively. Sodium alginate stabilized
nanocomposites were designated as NaALG1% NANOmet, NaALG3% NANOmet and
NaALG5% NANOmet respectively. The percentage yield of nanocomposites was high with
values ranging from 80 % to 99.87 %. The entrapment efficiencies of the samples ranged
from 63.06 % to 80.22 % while the loading capacities were in the range of 7.24 % to 24.10
%. Differential scanning calorimetry showed there was no interaction between the polymers
and metformin. Characterization of the metformin nanocomposites using UV- vis
spectroscopy, zeta sizer, scanning electron microscopy (SEM) and polydispersity were
performed. The UV-vis spectroscopy showed surface plasmon resonance of 371nm for all the
nanocomposites except XG5%NANOmet which had SPR of 335nm. The mean particle size
of GG1%NANOmet was ideal with a value of 188.7nm followed by AMS1%NANOmet
(386.7 nm). All the batches showed extended and sustained release profile with initial burst
effect at the first 30 min of release studies. Release of metformin in SIF was predominantly
higher than in SGF. The kinetics of release was mainly zero order for all the nanocomposites
with the exception of NaALG5% NANOmet which released the drug by higuchi kinetics.
Antimicrobial property of the optimized nanocomposites were similar (P>0.05). Generally,
MIC values of the samples against the microorganisms tested ranged from 2500- 5000µg/ml.
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In vivo anti hyperglycemic property of the optimized metformin nanocomposite using
glucose hyperload model results showed GG5%NANOmet as the optimum batch. At equal
doses it produced sustained and consistent significant (p<0.001) decrease in elevated blood
glucose level in glucose loaded hyperglycemic rats when compared with metformin and other
nanocomposites treated groups.
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CHAPTER ONE
1.0. INTRODUCTION
In recent years, there has been an exponential interest in the development of novel
drug delivery systems using nanoparticles [1]. The transition from microparticles to
nanoparticles has led to a number of changes in physical properties of materials [2]. Two of the
major factors in this are the increase in the ratio of surface area to volume, and the size of the
particle moving into the realm quantum effects predominate. The increase in the surface-area-to-
volume ratio, which is a gradual progression as the particle gets smaller, leads to an increasing
dominance of the behaviour of atoms on the surface of the particle over that of those in the
interior of the particle. This affects both the properties of the particle in isolation and its
interaction with other material. [2]
There have been tremendous developments in the field of Nanotechnology in recent
time with various technologies formulated to synthesize nanoparticles with specific
characteristics on morphology and distribution [3]. Although, there are several methods for
the synthesis of nanoparticles, they are very expensive and involve the use of toxic and
hazardous chemicals which cause danger to humans and the environment [4]. To overcome
these challenges, the eco-friendly synthesis of nanoparticles using environmentally benign
materials like Plants [5], microorganisms [4,5], seaweed [6] and enzymes [7] were employed.
It is a single step and offers several advantages such as time reducing, cost effective and Non-
toxic. Nanocrystalline silver is a known Noble metal and they have tremendous applications
in the field of Detection, Diagnostics, Therapeutics and Antimicrobial activity [8].
In general, nanoparticles offer significant advantages over the conventional drug delivery in
terms of high stability, high specificity, high drug carrying capacity, ability for controlled
release, possibility to use in different route of administration and the capability to deliver
both hydrophilic and hydrophobic drug molecules [1].
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1.1 Nanoscience
Nanoscience is the study of phenomena and manipulation of materials at atomic and
molecular levels, where properties are remarkably different from those at larger scale [11]. It
is the study of materials that display exceptional properties, functionality and phenomena due
to the influence of small dimensions. It is the science in which materials with small
dimensions exhibit new physical phenomena, collectively known as quantum effects, which
are size dependable and significantly different from the properties of large scale materials. It
is an inter disciplinary science which cuts across the areas of Physics, Chemistry, Biology
and medicine. Other disciplines affected by nanoscience include molecular biology, surface
Science, Engineering and Biotechnology.
1.2 Nanotechnology
The application of nanoscience to technology or practical devices is called
nanotechnology. Nanotechnology is the application of nanoscience to meet industrial and
commercial objectives [11]. Nanotechnology is also applied in the design, characterisation,
production and application of devices and systems by controlling shape and size at
NANOmeter scale (1- 100nm)
1.3 NANOMEDICINE
Nanomedicine is simply the application of nanotechnology to medicine or healthcare
delivery. It is the well defined application of nanotechnology in the area of healthcare and,
disease diagnosis and treatment. Nanomedicine is a relatively new field of science and
technology. By interacting with biological molecules at nano level, nanotechnology opens up
a vast field of research and application. Interactions between artificial molecular nanodevices
and biomolecules can be examined in the extracellular medium and inside the human cells.
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Working at nanoscale, allows exploiting physical properties different from those observed at
microscale such as the volume/surface ratio. The investigated diagnostic applications can be
considered for in vitro as well as for in vivo diagnosis. In vitro, the synthesized particles and
manipulation or detection devices allow for the recognition, capture, and concentration of
biomolecules. In vivo, the synthetic molecular assemblies are mainly designed as a contrast
agent for imaging [12]
A second area exhibiting a strong development is nanodrugs where nanoparticles are
designed for targeted drug delivery. The use of such carriers improves the drug
biodistribution, targeting active molecules to diseased tissues while protecting healthy ones
[12]
A third area of application is regenerative medicine where nanotechnology allows
developing biocompatible materials which support growth of cells used in cell therapy.
Nanomedicine can enhance the development of a personalized medicine both for diagnosis
and therapy.
‘There is no nanomedicine, there is nanotechnology in medicine’ (12). Even if the
expression “nanomedicine” has been widely used for a couple of years, it is more proper to
refer to “nanotechnology enabled medicine” in different sub‐areas of medicine such as
diagnostics, therapy or monitoring.
1.4. Nanoparticles
According to the definition from National Nanotechnology Initiative (NNI),
nanoparticles are structures of sizes ranging from 1 to 100 nm in at least one dimension.
However, the prefix “nano” is commonly used for particles that are up to several hundred
NANOmeters in size.[11].
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Nanoparticles can also be defined as particulate dispersions or solid particles with a
size in the range of 10-1000nm. The active pharmaceutical ingredient is dissolved, entrapped,
encapsulated or attached to a nanoparticle matrix. Depending upon the method of definition,
nanoparticles, nanospheres or nanocapsules can be obtained. Nanocapsules are systems in
which the drug is confined to a cavity surrounded by a unique polymer membrane; while
nanospheres are matrix systems in which the drug is physically and uniformly dispersed [13]
Nanoparticles exhibit unique properties, which are quite different from those of larger
particles. New properties of nanoparticles related to variation in specific characteristics like
size, shape and distribution have been demonstrated [14].
The advantages of using nanoparticles as a drug delivery system include the
following [13]
1. Particle size and surface characteristics of nanoparticles can be easily manipulated to
achieve both passive and active drug targeting after parenteral administration.
2. Controlled and sustained release of the drug during the transportation and at the site of
action, altering organ distribution of the drug and subsequent clearance of the drug in order to
achieve enhanced drug therapeutic efficacy and minimal side effects.
3. Drug loading is relatively high and drugs can be incorporated into the systems without
chemical reaction.
4. Site-specific targeting can be achieved by attaching targeting ligands to particle surface.
5. The system can be used for various routes of administration including oral, nasal,
parenteral, intra-ocular etc.
6. Avoidance of coalescence leads to enhanced physical stability.
7. Reduced mobility of incorporated drug molecules leads to reduction of drug leakage.
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8. Static interface solid/liquid facilitates surface modification
The Disadvantages of nanoparticles include:
1. Potential toxicity
While the small size of nanoparticle is what makes them so useful in medicine, it is also the
factor that might make them potentially dangerous to human health.
2. Environmental concerns
Artificially manufactured nanoparticles will be new to the environment in type and quantity
and would constitute a new class of non biodegradable pollutants.
Ideal Properties of polymers used in nanoparticle drug delivery system should be natural or
synthetic polymer, inexpensive nontoxic and biodegradable. They should be non
thrombogenic, non immunogenic and non inflammatory. Particle size of less than 100 nm is
ideal and they should also have prolonged circulation time [15-20]
1.4.1. Methods of Preparation of Nanoparticles [11]
Nanoparticles can be synthesized from a variety of materials such as proteins,
polysaccharides and synthetic polymers. The selection of matrix materials is dependent on
many factors including:
a) Size of nanoparticles required;
b) Inherent properties of the drug, e.g., aqueous solubility and stability;
c) Surface characteristics such as charge and permeability;
d) Degree of biodegradability,
e) Biocompatibility and toxicity;
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f) Drug release profile desired; and
g) Antigenicity of the final product.
Nanoparticles have been prepared most frequently by three methods:
(1) Dispersion of preformed polymers
(2) Polymerization of monomers; and
(3) Ionic gelation or coacervation of hydrophilic polymers.
However, other methods such as supercritical fluid technology and particle replication in
non-wetting templates have also been described in the literature for production of
nanoparticles. The latter was claimed to have absolute control of particle size, shape and
composition, which could set an example for the future mass production of nanoparticles in
industry (11).
(I). Dispersion of preformed polymers
Dispersion of preformed polymers is a common technique used to prepare
biodegradable nanoparticles from poly (lactic acid) (PLA); poly (D,L-glycolide), PLG; poly
(D, L-lactide-co-glycolide) (PLGA) and poly (cyanoacrylate) (PCA), This technique can be
used in various ways as described below.
a. Solvent evaporation method
In this method, the polymer is dissolved in an organic solvent like dichloromethane,
chloroform or ethyl acetate which is also used as the solvent for dissolving the hydrophobic
drug. The mixture of polymer and drug solution is then emulsified in an aqueous solution
containing a surfactant or emulsifying agent to form oil in water (o/w) emulsion. After the
formation of stable emulsion, the organic solvent is evaporated either by reducing the
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pressure or by continuous stirring. Particle size was found to be influenced by the type and
concentrations of stabilizer, homogenizer speed and polymer concentration. In order to
produce small particle size, often a high-speed homogenization or ultrasonication may be
employed.
b. Spontaneous emulsification or solvent diffusion method
This is a modified version of solvent evaporation method. In this method, the water
miscible solvent along with a small amount of the water immiscible organic solvent is used as
an oil phase. Due to the spontaneous diffusion of solvents an interfacial turbulence is created
between the two phases leading to the formation of small particles. As the concentration of
water miscible solvent increases, a decrease in the size of particle can be achieved. Both
solvent evaporation and solvent diffusion methods can be used for hydrophobic or
hydrophilic drugs. In the case of hydrophilic drug, a multiple w/o/w emulsion needs to be
formed with the drug dissolved in the internal aqueous phase.
(II). Polymerization method
This method involves the polymerization of monomers to form nanoparticles in an
aqueous solution. Drug is incorporated either by being dissolved in the polymerization
medium or by adsorption onto the nanoparticles after polymerization is completed. The
nanoparticle suspension is then purified to remove various stabilizers and surfactants
employed for polymerization by ultracentrifugation and re-suspending the particles in an
isotonic surfactant-free medium. This technique has been reported for making
polybutylcyanoacrylate or poly (alkylcyanoacrylate) nanoparticles. Nanocapsule formation
and their particle size depend on the concentration of the surfactants and stabilizers used.
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(III). Coacervation or ionic gelation method
Much research has been focused on the preparation of nanoparticles using
biodegradable hydrophilic polymers such as chitosan, gelatin and sodium alginate. A method
for preparing hydrophilic chitosan nanoparticles by ionic gelation was developed by Calvo
and co-workers [17]. The method involves a mixture of two aqueous phases, of which one is
the polymer chitosan, a di-block co-polymer ethylene oxide or propylene oxide (PEO-PPO)
and the other is a polyanion sodium tripolyphosphate. In this method, positively charged
amino group of chitosan interacts with negative charged tripolyphosphate to form coacervates
with a size in the range of nanometer. Coacervates are formed as a result of electrostatic
interaction between two aqueous phases, whereas, ionic gelation involves the material
undergoing transition from liquid to gel due to ionic interaction conditions at room
temperature.
(IV). Production of nanoparticles using supercritical fluid technology
Conventional methods such as solvent extraction-evaporation, solvent diffusion and organic
phase separation methods require the use of organic solvents which are dangerous to the
environment as well as to physiological systems. Therefore, the supercritical fluid technology
has been investigated as an alternative to prepare biodegradable micro- and nanoparticles
because supercritical fluids are environmentally safe.
A supercritical fluid can be generally defined as a solvent at a temperature above its critical
temperature, at which the fluid remains a single phase regardless of the prevailing conditions.
Supercritical carbon dioxide (SC CO2) is the most widely used supercritical fluid because of
its mild critical conditions (Tc = 31.1 °C, Pc = 73.8 bars), non toxicity, non-flammability, and
cost effectiveness. The most common processing techniques involving supercritical fluids are
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supercritical anti-solvent (SAS) and rapid expansion of supercritical solution (RESS). The
process of SAS employs a liquid solvent like methanol, which is completely miscible with
the supercritical fluid (SC CO2), to dissolve the solute to be micronized; at the process
conditions, because the solute is insoluble in the supercritical fluid, the extract of the liquid
solvent by supercritical fluid leads to the instantaneous precipitation of the solute, resulting in
the formation of nanoparticles. RESS differs from the SAS process in that its solute is
dissolved in a supercritical fluid (such as supercritical methanol) and then the solution is
rapidly expanded through a small nozzle into a region lower pressure, Thus the solvent power
of supercritical fluids dramatically decreases and the solute eventually precipitates.
1.5. Silver nanoparticles
Silver nanoparticles are of interest because of the unique properties (e.g., size and
shape dependent optical, electrical, and magnetic properties) which can be incorporated into
antimicrobial applications, biosensor materials, composite fibers, cryogenic superconducting
materials, cosmetic products, and electronic components [21]. Several physical and chemical
methods have been used for synthesizing and stabilizing silver nanoparticles [22]. The most
popular chemical approaches, including chemical reduction using a variety of organic and
inorganic reducing agents, electrochemical techniques, physicochemical reduction, and
radiolysis are widely used for the synthesis of silver nanoparticles. Recently, nanoparticle
synthesis is among the most interesting scientific areas of inquiry, and there is growing
attention to produce nanoparticles using environmentally friendly methods (green chemistry).
Green synthesis approaches include mixed-valence polyoxometalates, polysaccharides,
Tollens, biological, and irradiation method which have advantages over conventional
methods involving chemical agents associated with environmental toxicity [21].
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1.5.1. Synthesis of silver nanoparticles
(I) Physical approaches
Most important physical approaches include evaporation-condensation and laser ablation.
Various metal nanoparticles such as silver, gold, lead, cadmium and fullerene have
previously been synthesized using the evaporation-condensation method [21]. The absence of
solvent contamination in the prepared thin films and the uniformity of nanoparticles
distribution are the advantages of physical approaches in comparison with chemical
processes. Physical synthesis of silver nanoparticles using a tube furnace at atmospheric
pressure has some disadvantages, for example, tube furnace occupies a large space, consumes
a great amount of energy while raising the environmental temperature around the source
material, and requires a great deal of time to achieve thermal stability.
Moreover, a typical tube furnace requires power consumption of more than several kilowatts
and a preheating time of several tens of minutes to reach a stable operating temperature [23].
( a) Evaporation-condensation
It was demonstrated that silver nanoparticles could be synthesized via a small ceramic
heater with a local heating source [24]. The vapor can cool at a suitable rapid rate, because
the temperature gradient in the vicinity of the heater surface is very steep in comparison with
that of a tube furnace. This makes possible the formation of small nanoparticles in high
concentration. This physical method can be useful as a nanoparticle generator for long-term
experiments for inhalation toxicity studies, and as a calibration device for nanoparticle
measurement equipment [24].
( b) Laser ablation
Silver nanoparticles could be synthesized by laser ablation of metallic bulk materials
in solution [25 – 27]. The ablation efficiency and the characteristics of resultant nanosilver
particles depend upon many factors such as the wavelength of the laser impinging the
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metallic target, the duration of the laser pulses (in the femto-, pico- and nanosecond regime),
the laser frequency, the ablation time duration and the effective liquid medium, with or
without the presence of surfactants [28-30]. One merit of laser ablation technique when
compared to other methods for production of metal colloids is the absence of chemical
reagents in solutions. Consequently, pure and uncontaminated metal colloids for further
applications can be prepared by this technique [31]. Silver nanospheroids (20- 50 nm) were
reported to have been prepared by laser ablation in water with femtosecond laser pulses at
800 nm [32]. The formation efficiency and the size of colloidal particles were compared with
those of colloidal particles prepared by nanosecond laser pulses. The results revealed the
formation efficiency for femtosecond pulses was significantly lower than that for nanosecond
pulses. The size of colloids prepared by femtosecond pulses were less dispersed than that of
colloids prepared by nanosecond pulses. Furthermore, it was found that the ablation
efficiency for femtosecond ablation in water was lower than that in air, while, in the case of
nanosecond pulses, the ablation efficiency was similar in both water and air.
(II) Chemical approaches
The most common approach for synthesis of silver nanoparticles is chemical
reduction by organic and inorganic reducing agents. In general, different reducing agents
such as sodium citrate, ascorbate, sodium borohydride (NaBH4), elemental hydrogen, polyol
process, Tollens reagent, N, N-dimethylformamide (DMF), and poly (ethylene glycol)-block
copolymers are used for reduction of silver ions (Ag+) in aqueous or non-aqueous solutions.
The aforementioned reducing agents reduce silver ions (Ag+) and lead to the formation of
metallic silver (Ag0), which is followed by agglomeration into oligomeric clusters. These
clusters eventually lead to formation of metallic colloidal silver particles [33,34]. It is
important to use protective agents to stabilize dispersive nanoparticles during the course of
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metal nanoparticle preparation, and protect the nanoparticles that can be absorbed on or bind
onto nanoparticle surfaces, avoiding their agglomeration [35]. The presence of surface acting
agents (e.g., thiols, amines, acids, and alcohols) for interactions with particle surfaces can
stabilize particle growth, and protect particles from sedimentation, agglomeration, or losing
their surface properties. Polymeric compounds such as poly(vinylalcohol), poly
(vinylpyrrolidone, polyethylene glycol), poly(methacrylic acid), and polymethylmethacrylate
have been reported to be effective protective agents to stabilize nanoparticles. In one study,
Oliveira et al. [35] prepared dodecanethiol capped silver nanoparticles, based on Brust
procedure [36], based on a phase transfer of a gold ion complex from aqueous to organic
phase in a two-phase liquidliquid system, followed by a reduction with sodium borohydride
in the presence of dodecanethiol as a stabilizing agent, binding onto the nanoparticles
surfaces, thereby avoiding their aggregation and making them soluble in certain solvents.
They reported that small changes in synthetic factors lead to dramatic modifications in
nanoparticle structure, average size, size distribution width, stability and self-assembly
patterns. Zhang et al. [37] used a hyperbranched poly(methylene bisacrylamide aminoethyl
piperazine) with terminal dimethylamine groups (HPAMAM-N(CH3)2) to produce colloids of
silver. The amide moieties, piperazine rings, tertiary amine groups and the hyper-branched
structure in HPAMAM-N(CH3)2 are essential to its effective stabilizing and reducing
abilities.
(a) Microemulsion techniques
Uniform and size controlled silver nanoparticles can be synthesized using micro-
emulsion methods. The nanoparticles preparation in two-phase aqueous organic systems is
based on the initial spatial separation of reactants (metal precursor and reducing agent) in two
immiscible phases. The interface between the two liquids and the intensity of inter-phase
29
transport between two phases, which is mediated by a quaternary alkyl-ammonium salt, affect
the rate of interactions between metal precursors and reducing agents. Metal clusters formed
at the interface are stabilized, due to their surface being coated with stabilizer molecules
occurring in the non-polar aqueous medium, and transferred to the organic medium by the
inter-phase transporter [38]. One of the major disadvantages of this method is the use of
highly deleterious organic solvents. Thus large amounts of surfactant and organic solvent
must be separated and removed from the final product. For instance, Zhang et al.[37] used
dodecane as an oily phase (a low deleterious and even nontoxic solvent), but there was no
need to separate the prepared silver solution from the reaction mixture. On other hand,
colloidal nanoparticles prepared in non aqueous media for conductive inks are well-dispersed
in a low vapour pressure organic solvent, to readily wet the surface of the polymeric substrate
without any aggregation. These advantages can also be found in the applications of metal
nanoparticles as catalysts to speed up most organic reactions conducted in non-polar solvents.
It is essential to transfer nano metal particles to different physicochemical environments in
practical applications [39].
(b) UV-initiated photo reduction
This simple and effective method has been reported for synthesis of silver
nanoparticles in the presence of citrate, polyvinyl pyrrolidone, poly (acrylic acid), and
collagen. For instance, Huang and Yang [40] prepared silver nanoparticles via the photo
reduction of silver nitrate in layered inorganic laponite clay suspensions which served as a
stabilizing agent for the prevention of nanoparticles aggregation. The properties of the
produced nanoparticles were studied as a function of UV irradiation time. Bimodal size
distribution and relatively large silver nanoparticles were obtained when irradiated under UV
for 3 h. Further irradiation disintegrated the silver nanoparticles into smaller sizes with a
30
single distribution mode until a relatively stable size and size distribution was obtained [40].
Silver nanoparticles (nanosphere, nanowire, and dendrite) have been prepared by an
ultraviolet irradiation photoreduction technique at room temperature using poly(vinylalcohol)
(as protecting and stabilizing agent).
(c) Sonoelectrochemical method
Sonoelectrochemistry technique utilizes ultrasonic power mainly to manipulate the
material mechanically. The pulsed sonoelectrochemical synthetic method involves alternating
sonic and electric pulses while electrolyte composition plays a crucial role in shape formation
[41]. It was reported that silver nanospheres could be prepared by sonoelectrochemical
reduction using a complexing agent, nitrilotriacetate as stabilizing agent to avoid aggregation
[41].
(d) Photoinduced reduction
Nano-sized silver particles with an average size of 8 nm were prepared by
photoinduced reduction using poly(styrene sulfonate)/poly(allylamine hydrochloride)
polyelectrolyte capsules as microreactors [42]. It was also demonstrated that the
photoinduced technique could be used for converting silver nanospheres into triangular silver
nanocrystals (nanoprisms) with desired edge lengths in the range of 30-120 nm [43]. The
particle growth process was controlled using dual-beam illumination of nanoparticles. Citrate
and poly(styrene sulfonate) were used as stabilizing agents. In another study, silver
nanoparticles were prepared through a very fast reduction of Ag+ by α- aminoalkyl radicals
generated from hydrogen abstraction toward an aliphatic amine by the excited triplet state of
2-substituted thioxanthone series (TX−O−CH2−COO− and TX−S−CH2−COO−). The
31
quantum yield of this prior reaction was tuned by a substituent effect on the thioxanthones,
and led to a kinetic control of the conversion of Ag+ to Ag(0) [44].
(e) Electrochemical synthetic method
This method can also be used to synthesize silver nanoparticles. It is possible to
control particle size by adjusting the electrolysis parameters and to improve homogeneity of
silver nanoparticles by changing the composition of the electrolytic solutions.
Polyphenylpyrrole-coated silver nanospheroids (3-20 nm) were synthesized by
electrochemical reduction at the liquid/liquid interface [21]. This nano-compound was
prepared by transferring the silver metal ion from the aqueous phase to the organic phase,
where it reacted with pyrrole monomer [45]. In another study, spherical silver nanoparticles
(10-20 nm) with narrow size distributions were conveniently synthesized in an aqueous
solution by an electrochemical method [46]. Poly N-vinylpyrrolidone was chosen as the
stabilizer for the silver clusters in this study. Poly N-vinylpyrrolidone protects nanoparticles
from agglomeration, significantly reduces silver deposition rate, and promotes silver
nucleation and silver particle formation rate. Application of rotating platinum cathode
effectively solves the technological difficulty of rapidly transferring metallic nanoparticles
from the cathode vicinity to bulk solution, avoiding the occurrence of flocculates in vicinity
of the cathode, and ensures monodispersity of particles. The addition of sodium dodecyl
benzene sulfonate to the electrolyte improved the particle size and particle size distribution of
the silver nanoparticles [46].
( f) Laser irradiation
Silver nanoparticles can be synthesized by using a variety of irradiation methods.
Laser irradiation of an aqueous solution of silver salt and surfactant can produce silver
32
nanoparticles with a well defined shape and size distribution [47]. Furthermore, the laser was
used in a photo-sensitization synthetic method of synthesizing silver nanoparticles using
benzophenone. Laser and mercury lamp can be used as light sources for the production of
silver nanoparticles [48]. In visible light irradiation studies, the photo-sensitized growth of
silver nanoparticles using thiophene (sensitizing dye) and silver nanoparticle formation by
illumination of Ag(NH3)+ in ethanol has been accomplished [49].
( g) Microwave assisted synthesis
This technique is a promising method for the synthesis of silver nanoparticles. It was
reported that silver nanoparticles could be synthesized by a microwave-assisted synthesis
method which employs carboxymethyl cellulose sodium as a reducing and stabilizing agent
[21]. The size of the resulting particles depended on the concentration of sodium
carboxymethyl cellulose and silver nitrate. The produced nanoparticles were uniform and
stable, and were stable at room temperature for 2 months without any visible change [50].
The preparation of silver nanoparticles in the presence of Platinum seeds, polyvinyl
pyrrolidine and ethylene glycol was also reported [51]. Additionally, starch has been
employed as a template and reducing agent for the synthesis of silver nanoparticles with an
average size of 12 nm, using a microwave-assisted synthetic technique. Starch functions as a
stabilizing agent, preventing the aggregation of the produced silver nanoparticles [52].
Microwaves in combination with polyol process were applied in the synthesis of silver
nanospheroids using ethylene glycol and poly N-vinylpyrrolidone as reducing and stabilizing
agents, respectively [53]. In a typical polyol process inorganic salt is reduced by the polyol
(e.g., ethylene glycol which serves as both a solvent and a reducing agent) at a high
temperature. Yin et al. [54] reported that large-scale and size-controlled silver nanoparticles
could be rapidly synthesized under microwave irradiation from an aqueous solution of silver
33
nitrate and trisodium citrate in the presence of formaldehyde as a reducing agent. Size and
size distribution of the produced silver nanoparticles are strongly dependent on the states of
silver cations in the initial reaction solution. Silver nanoparticles with different shapes can be
synthesized by microwave irradiation of a silver nitrate ethylene- glycol-H2[PtCl6]-
poly(vinylpyrrolidone) solution within 3 min [55]. Moreover, the use of microwave
irradiation to produce monodispersed silver nanoparticles using basic amino acids (as
reducing agents) and soluble starch (as a protecting agent) has been reported [56]. Moreover,
silver nanoparticles supported on silica aero-gel were produced using gamma radiolysis. The
produced silver clusters were stable in the 2-9 pH range and started agglomeration at pH > 9
[57]. Oligochitosan as a stabilizer can be used in a preparation of silver nanoparticles by
gamma radiation.
(h) γ -ray irradiation
Silver nanoparticles (4-5 nm) were also synthesized by γ-ray irradiation of acetic water
solutions containing silver nitrate and chitosan [58]. In another study, silver nanospheroids
(1-4 nm) were produced by γ-ray irradiation of a silver solution in optically transparent
inorganic mesoporous silica. Reduction of silver ions within the matrix was brought about by
hydrated electrons and hydroalkyl radicals generated during the radiolysis of a 2-propanol
solution. The nanoparticles produced within the silica matrix were stable in the presence of
oxygen for at least several months [59]. Moreover, silver nanoparticles (60-200 nm) have
been produced by irradiating a solution, prepared by mixing silver nitrate and poly-vinyl-
alcohol, with 6 MeV electrons [60].
34
(i) Use of polysaccharides
In polysaccharide method, silver nanoparticles were prepared using water as an
environmentally-friendly solvent and polysaccharides as capping/reducing agents. For
instance, the synthesis of starch-silver nanoparticles was carried out with starch (as a capping
agent) and β-D-glucose (as a reducing agent) in a gently heated system [61]. The binding
interactions between starch and the synthesised silver nanoparticles were weak and could be
reversible at higher temperatures, allowing for the separation of the synthesized
nanoparticles. In dual polysaccharide function, silver nanoparticles were synthesized by the
reduction of silver ions inside nanoscopic starch templates [62]. The extensive network of
hydrogen bands in templates provided surface protection against nanoparticle aggregation.
Green synthesis of silver nanoparticles using negatively charged heparin (reducing/stabilizing
agent and nucleation controller) was also reported by heating a solution of silver nitrate and
heparin to 70 °C for approximately 8 h [63].
Transmission electron microscopy (TEM) micrographs demonstrated an increase in particle
size of silver nanoparticles with increased concentrations of silver nitrate (as the substrate)
and heparin. Moreover, changes in the heparin concentration influenced the morphology and
size of silver nanoparticles. The synthesized silver nanoparticles were highly stable, and
showed no signs of aggregation after two months [63]. In another study, stable silver
nanoparticles (10-34 nm) were synthesized by autoclaving a solution of silver nitrate (as the
substrate) and starch (as a capping/reducing agent) at 15 psi and 121 °C for 5 min [64]. These
nanoparticles were stable in solution for three months at approximately 25 °C. Smaller silver
nanoparticles (≤10 nm) were synthesized by mixing two solutions of silver nitrate containing
starch (as a capping agent), and NaOH solutions containing glucose (as a reducing agent) in a
spinning disk reactor with a reaction time of less than 10 min [64].
35
(j) Tollens method
Recently, a simple one-step process, Tollens method, has been used for the synthesis
of silver nanoparticles with a controlled size. This green synthesis technique involves the
reduction of Ag(NH3)2+ (as a Tollens reagent) by an aldehyde [65]. In the modified Tollens
method, silver ions are reduced by saccharides in the presence of ammonia, yielding silver
nanoparticle films (50-200 nm), silver hydrosols (20-50 nm) and silver nanoparticles of
different shapes. In this technique, the concentration of ammonia and the nature of the
reducing agent play an important role in controlling size and morphology of the silver
nanoparticles. It was revealed that the smallest particles were formed at the lowest ammonia
concentration. Glucose and the lowest ammonia concentration (5 mM) resulted in the
smallest average particle size of 57 nm with an intense maximum surface plasmon
absorbance at 420 nm. Moreover, an increase in ammonia from 0.005 M to 0.2 M resulted in
a simultaneous increase in particle size and polydispersity [66].
Silver nanoparticles with controllable sizes were synthesized by reduction of [Ag(NH3)2]+
with glucose, galactose, maltose, and lactose [66]. The nanoparticle synthesis was carried out
at various ammonia concentrations (0.005-0.20 M) and pH conditions (11.5-13.0), resulting
in average particle sizes of 25-450 nm. The particle size was increased by increasing NH3,
and the difference in the structure of the reducing agent (monosaccharides and disaccharides)
and pH (particles obtained at pH 11.5 were smaller than those at pH 12.5) influenced the
particle size. Polydispersity also decreased in response to decreased in the pH. Produced
silver nanoparticles were stabilized and protected by sodium dodecyl sulfate (SDS),
polyoxyethylenesorbitane monooleate (Tween 80), and polyvinylpyrrolidone (PVP 360) [66,
67].
36
(k) Use of Polyoxometalates
Silver, gold, palladium, and platinum nanoparticles can be produced at room
temperature, as a result of simply reacting the corresponding metal ions with reduced
polyoxometalates which served as reducing and stabilizing agents. Polyoxometalates are
soluble in water and have the capability of undergoing stepwise, multielectron redox
reactions without disturbing their structure. It was demonstrated that silver nanoparticles were
produced by illuminating a deaerated solution of polyoxometalate/S/Ag+ (polyoxometalate:
[PW12O40] 3, [SiW12O40] 4- ; S:propan-2-ol or 2,4-dichlorophenol) [68]. Furthermore,
green chemistry-type one-step synthesis and stabilization of silver nanostructures with MoV–
MoVI mixed-valence polyoxometalates in water at room temperature has been reported [69].
(III). Biological approaches
In recent years, the development of efficient green chemistry methods employing
natural reducing, capping, and stabilizing agents to prepare silver nanoparticles with desired
morphology and size have become a major focus of researchers. Biological methods can be
used to synthesize silver nanoparticles without the use of any harsh, toxic and expensive
chemical substances [70,71]. The bioreduction of metal ions by combinations of
biomolecules found in the extracts of certain organisms (e.g., enzymes/proteins, amino acids,
polysaccharides, and vitamins) is environmentally benign, yet chemically complex. Many
studies have reported successful synthesis of silver nanoparticle using microorganisms and
other biological systems)[72, 73].
Synthesis of silver nanoparticles by bacteria
It was reported that highly stable silver nanoparticles (40 nm) could be synthesized by
bioreduction of aqueous silver ions with a culture supernatant of non pathogenic bacterium,
37
Bacillus licheniformis [74]. Moreover, well-dispersed silver nanocrystals (50 nm) were
synthesized using the bacterium Bacillus licheniformis [75]. Saifuddin et al. [76] described a
novel combinational synthesis approach for the formation of silver nanoparticles by using a
combination of culture supernatant of B. subtilis and microwave irradiation in water. In
another study, rapid biosynthesis of metallic nanoparticles of silver using the reduction of
aqueous Ag+ ions by culture supernatants of Klebsiella pneumonia, E. coli, and Enterobacter
cloacae (Enterobacteriacae) was reported [77]. The synthetic process was quite fast and silver
nanoparticles were formed within 5 min of silver ions coming in contact with the cell filtrate.
It seems that nitroreductase enzymes might be responsible for bioreduction of silver ions. It
was also reported that visible-light emission could significantly increase synthesis of silver
nanoparticles (1-6 nm) by culture supernatants of K. pneumoniae [78]. Monodispersed and
stable silver nanoparticles were also successfully synthesized with bioreduction of [Ag
(NH3)2] + using Aeromonas sp. SH10 and Corynebacterium sp. SH09 [79]. It was speculated
that [Ag (NH3)2] + first reacted with OH− to form Ag2O, which was then metabolized
independently and reduced to silver nanoparticles by the biomass.
Lactobacillus strains, when exposed to silver ions, resulted in biosynthesis of nanoparticles
within the bacterial cells [80]. It has been reported that exposure of lactic acid bacteria
present in the whey of buttermilk to mixtures of silver ions could be used to grow
nanoparticles of silver [80].
Synthesis of silver nanoparticles by fungi
Silver nanoparticles (5-50 nm) could be synthesized extracellularly using Fusarium
oxysporum, with no evidence of flocculation of the particles even a month after the reaction
[81]. The long-term stability of the nanoparticle solution might be due to the stabilization of
the silver particles by proteins. The morphology of nanoparticles was highly variable, with
38
generally spherical and occasionally triangular shapes observed in the micrographs. Silver
nanoparticles have been reported to interact strongly with proteins including cytochrome c .
In UV-vis spectra from the reaction mixture after 72 h, the presence of an absorption band at
ca. 270 nm might be due to electronic excitations in tryptophan and tyrosine residues in the
proteins. In F. oxysporum, the bioreduction of silver ions was attributed to an enzymatic
process involving NADH-dependent reductase [82]. The exposure of silver ions to F.
oxysporum, resulted in release of nitrate reductase and subsequent formation of highly stable
silver nanoparticles in solution [83]. The secreted enzyme was found to be dependent on
NADH cofactor. They mentioned high stability of nanoparticles in solution was due to
capping of particles by release of capping proteins by F. oxysporum. Stability of the capping
protein was found to be pH dependent. At higher pH values (>12), the nanoparticles in
solution remained stable, while they aggregated at lower pH values (<2) as the protein was
denatured. Kumar et al. [63] have demonstrated enzymatic synthesis of silver nanoparticles
with different chemical compositions, sizes and morphologies, using α-NADPH-dependent
nitrate reductase purified from F. oxysporum and phytochelatin, in vitro. Silver ions were
reduced in the presence of nitrate reductase, leading to formation of a stable silver hydrosol
10-25 nm in diameter and stabilized by the capping peptide. Use of a specific enzyme in in
vitro synthesis of nanoparticles showed interesting advantages. This would eliminate the
downstream processing required for the use of these nanoparticles in homogeneous catalysis
and other applications such as non-linear optics. The biggest advantage of this protocol based
on purified enzyme was the development of a new approach for green synthesis of
nanomaterials over a range of chemical compositions and shapes without possible
aggregation. Ingle et al. [64] demonstrated the potential ability of Fusarium acuminatum Ell.
and Ev. (USM-3793) cell extracts in biosynthesis of silver nanoparticles. The nanoparticles
produced within 15-20 minutes and were spherical with a broad size distribution in the range
39
of 5-40 nm with the average diameter of 13 nm. A nitrate-dependent reductase enzyme might
act as the reducing agent. The white rot fungus, Phanerochaete chrysosporium, also reduced
silver ions to form nano-silver particles [65]. The most dominant morphology was pyramidal
shape, in different sizes, but hexagonal structures were also observed. Possible involvement
of proteins in synthesizing silver nanoparticles was observed in Plectonema boryanum UTEX
485 (a filamentous cyanobacterium) [66].
Stable silver nanoparticles could be achieved by using Aspergillus flavus [67]. These
nanoparticles were found to be stable in water for more than 3 months with no significant
aggregation because of surface binding of stabilizing materials secreted by the fungus [67].
Extracellular biosynthesis of silver nanoparticles using Aspergillus fumigatus (a ubiquitous
saprophytic mold) has also been investigated [68]. The resulted TEM micrograph showed
well-dispersed silver nanoparticles (5-25 nm) with variable shapes. Most of them were
spherical in nature with some others having occasionally triangular shapes [68]. Compared to
intracellular biosynthesis of nanoparticles; extracellular synthesis could be developed as a
simple and cheap method because of uncomplicated downstream processing and handling of
biomasses.
The extracellular filtrate of Cladosporium cladosporioides biomass was used to synthesize
silver nanoparticles [89]. It was suggested that proteins, organic acids and polysaccharides
released by C. cladosporioides were responsible for formation of spherical crystalline silver
nanoparticles. Kathiresan et al. [90] have shown that when the culture filtrate of Penicillium
fellutanum was incubated with silver ions and maintained under dark conditions, spherical
silver nanoparticles could be produced. They also changed crucial factors such as pH,
incubation time, temperature, silver nitrate concentration and sodium chloride to achieve the
maximum nanoparticle production. The highest optical density at 430 nm was found at 24 h
after the start of incubation time, 1 mM concentration of silver nitrate, pH 6.0, 5°C
40
temperature and 0.3% sodium chloride. Fungi of Penicillium genus was used for green
synthesis of silver nanoparticles [91]. Penicillium sp. J3 isolated from soil was able to
produce silver nanoparticles [92]. The bioreduction of silver ions occurred on the surface of
the cells and proteins might have critical role in formation and stabilization of the synthesized
nanoparticles. Sanghi et al., 2009 [93] have investigated the ability of Coriolus versicolor in
formation of monodisperse spherical silver nanoparticles. Under alkaline conditions (pH 10)
the time taken for production of silver nanoparticles was reduced from 72 h to 1 h. It was
indicated that alkaline conditions might be involved in bioreduction of silver ions, water
hydrolysis and interaction with protein functionalities. Findings of this study have shown that
glucose was necessary for the reduction of silver and S-H of the protein played an important
role in the bio reduction.
b. Synthesis of silver nanoparticles by plants
Camellia sinensis (green tea) extract has been reported to be used as a reducing and
stabilizing agent for the biosynthesis of silver nanoparticles in an aqueous solution in ambient
conditions [94]. It was observed that when the amount of C. sinensis extract was increased,
the resultant nanoparticles were slightly larger and more spherical. Black tea leaf extracts
were also reportedly used in the production of silver nanoparticles [95]. The nanoparticles
were stable and had different shapes, such as spheres, trapezoids, prisms, and rods.
Polyphenols and flavonoids seemed to be responsible for the biosynthesis of these
nanoparticles. Plant extracts from alfalfa (Medicago sativa), lemongrass (Cymbopogon
flexuosus), and geranium (Pelargonium graveolens) have served as green reducing agents in
silver nanoparticle synthesis. Harris et al., 2008 [96] have investigated the limits (substrate
metal concentration and time exposure) of uptake of metallic silver by two common
metallophytes, Brassica juncea and M. sativa. They demonstrated that B. juncea and M.
41
Sativa could be used in the phytosynthesis of silver nanoparticles. B. juncea, when exposed to
an aqueous substrate containing 1000 ppm silver nitrate for 72 h, accumulated up to 12.4 wt.
% silver. M. sativa accumulated up to 13.6 wt. % silver when exposed to an aqueous
substrate containing 10,000 ppm silver nitrate for 24 h. In the case of M. sativa, an increase in
metal uptake was observed by increasing the exposure time and substrate concentration. In
both cases, TEM analysis showed the presence of roughly spherical silver nanoparticles, with
a mean size of 50 nm. A high density of extremely stable silver nanoparticles (16-40 nm) was
rapidly synthesized by challenging silver ions with Datura metel (Solanaceae) leaf extract
[97]. The leaf extracts of this plant contains biomolecules, including alkaloids,
proteins/enzymes, amino acids, alcoholic compounds, and polysaccharides which could be
used as reductant to react with silver ions, and therefore used as scaffolds to direct the
formation of silver nanoparticles in the solution. Song and Kim in 2008 [98] elucidated the
fact that Pinus desiflora, Diospyros kaki, Ginko biloba, Magnolia kobus and Platanus
orientalis leaf broths synthesized stable silver nanoparticles with average particle size
ranging from 15 to 500 nm, extracellularly. In the case of M. kobus and D. kaki leaf broths,
the synthesis rate and final conversion to silver nanoparticles was faster, when the reaction
temperature was increased. But the average particle sizes produced by D. kaki leaf broth
decreased from 50 nm to 16 nm, when temperature was increased from 25 °C to 95 °C. The
researchers also demonstrated that only 11 min was needed for more than 90 % conversion at
the reaction temperature of 95 °C using M. kobus leaf broth [98]. It was further demonstrated
that leaf extracts from the aquatic medicinal plant, Nelumbo nucifera (Nymphaeaceae), was
able to reduce silver ions and produce silver nanoparticles (with an average size of 45 nm) in
different shapes [99]. The biosynthesized nanoparticles showed larvicidal activities against
malaria (Anopheles subpictus) and filariasis (Culex quinquefasciatus) vectors.
Silver nanoparticles were biosynthesized using Sorbus aucuparia leaf extract within 15 min.
42
The nanoparticles were found to be stable for more than 3 months. The sorbate ion in the leaf
extract of S. aucuparia encapsulated and stabilized the nanoparticles and this action seemed
to be responsible for their stability [100].
The various synthetic and natural polymers such as poly(ethylene glycol), poly-(N-vinyl-2-
pyrrolidone), starch, heparin, poly-cationic chitosan (1-4-linked 2-amino-2-deoxy-β-D
glucose), sodium alginate, and gum acacia have been reported as reducing and stabilizing
agents for biosynthesis of silver nanoparticles. It was reported that monodisperse spherical
silver nanoparticles (3 nm) could be synthesized using gum kondagogu, a non-toxic
polysaccharide, derived as an exudate from the bark of Cochlospermum gossypium) [101]. It
was suggested that carboxylate and hydroxyl groups were involved in complexation and
bioreduction of silver ions into nanoparticles. This method was compatible with green
chemistry principles as the gum serves a matrix for both Bioreduction and stabilization of the
synthesized nanoparticles. Due to availability of low cost plant derived biopolymer, this
method could be implemented for large-scale synthesis of highly stable monodispersed
nanoparticles. Spherical silver nanoparticles (40-50 nm) were produced using leaf extract of
Euphorbia hirta [102]. These nanoparticles had potential and effective antibacterial property
against Bacillus cereus and S. aureus. Acalypha indica (Euphorbiaceae) leaf extracts have
produced silver nanoparticles (20-30 nm) within 30 min [103]. These nanoparticles had
excellent antimicrobial activity against water borne pathogens, E. coli and V. cholera
(Minimum Inhibitory Concentration (MIC) = 10 μg ml-1). Moreover, silver nanoparticles (57
nm) were produced using Moringa oleifera leaf extract as reducing agent within 20 min.
These nanoparticles had considerable antimicrobial activity against pathogenic
microorganisms, including Staphylococcus aureus, Candida tropicalis, Klebsiella
pneumoniae, and Candida krusei [104]. It has been reported that cotton fibers loaded with
biosynthesized silver nanoparticles (~20 nm) using natural extracts of Eucalyptus citriodora
43
and Ficus bengalensis had excellent antibacterial activity against E. coli. These fibers had
potential for utilization in burn/wound dressings as well as in the fabrication of antibacterial
textiles and finishings [105]. Garcinia mangostana leaf extract has been used as reducing
agent to synthesize silver nanoparticles with high effective antimicrobial activity against E.
coli and S. aureus [106]. It was reported that Ocimum sanctum leaf extract could bioreduce
silver ions into crystalline silver nanoparticles (4-30 nm) within 8 min of reaction time. These
nanoparticles were stable due to the presence of proteins which may act as capping agents. O.
sanctum leaves contain ascorbic acid which may play an important role in reduction of silver
ions into metallic silver nanoparticles. These nanoparticles have shown strong antimicrobial
activity against E. coli and S. aureus [107]. Green synthesis of silver nanoparticles using
Cacumen platycladi extract was also investigated. Reducing sugars and flavonoids in the
extract seemed to be mainly responsible for reduction of silver ions, and their reductive
capability promoted at 90 °C, leading to formation of silver nanoparticles (18.4 ± 4.6 nm)
with narrow size distribution. The produced nanoparticles had significant antibacterial
activity against both gram negative and gram positive bacteria (E. coli and S. aureus) [108].
1.5.2 Reducing agents in the synthesis of silver nanoparticles
Chemical reduction of metal salts using various reducing agents in the presence of
stabilizer is currently of interest in the preparation of silver nanoparticles. Reducing agents
such as sodium Borohydride (NaBH4), hydrazine (N2H4), formaldehyde, etc. can be used to
reduce a silver containing salt to produce nanosilver particles [109]. Some reducing agents
used in synthesis of silver nanoparticles are β- D- glucose [61,110], ethylene glycol [110],
sodium borohydride [111] ,and aniline [112] . Other chemicals that have been used as
reducing agents include ethanol [113], citrate [114] and hydrallazine [115].
The use of plants and microorganisms in the synthesis of nanoparticles emerge as an
eco-friendly and exciting approach (116,117). In recent times, biosynthetic methods
44
employing both biological microorganism such as bacteria (118) and fungus [119]] or plants
extracts [120, 121] have emerged as a simple and viable alternative to more complex
chemical synthetic procedures to obtain nanomaterials. Extracts from microorganisms may
act both as reducing and capping agents in silver nanoparticles (Ag NPs) synthesis. The
reduction of Ag+ ions by combinations of biomolecules found in these extracts such as
enzymes or proteins, amino acids, polysaccharides, and vitamins [122] is environmentally
benign, yet chemically complex.
The bioreduction of aqueous silver ions with a culture supernatant of non pathogenic
bacterium, Bacillus licheniformis [74] had been mentioned earlier. Well-dispersed silver
nanocrystals (50 nm) have also been synthesized using the bacterium Bacillus licheniformis
[75]. Other microorganisms used in synthesis of silver nanoparticles include Bacillus subtilis
[76], Klebsiella pneumonia, Escherichia. coli, and Enterobacter cloaca [77].
Lactobacillus strains, when exposed to silver ions, resulted in biosynthesis of nanoparticles
within the bacterial cells [80].Silver nanoparticles has also been synthesized using Fusarium
oxysporum, which served both as reducing and stabilizing agent [81 -83]. The long-term
stability of the nanoparticle solution might be due to the stabilization of the silver particles by
proteins. The extracellular filtrate of Cladosporium cladosporioides biomass has been used to
synthesize silver nanoparticles [89]. It was suggested that proteins, organic acids and
polysaccharides released by C. cladosporioides were responsible for formation of spherical
crystalline silver nanoparticles. Kathiresan et al. [90] have shown that when the culture
filtrate of Penicillium fellutanum was incubated with silver ions and maintained under dark
conditions, spherical silver nanoparticles was produced.
Plants extract from Ocimum tenuiflorum, Solanum tricobatum, Syzygium cumini,
Centella asiatica and Citrus sinensis were use as reducing agents in the synthesis of silver
nanoparti-cles (Ag NPs) from silver nitrate solution.[123] The highest antimicrobial activity
45
of silver nanoparticles synthesized by S. tricobatum, O. tenuiflorum extracts was found
against Staphylococcus aureus (30 mm) and E. coli (30 mm) respectively [124]. Camellia
sinensis (green tea) extract has been used as a reducing and stabilizing agent for the
biosynthesis of silver nanoparticles in an aqueous solution in ambient conditions [94]. Plant
extracts from alfalfa (Medicago sativa), lemongrass (Cymbopogon flexuosus), and geranium
(Pelargonium graveolens) have served as green reducing agents in silver nanoparticle
synthesis. Song and Kim in 2008 [98] elucidated the fact that Pinus desiflora, Diospyros kaki,
Ginko biloba, Magnolia kobus and Platanus orientalis leaf broths synthesized stable silver
nanoparticles with average particle size ranging from 15 to 500 nm, extracellularly. Nelumbo
nucifera (Nymphaeaceae), was able to reduce silver ions and produce silver nano [99]. Silver
nanoparticles have also been synthesized using Sorbus aucuparia leaf extract [100], Acalypha
indica [103]. The various synthetic and natural polymers such as poly(ethylene glycol), poly-
(N-vinyl-2- pyrrolidone), starch, heparin, poly-cationic chitosan (1-4-linked 2-amino-2-
deoxy-β-D glucose), sodium alginate, and gum acacia have been reported as reducing and
stabilizing agents for biosynthesis of silver nanoparticles [101]
1.5.3 Stabilizing agents in the synthesis of silver nanoparticles
Stabilizing agents are basically used to protect nanoparticles and prevent aggregation
or agglomeration of particles. A number of chemicals can be used as stabilizing agents in the
synthesis of Silver nanoparticles. Also in the method of Patakfalvi and Dékány, citrate
present in the solution played an important role in the stabilization of the silver nanoparticles
formed [125]. If no sodium citrate was added to the solution, the silver particles formed
would aggregate and form precipitate. Another stabilizing agent is gallic acid, which acts as
both a reducing agent and stabilizer. In this case, the oxidation reaction of phenol groups in
gallic acid was responsible for the reduction of silver ions. The produced quinoid compound
with a keto enol-system could be adsorbed on the surface of silver nanoparticles [126]. Other
46
stabilizers used are; sodium dodecyl sulphate (SDS) [127] and cetyl trimethyl ammonium
bromide (CTAB) [128]. However, the most commonly applied stabilizers and protective
agents in nanoparticles synthesis are polymers: gelatin, D-sorbitol, polyvinylpyrrolidone
(PVP) [129,130], polyvinyl alcohol (PVA) [131] and polymethylvinylether (PMVE)) [130].
Among all polymer stabilizers of silver nanoparticles, poly–N-vinylpyrrolidone is considered
an excellent dispersant as it exhibits favourable protecting properties owing to its unique
structure [112,113,114]. PVP on one hand promotes the nucleation of AgNPs and on the
other hand it also effectively stabilizes the dispersed silver nanoparticles [134,135].
1.6 Why ecofriendly (green) synthesis
Generally, most of the metallic nanoparticles have been synthesized using chemical
techniques with toxic and hazardous concerns [136]. Therefore there is a growing need to
develop environment friendly synthesis techniques without using toxic chemicals [136]. A
simple, green/eco-friendly and chemical free biosynthesis of silver nanoparticles using
Azadiruchta indica leaf (neem) extract as reducing agent was employed in this research.
Although, silver nanoparticles can be synthesized by a number of physical and chemical
methods [137,138], many of these techniques are either expensive or involve the use of
hazardous chemicals. Bio-synthesis of nanoparticles is a fast growing research in
nanotechnology. In recent times, plant extract have been used as reducing and capping agent
for the synthesis of nanoparticles. The use of plant extract is more advantageous because it
does not require elaborate processes such as intracellular synthesis and multiple purification
steps or the maintenance of microbial cell culture [139]. The biosynthesis of silver
nanoparticles using Cissus quadrangularis [140], Catharanthus roseus [141], Cinnamomum
camphora [142], Nicotiana tobaccum [143] and Elettaria Cardamomom [144] etc. have been
reported in literature.
47
The aim of the present study is to synthesize silver nanoparticles using Azadiruchta indica
leaf extract as reducing agent which is cost effective and eco-friendly.
1.7. Characterisation of silver nanoparticles
Characterization of nanoparticles is essential to appreciate and control nanoparticles
synthesis and applications [145] Nanoparticles characterization is carried out using a range of
diverse methods like scanning and transmission electron microscopy (SEM, TEM), Fourier
transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and atomic
force microscopy (AFM). Other techniues include dynamic light scattering (DLS), powder X-
ray diffractometry (XRD), and UV– Vis spectroscopy [145]. These techniques assist in
resolving diverse parameters such as particle size, shape, crystallinity, fractal dimensions,
pore size and surface area. The morphology and particle size possibly will be determined by
TEM, SEM and AFM. The improvement of AFM over conventional microscopes such as
SEM and TEM is that AFM technique measures 3D images, so that particle height and
volume can be intended. Moreover, dynamic light scattering is applied for determination of
particles size distribution. Furthermore, X-ray diffraction is used for the determination of
crystallinity, while UV– Vis spectroscopy is utilized to confirm sample formation by
exhibiting the Plasmon resonance [146 - 148].
UV-Vis Analysis:
The optical property of silver nanoparticles is usually determined by UV-Vis
spectrophotometer. After the addition of aqueous silver nitrate to the plant extract, the
spectras are taken to determine the surface Plasmon resonance at 200 nm to 700 nm. Values
between 280 and 500 nm usually confirm the formation of silver nanoparticle (146)
48
Fourier transform infra red (FTIR) analysis:
The chemical composition of the synthesized silver nanoparticles is studied by using
FTIR spectrophotometer. FTIR spectral measurement are also performed to assess the
coupling of the polymers to drug loaded nanoparticles .The solutions are normally dried and
the resultant powders characterized in the range 4000–400 cm- 1 (145)
XRD Analysis:
The phase variety and grain size of synthesized Silver nanoparticles can be
determined by X-ray diffraction (145).
Scanning Electron microscopy:
Scanning electron microscopy (SEM) provides morphological examination with direct
visualization. The techniques based on electron microscopy offer several advantages in
morphological and sizing analysis; however, they provide limited information about the size
distribution and true population average [149]. For SEM characterization, nanoparticles
solution are first converted into a dry powder, and mounted on a sample holder followed by
coating with a conductive metal, such as gold, using a sputter coater. The sample is then
scanned with a focused fine beam of electrons [150]. The surface characteristics of the
sample are obtained from the secondary electrons emitted from the sample surface. The
nanoparticles should withstand vacuum, and the electron beam can damage the polymer. The
mean size obtained by SEM is comparable with results obtained by dynamic light scattering
[149]
49
Transmission electron microscope:
TEM operates on different principle than SEM, yet it often brings same type of data
[149]. The sample preparation for TEM is complex and time consuming because of its
requirement to be ultra thin for the nelectron transmittance. The nanoparticles dispersion is
deposited onto support grids or films. To make nanoparticles withstand the instrument
vacuum and facilitate handling, they are fixed using either a negative staining material, such
as phosphotungstic acid or derivatives, uranyl acetate, etc, or by plastic embedding. Alternate
method is to expose the sample to liquid nitrogen temperatures after embedding in vitreous
ice. The surface characteristics of the sample are obtained when a beam of electrons is
transmitted through an ultra thin sample, interacting with the sample as it passes through
[149]
Atomic force microscopy:
Atomic force microscopy (AFM) provides ultra-high resolution in particle size
measurement and is based on a physical scanning of samples at sub-micron level using a
probe tip of atomic scale [149]. The equipment provides a topographical map of sample
based on forces between the tip and the sample surface. Samples are usually scanned in
contact or noncontact mode depending on their properties. In contact mode, the topographical
map is generated by tapping the probe on to the surface across the sample and probe hovers
over the conducting surface in non-contact mode. The prime advantage of AFM is its ability
to image non-conducting samples without any specific treatment, thus allowing imaging of
delicate biological and polymeric nano and microstructures [151] AFM provides the most
accurate description of size and size distribution and requires no mathematical treatment.
Moreover, particle size obtained by AFM technique provides real picture which helps
understand the effect of various biological conditions
50
Dynamic light scattering & Zeta-Potential Analysis:
Dynamic light scattering (DLS) which is based on the laser diffraction method with
multiple scattering techniques is used to study the average particle size of silver
nanoparticles. Currently, the fastest and most popular method of determining particle size is
photon-correlation spectroscopy (PCS) or dynamic light scattering (DLS) [149]. DLS is
widely used to determine the size of Brownian nanoparticles in colloidal suspensions in the
nano and submicron ranges. Shining monochromatic light (laser) onto a solution of spherical
particles in Brownian motion causes a Doppler shift when the light hits the moving particle,
changing the wavelength of the incoming light. This change is related to the size of the
particle. It is possible to extract the size distribution and give a description of the particle’s
motion in the medium, measuring the diffusion coefficient of the particle and using the
autocorrelation function. . The photon correlation spectroscopy (PCS) represent the most
frequently used technique for accurate estimation of the particle size and size distribution
based on DLS [152].
Kinetic modeling
In order to understand the kinetic and mechanism of drug release, the result of in vitro
drug release study of nanoparticles is fitted with various kinetic equations like zero order
(cumulative % release vs. time), first order (log % drug remaining vs time), Higuchi’s model
(cumulative % drug release vs. square root of time). r2 and k values are calculated for the
linear curve obtained by regression analysis of the above plots. For mechanism of release, the
diffusion coefficient (n) is calculated from the slope of the plot log cumulative % drug release
vs. log time.
51
1.8 Metformin HCl
Metformin hydrochloride (MET) is a highly water-soluble anti-hyperglycemic agent
used in the treatment of type 2 non-insulin-dependent diabetes mellitus. It is a BCS class III
(high solubility, low permeability) drug. Its relatively low (50 – 60 %) bioavailability,
together with its short and variable biological half-life (1.5 – 4.5 h) [153] require repeated
administrations of high doses ( 1.5 – 2.0 g / day ) to maintain effective plasma concentrations,
thus reducing patient compliance and/or enhancing the incidence of side-effects. There is
continual effort among Pharmaceutical Scientists and researchers to improve the formulation
of Metformin to achieve optimal therapy.
1.9. Polymers used in this research
The various polymers used in this research are discussed below;
1.9.1. Guar gum
Guar gum is a water soluble polysaccharide extracted from the seeds of Cyamopsis
tetragonoloba, which belongs to Leguminosae family. It is a non-ionic natural polysaccharide
derived from the ground endosperm of guar beans. Its backbone consists of linear chains of (1
→ 4)-β-D-mannopyranosyl units with α-D-galactopyranosyl units attached by (1 → 6)
linkages , forming short side-branches [154]. Guar gum hydrates in cold water to form a
highly viscous solution in which the single polysaccharide chains interact with each other in a
complex way [155]. Its nine hydroxyl groups are available for the formation of hydrogen
bonds with other molecules, but it remains neutrally charged due to the absence of
dissociable functional groups. Extreme pH and high temperature conditions (e.g. pH 3 at
50°C) degrade its structure [156]. It remains stable in solution over pH range 5-7. Strong
acids cause hydrolysis and loss of viscosity, and alkalis in strong concentration also tend to
reduce viscosity. It is insoluble in most hydrocarbon solvents.
52
As the guar gum polymer is a low-cost, easily available and non-toxic polysaccharide, it is
widely applied in many industrial fields. Due to its high viscosity in aqueous solutions, it is
commonly used as a thickening agent in cosmetics and in sauces, salad dressings and ice
creams in the food industry [155]). In pharmaceuticals, guar gum is used in solid dosage
forms as a binder and disintegrant, and it has also been used as hydrophilic matrix, for
designing oral controlled release dosage forms [154]. Guar gum has been extensively used for
colon delivery due to its drug release retarding property and susceptibility to microbial
degradation in the large intestine [157].
Chemically modified forms of the gum can be used with the aim of changing its intrinsic
characteristics of solubility, viscosity and rheological behaviour. For instance, hydrossilalchyl
derivatives, which are often, used for the formulation of cements and plasters, or
carboxymethyl derivatives, which are employed as thickening agents.
Little information is available in the literature for the possibility of using guar gum
based nanosized materials as drug carriers due to its solubility in water, what makes difficult
to use it as adsorbent in aqueous conditions. Some researchers have incorporated to its
structure some compounds like silica, in order to obtain insoluble compounds which could act
as adsorbents in aqueous media [158]. Moreover, guar gum-based nanosystems have been
prepared by nanoprecipitation and cross-linking methods [157]. A different application of this
polysaccharide has been found as stabilizer of nanosuspension, where the presence of guar
gum during the synthesis process allows the achievement of a better stability of the
nanoparticles [156].
Little information is available in the open literature for the possibility of using guar gum in
the formulation of nanoparticles. Few attempts [154, 159-161) made did not highlight the use
of guar gum in green synthesis of nanoparticles.
53
1.9.2. Xanthan gum
Xanthan gum is a high molecular weight natural polysaccharide produced by fermentation
process. It consists of 1, 4-linked β-D-glucose residues, having a trisaccharide side chain
attached to alternate D-glucosyl residues [162]. Although the gum has many properties
desirable for drug delivery, its practical use is mainly confined to the unmodified forms due
to slow dissolution and substantial swelling in biological fluids. Xanthan gum has been
chemically modified by conventional chemical methods like carboxymethylation, and
grafting such as free radical, microwave-assisted, chemoenzymatic and plasma assisted
chemical grafting to alter physicochemical properties for a wide spectrum of biological
applications [162]
Several researchers have reported the suitability of xanthan gum in colon delivery
[163 – 170]. Although there is little report on the use of xanthan gum in formulation of
nanoparticles for drug delivery [171 – 173], there is no reported work on the use of xanthan
gum in green synthesis of nanoparticles.
1.9.3. Starch
Starch is an inexpensive, biodegradable, and renewable biopolymer that is synthesized
in granule shapes [174]. As polysaccharides, it contains amylose and amylopectin [175]. Due
to its biodegradability, abundance and low cost, starch has been widely used as excipients for
tabletting and drug delivery carriers [176]. Nano-sized starch particles have attracted much
attention due to their unique properties that are different significantly from their bulk
materials. The use of a high pressure homogenization method to prepare corn starch
nanoparticles with yield of almost 100% has been reported [177]. However, their synthesis
method did not allow proper control of particle sizes.
54
Several researchers [178 - 184] have also used starch in the synthesis of silver
nanoparticles.
1.9.4. Sodium alginate
Alginates are random anionic, linear, polymers consisting of varying ratio of
glucuronic and manuronic acid unit. Salts of alginate are formed when metal ion react with
glucuronic or manuronic acid residue. Alginate has been used in many biomedical
applications, including drug delivery systems, as they are biodegradable, biocompatible and
mucoadhesive [185] Alginate has a variable molecular weight, depending on the enzymatic
control during its production and the degree of depolymerization caused by its extraction.
Due to its abundance, low price and non-toxicity, alginate has been extensively used in
different industries. For instance, it has been used as food additive and thickener in salad
dressings and ice-creams in the alimentary industry [186]. Moreover, the biocompatibility
behaviour and the high functionality make alginate a favorable biopolymer material for its
use in biomedical applications, such as scaffolds in tissue engineering [187], immobilization
of cells [188], and controlled drug release devices [189]. In case of its applications in
nanomedicine, alginate has also been extensively investigated as a drug delivery device in
which the rate of drug release can be modified by varying the drug polymer interaction, as
well as by chemical immobilization of the drug in the polymer backbone using the reactive
carboxylate groups [186]. Apart from its easy functionalization due to its reactive structure,
there are many advantages and favourable properties of alginate for its use in drug delivery. It
is a natural polymer compatible with a wide variety of substances, which does not need
multiple and complex drug-encapsulation process. Moreover, it is mucoadhesive and
biodegradable and, consequently, it can be used in the preparation of controlled drug-delivery
systems achieving an enhanced drug bioavailability [189]. Therefore, the biocompatibility,
55
availability and versatility of this polysaccharide make it an important and hopeful tool in the
field of nanomedicine, especially in the preparation of nanoparticulate drug delivery systems.
1.10 Objectives of study
This study aims at the following;
1. Preparation of native aqueous extract of Azadirachta indica leaves and use of same as
ecofriendly reducing agent in the synthesis of silver nanoparticles.
2. Stabilization of silver nanoparticles using four polymers; acetylated starch, guar gum,
xanthan gum and sodium alginate.
3. Preparation of nanodrug delivery composites of metformin HCL using all 4 polymers
4. Characterization of the metformin nanocomposites using zeta size, SEM and
Polydispersity.
5. Antimicrobial property of the optimized nanocomposites
6. In vivo anti hyperglycemia property of the optimized Metformin nanocomposite using
glucose hyperload model
56
CHAPTER TWO
MATRIALS AND METHODS
2.1 Materials
Metformin HCl, guar gum and xanthan gums were purchased from sigma Aldrich, U
S A. Sodium alginate was obtained from BDH chemicals, England. Acetylated maize Starch
(AMS) was prepared in Advanced Biology/Physics Laboratory, Centre for Nanomedicine and
Biophysical Research, NIH- NIARD/ NIPRD, Abuja, Nigeria. Other chemicals and reagents
include Sodium hydroxide pellets, Monobasic potassium phosphate (BDH chemicals,
England), hydrochloric acid , acetic anhydride(Sigma Aldrich, U S A).
2.2 Preparation of silver nitrate solution
A 0.1 g quantity of silver nitrate was weighed and transferred to a beaker. Distilled
water was added to make 10 ml of 1 % w/v of silver nitrate solution. This was used as a silver
precursor in the synthesis of nanoparticles.
2.3. Synthesis of AMS
20 g of corn starch BP was dispersed in 50 mL of distilled water in a 250 mL beaker
to provide a starch-water ratio of 2 : 5. The starch slurry was mixed for 1 h at room
temperature to fully suspend the starch granules. After adjusting the pH to 8.0 with 1 M
aqueous sodium hydroxide, acetic anhydride (8%, w/w, on a starch dry basis) was added drop
wise. Sodium hydroxide (1 M) was added simultaneously at a rate sufficient of 20 mL/min to
maintain the pH of the suspension between 7.8 to 8.2 during the reaction. The reaction was
allowed to proceed for 60 min at the completion of acetic anhydride addition. The slurry was
adjusted to pH 5.5 with 1 M hydrochloric acid to end the reaction. The slurry was vacuum-
filtered and the resulting cake mixed with 40 mL of distilled water and refiltered. The
57
resultant cake was washed three times with distilled water to remove residual acid and then
oven dried overnight at 40 o C. The synthesized starch (AMS) was stored for subsequent use.
2.4 Synthesis of Silver nanoparticles using Azadirachta indica extract
1, 3 and 5 % modified Starch (AMS) were prepared by dispersing 1g, 3g and 5 g in
100ml of distilled water respectively and maintained at 40 0 C in a water bath. To each of the
starch dispersions, 10 mL of 1 % silver nitrate ( AgNO3 ) was added under constant stirring
using a magnetic stirrer assembly for 5 min, followed by incorporation of metformin HCl to
obtain [Ag (Drug/AMS)] + dispersion. .A 40 ml aliquot of a freshly prepared Azadirachta
indica (neem) extract (reducing agent) was then added to the resultant mixture and
maintained at a temperature of 40 0C for 24 h. The resultant suspension of Ag/drug/AMS
bionanocomposite was lyophilized (Virtis 2KBTXL-75 Benchtop SLC Freeze Dryer) and
subjected to further analysis.The same procedure was repeated for 1, 3 and 5 % guar gum,
xanthan gum and sodium alginate respectively. The composition of the nanoparticle
synthesized is shown in table 1
2.5 Characterisation of Silver nanocomposites
2.5.1. UV – vis spectroscopy to determine surface Plasmon resonance for silver
nanoparticles
UV‐vis spectral analysis was done using a double‐beam spectrophotometer
(Hitachi, U‐3010) with the samples dispersed in distilled water and kept in a quartz cuvette
with a path length of 10 mm. The photoluminescence emission spectra from the samples
(dispersed in distilled water) were recorded by a spectrofluorometer (LS 55, Perkin Elmer) at
room temperature using a four sided polished quartz cuvette with a path length of 10 mm.
58
Table 1: Composition of Nanocomposites
Batches Drug(g) AMS(g) Guar gum(g)
Xanthan gum(g)
Sodium alginate(g)
AMS1% NANOmet
0.500 1.000 - - -
AMS3% NANOmet
0.500 3.000 - - -
AMS5% NANOmet
0.500 5.000 - - -
GG1% NANOmet
0.500 - 1.000 - -
GG3% NANOmet
0.500 - 3.000 - -
GG5% NANOmet
0.500 - 5.000 - -
XG1% NANOmet
0.500 - - 1.000 -
XG3% NANOmet
0.500 - - 3.000 -
XG5% NANOmet
0.500 - - 5.000 -
NaALG1% NANOmet
0.500 - - - 1.000
NaALG3% NANOmet
0.500 - - - 3.000
NaALG5% NANOmet
0.500 - - - 5.000
KEY:
AMS1%NANOmet = 1%W/V modified starch (AMS) and Metformin HCl
AMS3%NANOmet = 3%W/V modified starch (AMS) and Metformin HCl
AMS5%NANOmet = 5%W/V modified starch (AMS) and Metformin HCl
GG1%NANOmet = 1%W/V Guar gum and Metformin HCl
GG3%NANOmet = 3%W/V Guar gum and Metformin HCl
GG5%NANOmet = 5%W/V Guar gum and Metformin HCl
XG1%NANOmet = 1%W/V Xanthan gum and Metformin HCl
XG3%NANOmet = 3%W/V Xanthan gum and Metformin HCl
XG5%NANOmet = 5%W/V Xanthan gum and Metformin HCl
NaALG1% NANOmet = 1%W/V Sodium alginate and Metformin HCl
NaALG3% NANOmet = 3%W/V Sodium alginate and Metformin HCl
NaALG5% NANOmet = 5%W/V Sodium alginate and Metformin HCl
59
2.5.2. Percent yield of nanoparticles
The percentage yield was calculated by dividing the actual yield by the initial weight
of sample and multiplying the result by 100 percent. The actual yield was the weight of the
nanoparticles while the initial yield was the combined weights of the drug and the polymer in
a beaker measured on a weighing balance
2.5.3. Entrapment efficiency and loading capacity
A 50 mg quantity of the nanocomposite was dissolved in 50 ml of Phosphate buffer
(pH 6.8). The suspension was centrifuged at 1500 rpm at 4 ° C for 30 min. The supernatant
was analysed for metformin at 232nm. The loading capacity and entrapment efficiency were
calculated for each nanocomposite using the formulae below
Loading Capacity (L.C) = {weight of drug in the nanocomposite – weight of drug in the
supernatant) /weight of nanocomposite x 100
Entrapment Efficiency (E.E) = (weight of drug in the nanocomposite – weight of drug in the
supernatant)/weight of drug in nanocomposite x 100
2.5.4. Determination of Particle size and Polydispersity Index
The mean particle size (Z-average), Polydispersity Index (Pdi) and zeta potential of
the nanoparticles were determined by dynamic light scattering technique using a Zetasizer
Ver:7.01 (Nano Zs 90, Malvern Instruments Ltd, UK) .The freeze dried nanocomposite
samples were dispersed in distilled water to obtain a proper scattering intensity before
measurements at 25°C. Triplicate determinations were made.
60
2.5.5. Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis
Thermogram of drug- polymer was employed (`DSC-Shimadzu 50) for the
determination of glass transition temperature (Tg). About 1 mg of sample was placed in
aluminium pan and scanned over a temperature range of 25-250 0° C at the rate of 50 ° C/
min. Each sample was subjected to three consecutive DSC scans. Tg was determined by the
midpoint of endothermic changes associated with the glass transition. Thermogravimetric
analyses were carried out (TG 209 F3 Tarsus® - Thermo-Microbalance (TGA -
Thermogravimetric Analyzer). About 10mg sample was positioned in silica pans and the
samples were heated at 10 °C / minute to a temperature of 600 °C. Thermal analysis was
performed under nitrogen flow.
2.5.6. Morphological Studies of NANOmet using Scanning Electron Microscopy (SEM)
The nanoparticles were examined by Scanning Electron Microscope (SEM), Hitachi
X650, Tokyo, Japan). The SEM images of lyophilised nanoparticles mounted on metal stubs
and spattered with gold were taken. SEM gave high resolution images on the surface of the
samples.
2.6 In-vitro drug release studies
Drug release studies were carried out separately in both simulated gastric fluid (pH 1.2 -
acid buffer) and phosphate-buffered saline (PBS) solution (pH 7.4) using beaker magnetic
stirrer assembly at 50 rpm at a temperature of 37±1 0 C. At 30 min intervals 5 ml samples
were withdrawn and analysed at 232 nm for metformin. A 5 ml volume of fresh dissolution
medium was added to maintain sink conditions after each withdrawal. Statistical
comparisons of the release parameters of nanocomposites were done using SPSS V 17.
61
2.6 1. In vitro release kinetic evaluation
The dissolution data of each batch were fitted to various kinetic equations and
mechanism of drug release investigated. Equation (1), (2), (3), (4) represent Zero order, First
order, and Korsmeyer-Peppas model respectively.
Qt = K0 t ---------------------------------------------------------(1)
In Qt = In Q0 – K1t--------------------------------------------- (2)
Qt = Kh t1/2------------------------------------------------------- (3)
Mt / Mα = Kptn ----------------------------------------------------(4)
Where, Qt is the percentage of drug released at time t, Q0 is the initial amount of drug present
in the formulation and K0, K1, Kh, KHC, KP are constants. Regression coefficient (R2) was
determined from the slope of the following plots: Cumulative % drug released Vs Time (Zero
order kinetic models), Log cumulative of % drug remaining Vs Time (First order kinetic
model), Cumulative % of drug released Vs Square root of Time (Higuchi model), and Log
cumulative % drug release Vs Log time (Korsmeyer- Peppas model) [190,191]. In
Korsmeyer- Peppas model, first 60% of drug release was fitted and release exponent “n” was
calculated which is indicative of drug release mechanism. According to Korsmeyer- Peppas
model, if ‘n’ is 0.45 then drug release will follow Fickian diffusion , for 0.45 < n < 0.89,
release is anomalous (non- Fickian) diffusion, for n = 0.89 release is considered as case II
transport and for n > 0.89 diffusion mechanism is super case II transport [192].
2.7. Antimicrobial Studies of Nanocomposites
The Minimum inhibitory concentration of GG5%NANOmet, NaAlG5%NANOmet,
XG5%NANOmet and AMS5%NANOmet were determined.
62
2.7.1 Microorganisms used:
Six test micro organisms were used for the study; one typed and five clinical isolates
obtained from Department of Microbiology and Biotechnology, National Institute for
Pharmaceutical Research and Development, Abuja, Nigeria. Gram-positive species used were
Staphylococcus aureus and M. tuberculosis while Escherichia coli, Psuedomonas
aeruginosa, Salmonella paratyphi ATCC 9150 and Klebsiella pneumonia were the Gram-
negative species. Candida albicans represented the fungal species. Their identities were
confirmed by their morphological characteristics on specific media, followed by biochemical
tests.
2.7.2 Drugs
Ciprofloxacin (Bayer), rifampicin, fluconazole (Sigma Aldrich, USA)
2.7.3 Preparation of stock samples suspension:
The samples were dissolved in distilled water to obtain a stock concentration of
10000µg/ml. The final concentration of samples in the well was 5000 µg/ml. Ciprofloxacin
(Bayer) was prepared to a final concentration of 16 µg/ml and served as the positive drug
control against bacterial strains. Rifampicin (Sigma) was prepared at a concentration of 5
µg/ml. Fluconazole powder (Sigma- Aldrich) at a concentration of 16µg/ml was used as
positive control against fungal isolates.
2.7.4. Preparation of innoculum:
Inocula were prepared by direct colony suspension as recommended by CLSI [193]
Strains of bacteria were inoculated in Mueller Hinton agar and incubated at 35°C ± 2 °C for
18 to 24 hours. Microbial suspensions in sterile saline solution were prepared from direct
colonies. These suspensions were adjusted to a turbidity level of 0.5 McFarland approx.
1.5x108 CFU/mL [194].
63
2.7.5. Determination of Minimum Inhibitory Concentration (MIC):
The minimum inhibitory concentration (MIC) of test microorganisms and reference
antibiotics were determined by tetrazolium microplate assay which were slightly modified
from serial broth microdilution method [195]. This assay was performed using round bottom
96-well clear microtitre plates. The wells in row A of each column were left blank and the
last seven wells from rows B- H were filled with 50μl of sterilized Muller Hinton broth.
Working solution of samples were added to the wells in rows A and B of each column and an
identical two-fold serial dilution were made from rows B to row H. The last wells in rows H
served as drug-free controls. Lastly, 50μL of bacterial and fungal inoculum were added in all
the wells from column 1 to 12 and mixed thoroughly to give final concentrations ranging
from 5000 μg/ mL - 78.125μg/ mL. Tests were done in triplicates. The cultured microplates
were sealed with parafilm and incubated at 37 °C for 24 h for bacterial and yeast species. The
MIC of samples was detected following addition of 50μL of 0.2mg/ mL p-
iodonitrotetrazolium chloride in all the wells (INT, Sigma-Aldrich, USA) and incubated at
37°C for 30 min. Microbial growth were determined by observing the change of color of
piodonitrotetrazolium chloride (INT) in the microplate wells (pinkish-red formazan when
there is growth and clear solution when there is no growth). MIC was defined as the lowest
sample concentration showing no color change (clear) and exhibited complete inhibition of
bacterial / fungal growth.
2.8. Oral glucose loading animal model
This method is often referred to as physiological induction of diabetes mellitus
because the blood glucose level of the animal is transiently increased with no damage to the
pancreas. In the clinical setting, it is known as Glucose Tolerance Testing (GTT): a standard
procedure often used for the diagnosis of border line diabetic patients. In this procedure, the
64
animals are fasted overnight, then oral glucose load (1- 2.5 g/kg body weight) is given and
blood glucose level is monitored over a period of time. Usually rabbits or male rats are used
[196]
2.8.1. Experimental animals
Eighteen wistar albino rats weighing between 150-225 g were obtained from the
Animal Facility Centre in National Institute for Pharmaceutical Research and Development
(NIPRD), Abuja, Nigeria and used for the study. They were grouped into 6 (six) consisting of
3 animals per cage, maintained at room temperature, 50% relative humidity. The rats were
allowed free access to water and commercially produced diet (Ladokun Feed Ltd.) ad libitum.
The animals were treated according to the international guidelines for the care of and use of
laboratory animals. Selection Criteria for animals:
1. All the animals used for the study were healthy and active in their cage.
2. Animals were male Wistar rats.
3. Weight of the animal used was 150-225 grams.
The animals were grouped as stated below; Group I Normal control rat (Normal saline)
Group II AMS5%NANOmet (500 mg/kg )
Group III NaALG5%NANOmet (500 mg/kg )
Group IV XG5%NANOmet (500 mg/kg )
Group V Metformin (500 mg/kg)
Group VI GG5%NANOmet (500 mg/kg )
2.8.2 Effects of Nanocomposites on Glucose loaded hyperglycemic rats
Prior to the test, rats were fasted for 18 h. Normal Saline (control), AMS5%NANOmet (500
mg/kg ), NaALG5%NANOmet (500 mg/kg ), XG5%NANOmet (500 mg/kg ) a reference
65
drug, Metformin (500mg), GG5%NANOmet (500 mg/kg ) were orally administered to
groups of five rats each. Glucose (1.5 g/kg) was orally administrated to each rat. Blood
samples were taken from tail veins at 0, 15, 30, 60, 90, and 120 min after the glucose meal for
the assay of glucose with ACUU – CHEK glucometer and corresponding test strips.
66
CHAPTER THREE
RESULTS AND DISCUSSIONS
3.1. UV – vis spectroscopy
The spectra for optimized batches are shown in Figures 1 to 4.
For AMS5%NANOmet, GG5%NANOmet and NaALG5%NANOmet, the surface plasmon
resonance (SPR) occurred at 371nm while for XG3%NANOmet, the SPR was at 335nm.
Initially the aqueous solution of silver nitrate was colourless. When the silver nitrate solution
was mixed with azadirachta indica extract, its colour changed to pale yellow within 1
minute and after 24 h the colour of the solution changed from pale yellow to yellowish brown
indicating the formation of silver nanoparticles which was confirmed by using ultra violet
visible spectroscopy (Figures 1 -4) [197]..
The silver nanoparticles exhibited reddish brown colour in aqueous solution due to
excitation of surface plasmon resonance. The colour change to dark-brown was due to
increased concentration as well as growth of silver nanoparticles. The UV-Vis spectrum of
reaction medium (Figures 1 to 4) shows an emission peak at 335 to 371nm, which
corresponds to the absorbance of silver nanoparticles and reveals that the nanoparticles were
well dispersed in the aqueous solution and there is no evidence for aggregation in UV-Vis
absorption spectrum [198].
3.2 Percentage yield of nanocomposites
The percentage yields of the various nanocomposites formulations are presented in
table 2. GG1%NANOmet which consists of 1%w/v Guar gum and Metformin, had the
highest percentage yield (99.87) while AMS1% NANOmet and AMS 3% NANOmet
consisting of 1%W/V and 3 % W/V of Acetylated modified Starch (AMS) respectively had
67
the least yield (80%) . There was significant (P<0.05) difference in the percentage yield of
the nanoparticles prepared from AMS1%, AMS 3% and AMS 5%. The increase percentage
yield may be due to increase in polymer concentration [177].
Among nanocomposites synthesized with Xanthan gum as stabilizing polymer, there was no
significant (P>0.05) difference in their percentage yield (XG1%NANOmet = 90±0.58,
XG3%NANOmet = 89.13±0.47 and XG5%NANOmet = 89.40±0.12)
3.3 : Entrapment Efficiency and Loading Capacity.
The entrapment efficiencies and loading capacities of the nanocomposites are shown in Table
3. The entrapment efficiency was above 69 % for all the formulations. Generally, there was
significant (P < 0.05) increase in entrapment efficiency with increase in polymer
concentration. The reverse was observed for the loading capacity; the increase in polymer
concentration in the nanocomposites resulted in significant (P < 0.05) decrease in loading
capacity. The highest entrapment efficiency was observed with XG5%NANOmet (80.20 %).
Drug loading expresses the percent weight of active ingredient encapsulated to the weight of
nanoparticles. Drug loading efficiency is the ratio of the experimentally determined
percentage of drug content compared with actual or theoretical mass of drug used for
preparation of the nanoparticles [199]. The loading efficiency depends on the polymer–drug
combination and the method used. Hydrophobic polymers encapsulate larger amounts of
hydrophobic drugs, whereas hydrophilic polymers entrap greater amounts of more
hydrophilic drugs [199]. Several formulation parameters, such as type of stabilizing agent and
weight ratio of polymer to drug will influence the extent of drug loading [200,201].
68
Fig 1: UV-vis spectra for AMS5%NANOmet
69
Fig 2 : UV-vis spectra for GG5%NANOmet
70
Fig 3 : UV-vis spectra for NaALG5%NANOmet
71
Fig 4: UV-vis spectra for XG5%NANOmet
72
Table 2: Percent yield of nanocomposites
Batches Theoretical(g) Actual(g) % Yield
AMS 1% NANOmet 1.50 1.20 ± 0.06 80.00 ± 0.58
AMS 3% NANOmet 3.50 2.80 ± 0.12 80.00 ± 1.15
AMS 5% NANOmet 5.50 4.56 ± 0.01 83.00 ± 0.06
GG 1% NANOmet 1.50 1.50 ± 0.00 99.87 ± 0.01
GG 3% NANOmet 3.50 3.20 ± 0.12 91.40 ± 0.10
GG 5% NANOmet 5.50 4.50 ± 0.12 81.80 ± 0.10
XG 1% NANOmet 1.50 1.35 ± 0.02 90.00 ± 0.58
XG 3% NANOmet 3.50 3.13 ± 0.12 89.40 ± 0.12
XG 5% NANOmet 5.50 4.90 ± 0.02 89.13 ± 0.47
NaALG 1% NANOmet 1.50 1.25 ± 0.06 83.33 -± 0.01
NaALG 3% NANOmet 3.50 3.20 ± 0.12 91.40 ± 0.58
NaALG 5% NANOmet 5.50 4.93 ± 0.12 89.64 ± 0.02
Values are expressed in mean ±SEM KEY:
AMS1%NANOmet = 1%W/V modified starch (AMS) and Metformin HCl
AMS3%NANOmet = 3%W/V modified starch (AMS) and Metformin HCl
AMS5%NANOmet = 5%W/V modified starch (AMS) and Metformin HCl
GG1%NANOmet = 1%W/V Guar gum and Metformin HCl
GG3%NANOmet = 3%W/V Guar gum and Metformin HCl
GG5%NANOmet = 5%W/V Guar gum and Metformin HCl
XG1%NANOmet = 1%W/V Xanthan gum and Metformin HCl
XG3%NANOmet = 3%W/V Xanthan gum and Metformin HCl
XG5%NANOmet = 5%W/V Xanthan gum and Metformin HCl
NaALG1% NANOmet = 1%W/V Sodium alginate and Metformin HCl
NaALG3% NANOmet = 3%W/V Sodium alginate and Metformin HCl
NaALG5% NANOmet = 5%W/V Sodium alginate and Metformin HCl
73
In the present nanoparticle fabrication, the drug and the polymer were dissolved in distilled
water. Hence there were no chances of diffusion of the drug away from the polymer. The
percentage of drug entrapment in the formulations was found to be good at all levels of drug
loading. Good entrapment efficiency of 71 to 80.20 % was observed for all the
nanocomposites. The high entrapment efficiency of the nanocomposite is believed to be due
to its solubility in the same solvent [199]. The highest entrapment efficiency of 80.20 % was
achieved by increasing polymer drug ratio. The decreased drug entrapment with increasing
theoretical drug loading may be due to an enhanced drug leakage into the aqueous phase
[199].
3.4: Differential Scanning Calorimetry (DSC)
The thermograms of the nanocomposites are shown in figures 5 to 9. DSC is used to obtain
the thermal critical points like melting point, enthalpy specific heat or glass transition
temperature of substances. It is a method of investigating the thermal characteristics of
substances like polymers. DSC is a highly useful means of detecting drug-excipient
incompatibility in a formulation. It gives insight into the capacity of the nanoparticles to
entrap high amounts of the drug [202]. DSC detects phase transition such as glass transition
(exothermic), crystallization and (endothermic) melting: the nanoparticle sample is heated
and changes in the heat flow, compared to reference, are recorded [199]. DSC thermograms
were obtained to define the physical state of the drug and polymer in the nanoparticles and to
detect any drug polymer interactions in the polymeric network of the nanoparticles [199].
74
Table 3: Entrapment Efficiency and Loading Capacity of Nanocomposites
Batches Entrapment Efficiency (%)
Loading Capacity (%)
AMS1% NANOmet
71.47 23.80
AMS3% NANOmet
77.16 11.03
AMS5% NANOmet
79.56 7.24
GG1% NANOmet
69.40 23.10
GG3% NANOmet
76.00 10.87
GG5% NANOmet
80.00 7.28
XG1% NANOmet
72.57 24.10
XG3% NANOmet
78.10 11.17
XG5% NANOmet
80.22 7.30
NaALG1% NANOmet
63.06 21.00
NaALG3% NANOmet
71.80 10.27
NaALG5% NANOmet
76.50 7.00
KEY:
AMS1%NANOmet = 1%W/V modified starch (AMS) and Metformin HCl
AMS3%NANOmet = 3%W/V modified starch (AMS) and Metformin HCl
AMS5%NANOmet = 5%W/V modified starch (AMS) and Metformin HCl
GG1%NANOmet = 1%W/V Guar gum and Metformin HCl
GG3%NANOmet = 3%W/V Guar gum and Metformin HCl
GG5%NANOmet = 5%W/V Guar gum and Metformin HCl
XG1%NANOmet = 1%W/V Xanthan gum and Metformin HCl
XG3%NANOmet = 3%W/V Xanthan gum and Metformin HCl
XG5%NANOmet = 5%W/V Xanthan gum and Metformin HCl
NaALG1% NANOmet = 1%W/V Sodium alginate and Metformin HCl
NaALG3% NANOmet = 3%W/V Sodium alginate and Metformin HCl
NaALG5% NANOmet = 5%W/V Sodium alginate and Metformin HCl
75
AMS 5 %NANOmet
Desolvation occurred at about 100 oC, Glass transition (Tg ) took place at about 130 o
C while Cold crystallization occurred at about 140 oC. Broad peak at about 160 – 170 o C is
possibly due to polymer (AMS) melting. Endotherm at 220 o C is due to melting of drug
(metformin). DSC results showed that there was no interaction between the polymer
(acetylated Starch) and drug (metformin) [203].
GG 3%NANOmet
Desolvation process started early at temperature slightly above 50 oC to 100 oC. Low
magnitude endothermic process at about 210 - 220 o C of metformin could be detected
.Decomposition occurred beyond 250 o C. This also confirmed there was no interaction
between Guar gum and metformin [203]
GG 5%NANOmet
Desolvation process started early at temperature at 55 o C to 130 o C. Low magnitude
endothermic process at about 220 o C for metformin could be detected .Decomposition
occurred beyond 250 o C. This also confirmed there was no interaction between Guar gum
and metformin [203]
XG 5% NANOmet
Desolvation process occurred at less than 100 o C. Possible peak is due to metformin at 220 o
C. Values above 250 o C are not characteristic of any interactions.
In all the nanocomposites, there was no interaction between metformin and the polymers
[202].
NaAlg 5% NANOmet
Desolvation process at 50 -90 o C .Endothermic process due to metformin occurred at about
210 oC. Exothermic peaks are not characteristics or decomposition. DSC thermograms also
showed no interaction between sodium alginate and the metformin
76
Fig.5: Thermogram of AMS5 % NANOmet
77
Fig.6: Thermogram of GG3 % NANOmet
78
Fig. 7: Thermogram of GG5 % NANOmet
79
Fig. 8: Thermogram of XG5 % NANOmet
80
Fig. 9: Thermogram of NaALG5% NANOmet
81
3.5: Thermogravimetric Analysis (TGA)
Thermogravimetric analysis is also a method used to investigate the thermal characteristics of
polymers. TGA is an analytical technique used to determine a material’s thermal stability and
its fraction of volatile components by monitoring the weight change that occurs as the
specimen is heated. Thermogravimetric analysis was done for the polymers, guar gum,
xanthan gum and sodium alginate. For guar gum and xanthan gum, the percentage change in
weight as a function of temperature was 0.067 % / °C (Fig. 10) and 0.071 % / °C (Fig.11)
respectively while for sodium alginate the percentage change in weight as a function of
temperature was 0.100 % / °C (Fig. 12). The thermogravimetric analysis result for guar gum
and xanthan gum were similar as there was no significant (P > 0.05) difference in their
values. However, the thermogravimetric analysis result for sodium alginate was significantly
(P<0.05) higher than those for guar and Xanthan gums. This indicates that alginate
decomposes faster under heating than the other two natural polymers (Xanthan and Guar
gums).
The rate of weight changes upon heating for the three polymers, however, was not sufficient
to cause denaturation. The order of thermal stability of the polymers was : 0.067 % / °C >
0.071 % / °C > 0.100 % / °C for guar gum, xanthan gum and sodium alginate respectively.
82
Fig. 10: Thermogravimetric analysis (TGA) of guar gum
83
Fig. 11: Thermogravimetric analysis (TGA) of xanthan gum
84
Fig. 12: Thermogravimetric analysis (TGA) of sodium alginate
85
3.6: Determination of Particle size and Polydispersity Index (PDI)
The mean particle size (Z-average), Polydispersity Index (Pdi) and peaks of the
nanoparticles were determined by dynamic light scattering technique using a Zetasizer Ver:
7.01 (Nano Zs 90, Malvern Instruments Ltd, UK) Particle size, size distribution and
polydispersity index are important characterizations of nanoparticles because they govern the
other characterizations, such as saturation solubility and dissolution velocity, physical
stability, or even biological performances [204]. Particle size is often used to characterize
nanoparticles, because it facilitates the understanding of the dispersion and aggregation [199].
Due to larger surface area and attractive force between the particles, the tendency of possible
aggregation is high in nanoparticles. To overcome such aggregations, the introduction of a
stabilizing agent in the preparation was necessary. Guar gum appeared to be the most suitable
in reducing aggregation between nanoparticles which suspends immediately after formation
[199].
The mean particle sizes of optimized batches are shown in Table 4 and Fig 13. The
results showed that nanoparticles produced were of sub micron size and had relatively low
poly dispersity which indicates narrow particle size distribution for the nanocomposites.
Inefficient polymeric synthesis may form polymers with high polydispersity index that
degrade more rapidly. The particle size and particle size distribution are critical factors in the
characterisation of nanoparticles, as batches with wide particle size distribution show
significant variations in drug loading, drug release, bioavailability and efficacy. Formulation
of nanoparticle with narrow size distribution will be a challenge. As nanoparticles are
internalized into cells by endocytosis, an increase in particle size will decrease uptake and
potentially, bioavailability of the drug.
86
GG1%NANOmet
The average particle size (z-average) was 188.70 nm. Particle size analysis showed
the presence of nanoparticles with polydispersity index (PDI) of 0.55 (Table 4). The average
mean particle size (Z-average) of GG1%NANOmet (188.7 nm) was significantly (P<0.05)
less than other nanocomposites: NaALG1%NANOmet (584.4 nm), AMS1%NANOmet
(386.7nm) and XG1%NANOmet (689.90 nm). Other recent research work on synthesis of
nanoparticles using guar gum resulted in mean particle size of 200 to 400 nm [205],
approximately 50 nm [206), 280 nm [207] and 200 – 300 nm [208]). The mean particle size
(188.7 nm) for GG1%NANOmet in this research was comparable to the results from previous
researches [207, 208].
NaALG1% NANOmet
The average particle size (z-average) was found to be 584.40 nm. Particle size
analysis showed the presence of nanoparticles with polydispersity index (PDI) of 0.57. The
average particle size for NaALG1%NANOmet was significantly (P<0.05) higher than the Z-
average for GG1%NANOmet and AMS1%NANOmet but was significantly (P<0.05) lower
than that of XG1%NANOmet. The Z – average for NaALG1%NANOmet was higher when
compared to mean particle size for sodium alginate nanoparticles (200 nm) reported by
Saeed Moradhaseli et al,2013 [209]. This value was also higher compared to sodium alginate
prepared from previous researches [210 – 211]
AMS1%NANOmet
Mean particle size diameter and polydispersity index of AMS1%NANOmet were all
measured in solutions directly after synthesis, using dynamic light scattering. The average
particle size (z-average) was 386.70 nm. Particle size analysis showed the presence of
87
nanoparticles with polydispersity index (PDI) of 0.61 (Table 4). The Z-average for this
NANOmet was significantly (P < 0.05) less than that of GG1%NANOmet but higher (P <
0.05) than NaALG1%NANOmet and XG1%NANOmet.
XG1%NANOmet
Particle size measurements: mean particle size diameter and polydispersity index were all
measured in solutions directly after synthesis, using dynamic light scattering. The average
particle size (z-average) for XG1%NANOmet was 689.90 nm (Table 4). This NANOmet had
the highest particle size compared to others. Its Particle size analysis showed the presence of
nanoparticles with polydispersity index (PDI) of 0.72. Based on the above, it is expected that
GG5%NANOmet will have the highest bioavailabilty when compared to other
nanocomposites [212]. AMS5%NANOmet will also have a relatively higher bioavailability.
88
Table 4: Mean particle size diameters and poly dispersity indices (PDI) of nanocomposites Nanocomposites Mean particle size diameter
(nm)
Polydispersity Index
GG1%NANOmet 188.70 0.55
NaALG1%NANOmet 584.40 0.57
AMS1%NANOmet 386.70 0.61
XG1%NANOmet 689.90 0.94
GG1%NANOmet = 1%W/V guar gum and metformin HCl NaALG1%NANOmet = 1%W/V Sodium alginate and metformin HCl AMS1%NANOmet = 1%W/V modified starch (AMS) and Metformin HCl XG1%NANOmet = 1%W/V xanthan gum and metformin HCl
89
0
100
200
300
400
500
600
700
800
900
1000
GG1%NANOmet NaALG1%NANOmet AMS1%NANOmet XG1%NANOmet
nanoparticles
Mea
n p
arti
cle
Siz
e d
iam
eter
(n
m)
Fig 13: Comparison of the mean particle size of nanoparticles.
90
3.7: Morphological Studies
AMS has smooth, near spherical shaped appearance (Fig.14), while AMS1%NANOmet
showed hydration of the polymer (Fig 15). The surface of formulated nanoparticles depends
on two factors ; saturated solution of polymer, produced smooth and high yield nanoparticles
while un dissolved polymer produced irregular and rod shaped particles, and secondly the
diffusion rate of solvent is too fast and the solvent may diffuse into the aqueous phase before
stable nanoparticles are formed causing the aggregation of nanoparticle [199]. In this
preparation the polymer was fully saturated and the diffusion rate of solvent was minimal
leading to the formation of near smooth, spherical nanoparticles. The particle sizes of
AMS1%NANOmet from SEM analysis (Fig. 15) was greater than that obtained by the DLS
(Table 6). This difference is due to the fact that SEM allows only the visualization of the
nanoparticle core, whereas the hydrodynamic radius of the particles was measured by DLS.
Particle size is often used to characterize nanoparticles, because it facilitates the
understanding of the dispersion and aggregation [199]. Drug release process is controlled by
dual mechanism; the liquid enters the polymer matrix, dissolves the drug and enable the drug
to diffuse out through the liquid located in the polymer matrix. Both these transfers are
controlled by diffusion and the movement of the drug which increases with the liquid
concentration in the dosage form. As a result, drug delivery in the intestine is effectively
controlled. Drug release is governed by polymer structure and properties. The release of
metformin from AMS 1%NANOmet was 53.99 % in SGF and 98.66 % in SIF. These values
are significantly (P<0.05) higher than those from nanoparticles prepared from commercial
starch [177-181]
91
Fig.14: Scanning electron microscopy for Modified Starch (AMS)
92
Fig.15: Scanning electron microscopy for AMS1%NANOmet
93
3.8: DRUG RELEASE PROFILES
The in vitro release profiles of all formulation are shown in Figures 16 to 27. The release of
metformin from the nanocomposites was majorly polymer concentration dependent.
GG1%NANOmet
The release profile of GG1%NANOmet in SGF was biphasic (Fig.16). There was
initial burst release within the first 30 min followed by controlled release to the 10th hour of
the release studies. The release of metformin was steady at a rate of 4.95 h-1. The time for 50
% (T50) of 9.5 h in SGF is quite appreciable and will be a good candidate for once daily
dosing for the management of Diabetes mellitus. This will also eliminate the problem of non
compliance usually associated with the three times dose per day [213] .The maximum release
of 94.8 % in SIF is therapeutically acceptable. The initial release in SIF for the first 30 mins
was very fast (46.4 %), then the release slowed to 48.4 % at 1h and remain steady till the
peak at the 16th hour.
GG3%NANOmet
The dissolution profile of batch GG3%NANOmet is shown in Fig.17. The
formulation sustained the release of the drug up to 6 h. In first hour 16.80 ± 0.79 % drug was
released. This may be as a result of drug present at the surface of the particles. Approximately
50.80 % and 61.60 % of the drug was released at the 2.5 h in SGF and SIF respectively. The
drug released got to a maximum at 4.5 h and was maintained for the next 2 h (up to 6 h).
GG3% NANOmet showed a controlled release profile. There was no initial burst release.
This was due to diffusion of drug through matrix and the polymer (guar gum).
94
GG5%NANOmet
Fig. 18 shows the release profile of GG5%NANOmet. The result showed that the
release of metformin from the nanocomposite was complete in 7 h with a maximum drug
release of 94.8 %. The release profile of this NANOmet in SGF was triphasic. There was a
burst release phase within the first 2 h, followed by a lag phase within the 2nd to the 3rd hour
of release; and finally controlled release phase of up to 6 h. The T50 of 4. 5 h in both SGF and
SIF is quite desirable as a candidate for controlled release compared to the half life for the
normal release metformin tablet which is about 1.5 h [153].
AMS1%NANOmet
The maximum release of drug from AMS 1%NANOmet (Fig 19) was 98.66 % at the
7.5 h. The time taken for 50% of the drug to be release was 7.0 h, a value which is
significantly (P < 0.05) higher than that obtained for the marketed metformin (glucophage)
[153].The release of drug from AMS1%NANOmet followed a biphasic profile, with a slight
initial burst at the first 30 mins followed by sustained release for the next 7 h when the
release study was performed in SGF.
In SIF, the release of metformin from AMS1%NANOmet showed triphasic profile, with a
burst release within the first 1 h, followed by a lag phase between the first and second hour of
release. Finally, there was controlled release from the 2nd hour to about the 8th hour of study.
AMS3%NANOmet
The release profiles of AMS 3%NANOmet (Fig.20) followed a controlled release
pattern. This may be due to diffusion of metformin through the matrix and the polymer
degradation.The profile in SIF, however, followed a biphasic profile, with an initial burst
release within the first hour and thereafter the release was controlled up to the 7th hour. There
95
was no significant difference in the T50 of this NANOmet in both SGF and SIF (3.5 h and 3.8
h) respectively. The T1/2 value was still higher than the marketed metformin drug.
AMS5%NANOmet
AMS5%NANOmet (Fig.21) showed a controlled release pattern in SGF but triphasic
release profile in SIF. Release in both media followed zero order kinetics which involved
polymer degradation and diffusion of the drug from the NANOmet. There was no significant
(P > 0.05) difference in their maximum drug (98.66 %, 99.66 % and 99.66 %). There was,
however, significant (P > 0.05) difference in their T50. (AMS1%NANOmet = 7 h, AMS
3%NANOmet = 4 h and AMS 5%NANOmet = 3.5 h). AMS1% NANOmet has optimum
release profile with desirable T50 of 7 h for control release and once daily dosing [214].
NaALG1% NANOmet
The release profile for NaALG3%NANOmet (Fig.22) showed prolonged release with
minimal burst effect in the first 0.5 h (10 % and 25.5 %) in SGF and SIF respectively. In
SGF, the release profile showed a flat pattern after the initial burst release of 10 % within the
first half hour of the release studies. However, the profile in SIF was controlled release which
continued till the 7th hour of the study.
NaALG3% NANOmet
In SGF, NaALG3%NANOmet showed a controlled release profile of up to the 7th
hour, after which a faster release was observed till 85.2 % of metformin, was released at the
8th hour of the study. This is probably due to complete polymer degradation leading to rapid
release of drug.
96
In SIF, the formulation controlled the release of the drug up to the 8th hour of the study, when
98.40 % of the metformin was released. A combination of gradual polymer depolymerization
and diffusion could account for this. The kinetics of release was by Higuchi square root.
NaALG5% NANOmet
NaALG5%NANOmet (Fig.23) had similar release profile to NaALG3%NANOmet.
There was no burst release. The initial release at half an hour was 6.4% in SGF and 13.6 % in
SIF. The maximum release was 97.6 % at the 8th hour of the study. The time taken for 50 %
of drug to be released was 8 h in SGF and 2 h in SIF. This is expected as metformin site of
action is basically in the intestine which has alkaline pH [215,216]. There was burst release at
the first 30 min. The fast release may be attributed to the maximum surface area available for
dissolution of the drug from the nanocomposite. Thereafter the release slowed and was
maintained for more than 8 h.
XG1%NANOmet,
XG1%NANOmet (Fig. 25) formulations displayed a controlled release profile in both
SGF and SIF. Xanthan gum has been utilized in controlled and targeted drug delivery with
optimum results [171 – 173]. The release of metformin from the XG1%NANOmet was
sustained through a process of gradual polymer degradation and drug diffusion for a total
time of 8.5 h. this was similar to the profile of XG5%NANOmet
XG3%NANOmet
XG3%NANOmet formulations displayed a controlled and prolonged release profile in
both SGF and SIF. Xanthan gum has been utilized in controlled and targeted drug delivery
with optimum results [171 – 173]. The release of metformin from XG3%NANOmet was also
97
sustained through a process of gradual polymer degradation and drug diffusion for a total
time of 8.5 h. This was same for all the formulations stabilized with xanthan gum.
XG5%NANOmet
XG5%NANOmet formulations displayed a controlled and prolonged release profile in
both SGF and SIF in a similar pattern to XG1%NANOmet and XG3%NANOmet.
3.9 Time for 50 % of Drug to be released in SGF (T50 )
The T50 for AMS1%NANOmet was found to be 7 h (Table 5). This value is
significantly (P < 0.05) higher than the half life of metformin tablet [153]. The time taken for
50 % of metformin to be released from AMS3%NANOmet (T50) was 3.7 h. This value is not
significantly (P > 0.05) different from the half life of metformin tablet [153]. The T50 for
AMS3%NANOmet was significantly (P < 0.05) less than that for AMS1%NANOmet. The
time taken for 50 % of metformin to be released from the AMS5%NANOmet (T50) was 3.5 h
(Table 8). This value is similar (P > 0.05) to the T50 for AMS3%NANOmet (3.7 h). The T50
increased with decrease in polymer concentration (3.50 ± 0.17 < 3.70 ± 0.12 < 7.0 ± 0.12) for
AMS5%NANOmet, AMS3%NANOmet and AMS1%NANOmet respectively.
The T50 for GG1%NANOmet was 9.0 h. This value is significantly (P < 0.05) higher
than the half life of metformin tablet [153] .This value was also higher (P < 0.05) than T50 for
the AMS1%NANOmet. This may be due to the fact that guar gum has a higher retarding
capacity than starch [156], from which AMS was synthesized. .The time taken for 50 % of
metformin to be released from the GG3%NANOmet was 2.5 h (Table 5). This value is not
significantly (P > 0.05) different from the half life of metformin tablet [153]. The T50 for
GG3%NANOmet was significantly (P < 0.05) less than that for GG1%NANOmet.
98
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7 8 9 10
TIME(h)
CU
MU
LA
TIV
E P
ER
CE
NT
DR
UG
RE
LE
AS
E
% RELEASE IN SGF
% RELEASE IN SIF
Fig .16: Release profile of GG 1 % NANOmet
99
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7
Time(h)
Cu
mu
lati
ve p
erce
nt
dru
g r
elea
se
% RELEASE IN SGF
% RELEASE IN SIF
Fig .17: Release profile of GG3% NANOmet
100
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7 8
Time(h)
Cu
mu
lati
ve p
erce
nt
dru
g r
elea
se
% RELEASE IN SGF
% RELEASE IN SIF
Fig .18: Release profile of GG5% NANOmet
101
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7 8
Time(h)
Cu
mu
lati
ve p
erce
nt
dru
g r
elea
se
Rellease in SGF
Release in SIF
Fig .19: Release profile of AMS 1% NANOmet
102
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7 8
TIME(H)
CU
MU
LA
TIV
E P
ER
CE
NT
DR
UG
RE
LE
AS
E
% RELEASE IN SGF
% RELEASE IN SIF
Fig .20: Release profile of AMS 3% NANOmet
103
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7 8
Time(h)
Cu
mu
lative
per
cent
dru
g r
elea
se
% RELEASE IN SGF
% RELEASE IN SIF
Fig.21: Release profile of AMS 5% NANOmet
104
0
10
20
30
40
50
60
70
80
90
100
0 1 2 3 4 5 6 7 8
Time(h)
Cu
mu
lati
ve p
erce
nt
dru
g r
elea
se
% RELEASE IN SGF
% RELEASE IN SIF
Fig .22: Release profile of NaALG1 1% NANOmet
105
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7 8 9
Time(h)
Cu
mu
lati
ve p
erce
nt
dru
g r
elea
se
% RELEASE IN SGF
% RELEASE IN SIF
Fig .23: Release profile of NaALG 3% NANOmet
106
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7 8 9
Time(h)
Cu
mu
lati
ve p
erce
nt
dru
g r
elea
se
% RELEASE IN SGF
% RELEASE IN SIF
Fig .24: Release profile of NaALG 5% NANOmet
107
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7 8 9
Time(h)
Cu
mu
lati
ve P
erce
nt
Dru
g R
elea
se
% RELEASE IN SGF
% RELEASE IN SIF
Fig .25: Release profile of XG 1% NANOmet
108
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7 8 9
Time (h)
Cu
mu
lati
ve p
erce
nt
dru
g r
elea
se
% RELEASE IN SGF
% RELEASE IN SIF
Fig .26: Release profile of XG 3% NANOmet
109
0
10
20
30
40
50
60
70
80
90
100
0 1 2 3 4 5 6 7 8 9
Time(h)
Cu
mu
lati
ve P
erce
nt
Dru
g R
elea
se
% RELEASE IN SGF
% RELEASE IN SIF
Fig .27: Release profile of XG 5% NANOmet
110
The time taken for 50 % of metformin to be released from GG5%NANOmet was 4 h.
This value is similar (P > 0.05) to the T50 for GG3%NANOmet.
NaALG1%NANOmet had no value for T50. This is because only 25 % of metformin
was released at the 7th hour in SGF.The time taken for 50 % of metformin to be released from
NaALG3% NANOmet was 7.6 h . This value is significantly (P < 0.05) higher than the half
life of metformin tablet (58). The T50 for NaALG3%NANOmet (7.60 ±0.12) was not
significantly (P < 0.05) different from that for AMS1%NANOmet (7.00 ± 0.12).
The time taken for 50 % of metformin to be released from the AMS5%NANOmet
(T50) was 8 h. The T50 for XG1%NANOmet (4.50 ± 0.10) was statistically comparable (P >
0.05) to XG5%NANOmet (5.00 ± 0.17), but significantly (P < 0.05) higher than that for
XG3%NANOmet (3.50 ±0.17). The T50 for XG3%NANOmet (3.30 ± 0.58) was statistically
comparable (P > 0.05) to AMS3%NANOmet (3.70 ± 0.12), AMS5%NANOmet (3.50 ±
0.17), GG3%NANOmet (2.50 ± 0.12) and GG5%NANOmet (4.00 ± 0.12). This value is
significantly (P < 0.05) higher than the half life of metformin tablet [153]
The T50 for XG5%NANOmet (5.00 ± 0.17) was statistically similar (P > 0.05) to
XG3%NANOmet (4.50 ± 0.17), but significantly (P < 0.05) higher than that for
XG1%NANOmet (3.50 ± 0.17). This value is significantly (P < 0.05) higher than the half
life of metformin tablet [153]
3.10: Time for 50 % of Drug to be released in SIF (T50) )
The T50 for AMS1%NANOmet when release studies were done in SIF was 5.40 ±
0.12 h (Table 5). This value is significantly (P < 0.05) higher than the half life of metformin
tablet [153]. Compared to the T50 in SGF, the time taken for 50 % of metformin to be
released in SIF is lower (P < 0.05). The time taken for 50 % of metformin to be released
from AMS3%NANOmet was 2.8 h. This value is not significantly (P > 0.05) different from
111
the half life of metformin tablet (58). The T50 for AMS3%NANOmet was significantly (P <
0.05) less than that for AMS1%NANOmet (5.40 ± 0.12 h). Similar trend was observed when
release studies were performed in SGF. The time taken for 50 % of metformin to be released
from the AMS5%NANOmet was 3.8 h. This value is similar (P > 0.05) to the T50 for
immediate released metformin Hcl [153].
The T50 for GG1%NANOmet was 1.2 h. This value is significantly (P < 0.05) less
than the half life of metformin tablet. This value was also lower (P < 0.05) than T50 for the
GG1%NANOmet when release study was performed in SGF.
The T50 of GG3%NANOmet was 2.2 h. This value is not significantly (P > 0.05)
different from the half life of metformin tablet [153]. The T50 for GG3%NANOmet was
significantly (P < 0.05) higher than that for GG1%NANOmet. The reverse was the case when
studies were performed in SGF.
The time taken for 50 % of metformin to be released from the GG5%NANOmet
(T50) was 4.0 h . This value is exactly same with T50 when studies was done in SGF (4.00 ±
0.12) .when compared to the T50 for GG3%NANOmet (2.2 h), the value for
GG5%NANOmet (4.00±0.12) was higher (P < 0.05) in SIF release studies.
During release studies in SIF, The T50 for guar gum stabilized NANOmet increased
with increase in polymer concentration (1.20 ± 0.06 < 2.20 ± 0.12 < 4.00 ± 0.12) for
GG1%NANOmet, GG3%NANOmet and GG5%NANOmet respectively.
NaALG1%NANOmet had T50 of 1.10 ± 0.06 h. This value is lower than the half life
of metformin HCl. The time taken for 50 % of metformin to be released from NaALG3%
NANOmet (T50) was 1.70 h. This value is significantly (P < 0.05) higher than the half life of
metformin tablet. The T50 for NaALG3%NANOmet (1.70 ± 0.06 h) was significantly (P <
0.05) less than that for the same NANOmet when release was done in SGF (7.60 ± 0.12 h).
112
The time taken for 50 % of metformin to be released from the AMS5%NANOmet
(T50) was 1.7 h. the T50 in SIF (1.70 ± 0.12) was far less (P < 0.05) than T50 in SGF (8.0 ±
0.06) . The T50 for XG1%NANOmet (4.90 ± 0.06) was not significantly (P > 0.05) different
from AMS1%NANOmet (5.40 ± 0.12) and GG5%NANOmet (4.0 ±0.12), XG3%NANOmet
(4.70 ± 0.09) and XG3%NANOmet (5.00 ± 0.29) when release studies was carried out in SIF.
This value is significantly (P < 0.05) higher than the half life of metformin tablet [153].
The T50 for XG3%NANOmet (4.70 ± 0.58) was statistically comparable (P > 0.05) to
AMS1%NANOmet (5.40 ± 0.12) and GG5%NANOmet (4.00 ± 0.12). This value is
significantly (P < 0.05) higher than the half life of metformin tablet.The T50 for
XG5%NANOmet (5.00 ± 0.29) was also statistically comparable (P > 0.05) to
AMS1%NANOmet (5.40 ± 0.12) and GG5%NANOmet (4.00 ± 0.12). There was no
significant (P < 0.05) different in T50 of NANOmet stabilized with xanthan gum.
3.11: Time for 25 % and 75 % of Drug to be released in SGF (T25 and T75 )
The time taken for 25 % of the drug to be released was also used to characterise the release
profile. The T25 for AMS1%NANOmet was 1.10 h during release studies in SGF while T75
was not available as the maximum drug release was 53.99 % . The time taken for 25 % of
metformin to be released from AMS3%NANOmet (T25) was 0.7 h. This nanocomposite had
no T75 since its maximum release was 60.99 %. The time taken for 25 % and 75 % of
metformin to be released from the AMS5%NANOmet was 0.6 h and 4.80 h respectively.
The T25 decreased with increase in polymer concentration (1.10 ± 0.17 < 0.70 ± 0.12 < 0.6 ±
0.12 ) for AMS1%NANOmet, AMS3%NANOmet and AMS5%NANOmet respectively.
This indicates that increased polymer concentration in the NANOmet enhance better
controlled release of the drug [177]. However, only AMS5%NANOmet had T75 of 4.80 h
while the other NANOmet had no values.
113
The T25 for GG1%NANOmet was 3.20 h while T75 was not computed as the
maximum release of metformin from this NANOmet 50.44 %. This value is not significantly
(P < 0.05) different from the half life of metformin tablet [153]. This also indicates a more
prolonged and controlled delivery of the metformin.The time taken for 25 % and 75 % of
metformin to be released from GG3% NANOmet (T25 and T75)) was 1.80 h and 7.00 h
respectively. The time taken for 25 % of metformin to be released from the GG5%NANOmet
(T50) was 1.55 h. Like AMS NANOmet. The T25 for guar gum stabilized NANOmet
decreased with increase in polymer concentration (3.20 ± 0.15 < 1.80 ± 0.17 < 1.15 ± 0.12)
for GG1%NANOmet, GG3%NANOmet and GG5%NANOmet respectively. This indicates
that increased polymer concentration in the nanocomposite enhanced controlled release of the
drug ([156] From NaALG1%NANOmet, 25% of metformin was released in 6.50 h in SGF.
T75 was not computed as the maximum percent of drug released from the NANOmet was 25
%. The time taken for 25% and 75 % of metformin to be released from NaALG3%
NANOmet (T25 and T75)) was 3.0 h and 7.09 h respectively.
The time taken for 25 % of metformin to be released from the AMS5%NANOmet
(T25) was 2.10 h. There was no value for T75 as the maximum drug release was 49.2 %. The
T25 for sodium alginate stabilized nanopaticles decreased with increase in polymer
concentration for GG1%NANOmet, GG3%NANOmet and GG5%NANOmet with values of
6.50 ± 0.12 < 3.00 ± 0.58 < 2.10 ± 0.06 respectively when release was conducted in SGF.
This indicates that increased polymer concentration in the NANOmet controlled release of
the drug [189]
The time taken for 25% and 75 % of metformin to be released from XG1%
NANOmet (T25 and T75)) was 3.0 h and 7.74 h respectively. The time taken for 25% and 75
% of metformin to be released from XG3% NANOmet (T25 and T75)) was 1.35 h and 8.5h
respectively. The T25 for XG3NANOmet was significantly (P < 0.05) less than the value for
114
XG1%NANOmet (3.0 h). Interestingly, The T75 for this NANOmet was significantly (P <
0.05) higher than XG1%NANOmet (7.74 h).
The time taken for 25% and 75 % of metformin to be released from XG5%
NANOmet (T25 and T75)) was 2.0 h and 8.9 h respectively.
While there was difference in T25 among all the xanthan gum stabilized NANOmet, the T75
of both XG3%NANOmet and XG5%NANOmet were significantly (P < 0.05) higher than
that of XG1%NANOmet. The effect is likely polymer concentration dependent [217]
3. 12: Time for 25 % and 75 % of Drug to be released in SIF (T25 and T75 )
The T25 for AMS1%NANOmet was 1.6 h during release studies in SIF while T75 was
6.3 h. During release studies in SIF, the time taken for 25 % of metformin to be released from
the NANOmet (T25) was 0.85 h whie T75 was 6.20 h. The time taken for 25 % and 75 % of
metformin to be released from the AMS5%NANOmet was 0.35 h and 5.70 h respectively.
During studies in SIF, the T25 and T75 for AMS stabilized NANOmet decreased with increase
in polymer concentration (1.60 ± 0.12 < 0.85 ± 0.06 < 0.35 ± 0.12) and (6.30 ± 0.17 < 6.20 ±
0.12 < 5.70 ± 0.12) for AMS1%NANOmet, AMS3%NANOmet and AMS5%NANOmet
respectively. The same trend was observed during studies in SGF. This indicates that
increased polymer concentration in the NANOmet enhance better controlled release of the
drug [177]. However, the Time taken for 25 % and 75% of the NANOmet to release
metformin was significantly (P < 0.05) lower during studies in SIF than in SGF. This may be
due to the fact that metformin major site of action is the intestine [215,216] .The T25 for
GG1%NANOmet was 0.21 h while T75 was 3.8 h. The time taken for 25% and 75 % of
metformin to be released from GG3% NANOmet (T25 and T75)) was 1.0 h and 3.5 h
respectively. The time taken for 25 % of metformin to be released from the GG5%NANOmet
(T25) was 1.55 h while 5.70 h was the time for 75 % of the drug to be released in SIF
115
dissolution medium. From NaALG1%NANOmet, 25% of metformin was released in 0.5 h in
SIF medium. T75 was 4.5 h during release studies in SIF. The time taken for 25% and 75 % of
metformin to be released from NaALG3% NANOmet (T25 and T75)) was 0.7 h and 6.0 h
respectively. The time taken for 25 % of metformin to be released from the
AMS5%NANOmet (T25) was 0.8 h. while T75 was 3.6 h. The T25 increased with increase in
polymer concentration (0.50 ± 0.12 < 0.70 ± 0.17 < 0.8 ± 0.06) for NaALG1%NANOmet,
NaALG3%NANOmet and NaALG5%NANOmet respectively when release was carried out
in SIF medium. The reverse was the case during release studies in SGF. The T25 for sodium
alginate stabilized NANOmet decreased with increase in polymer concentration (3.20 ± 0.15
< 1.80 ± 0.17 < 1.15 ± 0.12) when release was conducted in SGF.
The time taken for 25 % and 75 % of metformin to be released from XG1%
NANOmet (T25 and T75)) was 2.1 h and 6.7 h respectively during release studies in SIF. The
time taken for 25 % and 75 % of metformin to be released from XG3% NANOmet (T25 and
T75)) was 1.8 h and 7.9 h respectively. While there was no significant (P < 0.05) difference in
T25 between XG1%NANOmet and XG3%NANOmet, the T75 of XG3%NANOmet was higher
than XG1%NANOmet (6.7 h) in a significant (P < 0.05) manner. 2.4 h and 7.8 h were the
time taken for 25% and 75 % of metformin to be released from XG5% NANOmet
respectively. The values were not significantly (P < 0.05) different from the ones reported
during release studies in SGF. The T25 was significantly (P < 0.05) higher than that of
XG3%NANOmet (1.8 h) while T75 was similar in value( P > 0.05) to XG3%NANOmet. The
T75 value for AMS 5%NANOmet (4.8 h) in SGF was significantly (P < 0.05) less than T75 for
GG3%NANOmet (7.0 h), NaALG3%NANOmet (7.9 h) and XG1%NANOmet (7.74 h) ,
XG3%NANOmet (8.5 h) and XG3%NANOmet (8.9 h). During release studies in SIF, The
T75 value for AMS 5%NANOmet (4.8 h) was significantly (P < 0.05) less than T75 for
GG3%NANOmet (7.0 h), NaALG3%NANOmet (7.9 h) and XG1%NANOmet (7.74 h) ,
116
XG3%NANOmet (8.5 h) and XG3%NANOmet (8.9 h).In terms of T75, the time taken for 75
% of the total drug to be release, the nanocomposite prepared with higher concentration (3 %
and 5 %) of polymer gave optimum release profiles.
3.13: MAXIMUM RELEASE
Results for the maximum release of nanocomposites are shown in table 5.
3.13.1 MAXIMUM RELEASE IN SGF
The maximum drug released from AMS1%NANOmet was found to be 53.99± 0.06
%. This value is significantly (P < 0.05) less than the value for cumulative percent of
metformin release in SIF medium (98.66 ± 0.01 % [215]. The maximum percent release of
metformin from AMS1%NANOmet was 60.99 ± 0.03. This value is significantly (P < 0.05)
different from that of metformin release in SIF medium. However, the maximum percent
released by this NANOmet is higher (P < 0.05) than that for AMS1%NANOmet. 83.66±
0.12 % of metformin was the maximum cumulative percent released from
AMS5%NANOmet. This value is higher (P < 0.05) than the value for AMS3%NANOmet
(60.99 ± 0.03 %). The maximum percent release of metformin increased with increase in
polymer concentration (53.99 ± 0.06 % < 60.99 ± 0.33 % < 83.66 ± 0.12 %) for
AMS1%NANOmet, AMS3%NANOmet and AMS5%NANOmet respectively. In essence, the
release of metformin from AMS stabilized nanoparticles in SGF medium was polymer
concentration dependent.
Maximum drug release (Cmax) for GG1%NANOmet was 50.40 ± 0.23 % in SGF
medium. This value is significantly (P < 0.05) less than the maximum percent release for SIF
studies (94.80 ± 0.12 %).
The maximum percent of metformin released from the NANOmet was 74.40 ± 0.12.
This value is not significantly (P > 0.05) different from the value reported for SIF dissolution
117
studies of the same NANOmet (94.00 ± 1.15 %). 62.80 % of metformin was released from
the GG5%NANOmet as the maximum. Guar gum stabilized NANOmet had varied maximum
cumulative percent release with GG3%NANOmet having the highest.
NaALG1%NANOmet had value of 25.00± 0.58 % as its maximum release. This is
because only 25% of metformin was released at the 7th hour in SGF. 85.20± 0.12 % of
metformin was released from NaALG3% NANOmet as maximum. This value is significantly
(P < 0.05) higher than the value for NaALG1%NANOmet (25.00 ± 0.58). The maximum
cumulative metformin released from AMS5%NANOmet was 98.40± 0.23 %. The maximum
cumulative percent of metformin was also polymer concentration dependent; 25.00 ± 0.58 %,
85.20 ± 0.12 %, 98.40 ± 0.23 % were the maximum percent released for
NaALG1%NANOmet, NaALG3%NANOmet and NaALG5%NANOmet respectively.
XG1%NANOmet released 79.00 ± 0.58 % at the end of 8.5 h. This was statistically
comparable (P > 0.05) to GG3%NANOmet (74.40 ± 0.12 %), but higher than the maximum
drug released for XG5%NANOmet (72.50 ± 0.29 %). XG3%NANOmet released 74.89±0.04
at the end of 8.5 h. This was statistically comparable (P > 0.05) to GG3%NANOmet (74.40 ±
0.12 %). XG5%NANOmet released 72.50 ± 0.29 % at the end of 8.5 h. This was statistically
comparable (P > 0.05) to GG3%NANOmet (74.40 ± 0.12 %), but significantly (P < 0.05) less
than the maximum release values for XG1%NANOmet and XG3 %NANOmet.
In general, the maximum release of metformin from Xanthan gum stabilized nanoparticles
decreased with increase in polymer concentration. This may be attributed to the retarding
ability of xanthan gum [169-171,204]
118
3.13.2 MAXIMUM RELEASE IN SIF
The maximum drug released from AMS1%NANOmet was found to be 98.66 ± 0.06
%. This value is significantly (P < 0.05) higher than the value for cumulative percent of
metformin release in SGF medium (53.99 ± 0.06 %). This is because metformin usually
exerts its effect at the lower GIT which has higher pH [215]. The maximum percent release of
metformin from AMS3%NANOmet was 99.66 ± 0.06 %. This value is not significantly (P >
0.05) different from that of metformin released from AMS1%NANOmet. However, the
maximum percent released of metformin by this NANOmet is significantly higher (P < 0.05)
in SIF than in SGF. 99.66 ± 0.06 % of metformin was the maximum cumulative percent
released from AMS5%NANOmet. This value is exactly same with the value for
AMS3%NANOmet (99.66 ± 0.06 %). The maximum percent release of metformin from
nanoparticles stabilized with AMS in SIF was not concentration dependent. This may be due
to high release of metformin in the lower GIT [215,216]
Cmax for GG1%NANOmet was 94.80 ± 0.12 % in SIF. This value is significantly (P
< 0.05) higher than the maximum percent release for SGF studies (50.40 ± 0.23 %). The
maximum percent of metformin released from the GG3%NANOmet was 94.00 ± 1.15. This
value is significantly (P < 0.05) different from the value reported for SGF dissolution studies
for this nanocomposite (74.40 ± 0.12 %). 94.80 % of metformin was released from the
GG5%NANOmet as the maximum.
NaALG1%NANOmet had value of 85.50 ± 0.06 as its maximum release when release
studies were carried out in SIF. 98.40 ± 0.12 % of metformin was released from NaALG3%
NANOmet as maximum. This value is not significantly (P < 0.05) different from the value
for NaALG1%NANOmet (85.50 ± 0.06).
The maximum cumulative percent of metformin released from Sodium alginate nanoparticles
during release studies in SIF medium was also not polymer concentration dependent. 85.50 ±
119
0.06, 98.40 ± 0.12, 97.60 ± 0.02 were the maximum percent drug released for
NaALG1%NANOmet, NaALG3%NANOmet and NaALG5%NANOmet respectively
XG1%NANOmet, XG3%NANOmet and XG3%NANOmet had maximum drug
release of 94.50 ± 1.26, 98.31 ± 0.02 and 90.00 ± 0.87 % respectively, which were
statistically comparable (P > 0.05) to other nanocomposites for release studies in SIF [218-
219]
The maximum drug releases for all the formulations were significantly higher in SIF
than in SGF probably due to the fact that the main site of its absorption is proximal small
intestines (88, 89). However, nanoparticles synthesized with guar gum had significantly
(P<0.05) lower maximum release than the ones synthesized from AMS, xanthan gum and
sodium alginate. NaALG1%NANOmet had significantly (P < 0.05) lower release than the
other nanocomposites formulations, which had similar maximum release . (P < 0.05)
For AMS NANOmet formulations, the polymer concentration had significant (P < 0.05)
effect on the release profile in SGF but not in SIF [215]. Maximum percent release of drug
increased with increase in polymer concentration. A similar trend was also observed for the
other formulations (NaALGNANOmet, GGNANOmet and XGNANOmet). Maximum drug
release was a function of polymer concentration.
120
Table 5: Release Parameters for Metformin Nanocomposites
Formulation Maximum % Release in SGF
Maximum % Release in SIF
T50 in SGF (h)
T50 in SIF (h)
T25 in SGF (h)
T25 in SIF (h) T75 in SGF (h)
T75 in SIF (h)
AMS1% NANOmet
53.99 ± 0.06 98.66 ± 0.01 7.00 ± 0.12 5.40 ± 0.12 1.10 ± 0.06 1.60 ± 0.06 - 6.30 ±0.06
AMS3% NANOmet
60.99 ± 0.33 99.66 ± 0.006 3.70 ± 0.12 2.80 ± 0.12 0.70 ± 0.06 0.85 ±0.03 - 6.20 ± 0.12
AMS5% NANOmet
83.66 ±0.12 99.66 ± 0.01 3.5±0.1732 3.80 ± 0.12 0.80 ± 0.03 0.35 ± 0.03 4.80 ± 0.06 5.70 ± 0.06
GG1% NANOmet
50.40 ±0.23 94.80 ± 0.12 9.00 ± 0.23 1.20 ± 0.06 3.20 ± 0.06 0.21 ± 0.06 - 3.80 ± 0.06
GG3% NANOmet
74.40 ±0.12 94.00 ±1.15 2.50 ± 0.12 2.20 ± 0.12 1.80 ± 0.06 1.00 ± 0.06 7.00 ± 0.06 3.50 ± 0.06
GG5% NANOmet
62.80 ±0.12 94.80 ± 0.12 4.0±0.1155 4.0±0.12 1.15 ± 0.03 1.55 ±0.03 - 5.70 ± 0.06
NaALG1% NANOmet
25.00 ± 0.58 85.50 ± 0.06 - 1.10 ± 0.06 6.50 ± 0.12 0.50 ± 0.03 - 4.50 ± 0.06
NaALG3% NANOmet
85.20 ± 0.12 98.4±0.12 7.60 ± 0.12 1.70 ± 0.06 3.00 ± 0.58 0.70 ± 0.06 7.90 ± 0.06 6.00 ± 0.29
NaALG5% NANOmet
98.40 ± 0.23 97.60 ± 0.20 8.00 ± 0.12 1.70 ± 0.12 2.10 ± 0.06 0.80 ± 0.06 - 3.60 ± 0.12
XG1% NANOmet
79.00 ± 0.06 94.50 ±1.26 4.50 ± 1.00 4.90 ± 0.06 3.00 ± 0.01 2.10 ± 0.15 7.74 ± 0.03 6.70 ± 0.06
XG3% NANOmet
74.89 ± 0.04 98.31 ± 0.02 3.30 ± 0.58 4.70 ± 0.06 1.30 ± 0.06 1.80 ± 0.06 8.50 ± 0.06 7.90 ± 0.06
XG5% NANOmet
72.50 ± 0.03 90.00 ± 0.87 5.00 ± 0.17 5.00 ± 0.29 2.00 ± 0.12 2.40 ± 0.06 8.90 ± 0.10 7.80 ± 0.06
Values are expressed as mean±SEM
KEY:
AMS1%NANOmet = 1%W/V modified starch (AMS) and Metformin HCl
AMS3%NANOmet = 3%W/V modified starch (AMS) and Metformin HCl
AMS5%NANOmet = 5%W/V modified starch (AMS) and Metformin HCl
GG1%NANOmet = 1%W/V Guar gum and Metformin HCl
GG3%NANOmet = 3%W/V Guar gum and Metformin HCl
GG5%NANOmet = 5%W/V Guar gum and Metformin HCl
XG1%NANOmet = 1%W/V Xanthan gum and Metformin HCl
XG3%NANOmet = 3%W/V Xanthan gum and Metformin HCl
XG5%NANOmet = 5%W/V Xanthan gum and Metformin HCl
NaALG1% NANOmet = 1%W/V Sodium alginate and Metformin HCl
NaALG3% NANOmet = 3%W/V Sodium alginate and Metformin HCl
NaALG5% NANOmet = 5%W/V Sodium alginate and Metformin HCl
121
3.14: Kinetics and mechanism of release
The kinetics and mechanism of release of the nanocomposites are presented in Table 6.
AMS 1% NANOmet formulation released the drug by zero order kinetics via fickian
diffusion [220] when release studies were carried out in SGF. The release of metformin from
this nanoparticle was independent of concentration (R2 = 0.90, n= 0.33)
With increase in polymer concentration (AMS 3%NANOmet), the release kinetics followed
higuchi via fickian processes (R2 = 0.95, n= 0.43) in SGF.
AMS5%NANOmet released the metformin from the nanoparticle through zero order
via non fickian process (R2 = 0.96, n= 0.46). This means that drug release from the
NANOmet followed both diffusion and erosion controlled mechanisms. The dosage forms
following this profile, release the same amount of drug by unit time and it is the ideal method
of drug release in order to achieve a prolonged pharmacological action [221]).
Drug release from GG1%NANOmet followed Higuchi kinetics via non fickian
(anomalous) diffusion when studies were carried out in SGF (R2 = 0.96, n= 0.87). Higuchi
describes drug release as a diffusion process based in the Fick’s law, square root time
dependent. For diffusion controlled process a plot of Q versus square root of time is linear.
Diffusion controlled process dominates when the slope of the logarithm plot approaches 0.5
[222,223].
GG3%NANOmet released the metformin from the nanoparticle through Higuchi
kinetics and zero order (R2 = 0.94, n= 1.00). This means that drug released from the
NANOmet followed mixed released kinetics through diffusion and erosion controlled
mechanisms [224].
Drug release from GG5%NANOmet followed Zero order kinetics via non fickian
(anomalous) diffusion in SGF (R2 = 0.96, n= 0.62).
122
The release of metformin from this NANOmet was independent of concentration [220]. This
also implies that drug release from the NANOmet followed both diffusion and erosion
controlled mechanisms.
Release of metformin from NaALG NANOmet formulations followed a different
pattern, while NaALG3%NANOmet released the drug by Zero order kinetics via anomalous
mechanism (R2 = 0.54, n = 0.65). Release from NaALG1%NANOmet and
NaALG5%NANOmet followed higuchi kinetics (R2 = 0.79, n = 0.30, R2 = 0.93, n = 0.71))
respectively
XG1%NANOmet released the metformin HCl by Zero Order kinetics via super case
11 transport (R2 = 0.97, n = 0.77). XG3%NANOmet release the metformin HCl by higuchi
kinetics via super case II transport XG5%NANOmet, like XG1%NANOmet, released the
metformin HCl by zero order kinetics via super case II transport The regression coefficient
with the highest linearity was zero order (R2 = 0.99, n = 0.79).
The kinetics of release in SIF was similar to that in SG|F. AMS 1% NANOmet
formulation also released Metformin by zero order kinetics via non fickian diffusion [220]
when release studies were carried out in SIF. The release of metformin from this nanoparticle
was independent of concentration (R2 = 0.91, n= 0.46) The dosage forms following this
profile, release the same amount of drug by unit time and it is the ideal method of drug
release in order to achieve a prolonged pharmacological action
With increase in polymer concentration (AMS 3%NANOmet), the release kinetics followed
higuchi via non fickian processes (R2 = 0.90, n= 0.43) in SIF. The result is similar to the
kinetics in SGF. AMS5%NANOmet released the metformin from the nanoparticle through
zero order via fickian process (R2 = 0.65, n= 0.32). This means that drug release from the
NANOmet was independent of concentration. This is an ideal kinetics model for achieving
controlled release
123
Drug release from GG1%NANOmet followed Zero order kinetics via fickian
diffusion during studies in SIF (R2 = 0.96, n= 0.32). This is the ideal kinetic model for
controlled release of drugs
GG3%NANOmet released the metformin from the nanoparticle through Higuchi
kinetics via non fickian mechanism (R2 = 0.96, n= 0.85). This means that drug released from
the NANOmet followed mixed released kinetics through diffusion and erosion controlled
mechanisms [224]
Drug release from GG5%NANOmet followed Zero kinetics via non fickian
(anomalous) diffusion when studies were carried out in SIF (R2 = 0.96, n= 0.79).
The release of metformin from this NANOmet was independent of concentration. This also
implies that drug release from the NANOmet followed both diffusion and erosion controlled
mechanisms.
Release of metformin from NaALG NANOmet formulations followed a different
pattern. While NaALG1%NANOmet and NaALG5% NANOmet released the drug by first
order (R2 = 0.94, 0.98), release from NaALG3%NANOmet and NaALG5%NANOmet
followed higuchi kinetics ( R2 = 0.90)
During release studies in SIF, XG1%NANOmet also released the drug by Zero Order kinetics
via super case II transport. The regression coefficient with the highest linearity was zero
order (R2 = 0.98, n = 1.00). XG3%NANOmet release the metformin HCl by zero order since
the release exponent (n) has a value of 1. This is the ideal method of drug release in order to
achieve a prolonged pharmacological action.During release studies in SIF, XG5%NANOmet,
like XG1%NANOmet, also released the drug by zero order kinetics via super case II
transport. The regression coefficient with the highest linearity was zero order (R2 = 0.98, n =
1.10). For Xanthan gum stabilized nanoparticles, the release kinetics was basically zero order
while the mechanism of release was mainly non fickian.
124
Table 6: Kinetics and mechanism of release for metformin nanoparticles
formulation Zero order(S.D)
First order(S.D)
Higuchi kinetics(S.D)
Korsemeyer n
AMS 1 % SGF 0.90 (3.90)
0.87 (0.03)
0.88 (13.85)
0.91 0.33
AMS 1% SIF 0.94 (5.93)
0.91 (0.04)
0.90 (19.02)
0.93 0.46
AMS 3 % SGF 0.88 (5.82)
0.93 (0.05)
0.95 (21.15)
0.95 0.43
AMS3 % SIF 0.78 (7.84)
0.88 (0.06)
0.90 (27.15)
0.78 0.72
AMS 5% SGF 0.96 (11.09)
0.94 (0.13)
0.95 (38.56)
0.96
0.62
AMS 5% SIF 0.65 (7.91)
0.31 (0.20)
0.57 (24.23)
0.65 0.32
GG1%SGF 0.95 (4.95)
0.95 (0.032)
0.96 (20.44)
0.95 0.87
GG1%SIF 0.96 (9.87)
0.88 (0.20)
0.91 (31.42)
0.86 0.32
GG3%SGF 0.87 (12.76)
0.92 (0.12)
0.94 (43.42)
0.93 1.00
GG3%SIF 0.90 (15.82)
0.95 (0.25)
0.9589 (53.19)
0.97 0.85
GG5%SGF 0.96 (8.50)
0.95 (0.067)
0.96 ( 28.77)
0.97 0.62
GG5%SIF 0.89 (11.73)
0.56 0.13)
0.87 (37.75)
0.97 0.79
NaALG1%SGF 0.67 (1.52)
0.69 (.008)
0.79 (5.77)
0.81 0.30
NaALG1%SIF 0.80 (7.76)
0.94 (0.09)
0.90 (26.77)
0.88 0.40
NaALG3%SGF 0.54 (5.30)
0.36 (0.05)
0.50 (18.89)
0.80 0.65
NaALG3%SIF 0.79 (9.20)
0.89 (0.09)
0.90 (32.00)
0.92 0.55
NaALG5%SGF 0.84 (5.11)
0.89 (0.03)
0.93 (19.87)
0.93 0.71
NaALG5%SIF 0.87 (12.24)
0.98 (0.16)
0.95 (41.86)
0.93 0.70
XG1%NANOmet SGF
0.97 (9.48)
0.97 (-0.05)
0.94 (25.22)
0.93 0.77
XG1%NANOmet SIF
0.97 (10.81)
0.9693 (-0.08)
0.99 (32.08)
0.99 1.00
XG3%SGF 0.97 (6.37)
0.92 (0.05)
0.93 (25.23)
0.94 0.62
XG3%SIF 0.94 (9.62)
0.98 (0.07)
0.99 (32.08)
0.97 1.00
125
XG5%SGF 0.99 (6.32)
0.98 (-0.06)
0.94 (25.23)
0.99 0.79
XG5%SIF 0.98 (9.65)
0.98 (-0.06)
0.99 (32.08)
0.99 1.06
KEY:
AMS1%NANOmet = 1%W/V modified starch (AMS) and Metformin
AMS3%NANOmet = 3%W/V modified starch (AMS) and Metformin
AMS5%NANOmet = 5%W/V modified starch (AMS) and Metformin
GG1%NANOmet = 1%W/V Guar gum and Metformin
GG3%NANOmet = 3%W/V Guar gum and Metformin
GG5%NANOmet = 5%W/V Guar gum and Metformin
XG1%NANOmet = 1%W/V Xanthan gum and Metformin
XG3%NANOmet = 3%W/V Xanthan gum and Metformin
XG5%NANOmet = 5%W/V Xanthan gum and Metformin
NaALG1% NANOmet = 1%W/V Sodium alginate and Metformin
NaALG3% NANOmet = 3%W/V Sodium alginate and Metformin
NaALG5% NANOmet = 5%W/V Sodium alginate and Metformin
S.D = standad deviations
126
3.15 Statistical comparison of the Release profiles of nanocomposites using multiple
time points dissolution.
There was significant (P < 0.05) difference in the release profile among the various
nanocomposite formulations when studies were carried out in SGF. Post Hoc test was carried
out using SPSS v17 to detect the level of significance. AMS1% NANOmet (35.34±2.38) had
a significantly (P < 0.05) different release profile from AMS3%NANOmet (48.30 ± 3.47),
AMS5%NANOmet (56.95 ± 6.34) and GG3%NANOmet (53.10 ± 7.14). AMS1%NANOmet
also had different release profiles from NaALG1%NANOmet and XG3%NANOmet (48.93 ±
4.18). The release profile of AMS1% NANOmet in comparison with NaALG1%NANOmet
(21.68 ± 1.04) was significantly (P < 0.05) higher, but lower than the other nanocomposites
(AMS3%NANOmet (48.30 ±3.47), AMS5%NANOmet (56.95 ± 6.34), GG3%NANOmet
(53.10 ±7.14), NaALG1%NANOmet and XG3%NANOmet. AMS1%NANOmet had similar
profile to GG1%NANOmet, GG5%NANOmet (42.955 ± 4.70) and NaALG5%NANOmet
(35.10 ± 3.31). AMS3 %NANOmet (48.30 ± 3.47) had a similar (P > 0.05) release pattern
when compared to other nanocomposites prepared with same concentration (3 %) of polymer
(GG3%NANOmet (53.10 ± 7.14), XG3%NANOmet (48.93 ± 4.18)), with the exception of
NaALG 3% NANOmet with a significant (P < 0.05) different profile. The release profile of
AMS3%NANOmet was also not significantly (P > 0.05) different from AMS5%NANOmet
(56.95 ± 6.34) and GG5%NANOmet (42.95 ± 4.70). AMS3%NANOmet had significantly (P
< 0.05) higher release profile than GG1%NANOmet (28.88±3.43), NaALG1%NANOmet
(21.68 ±1.04), NaALG3%NANOmet (28.10 ± 4.29), and NaALG5%NANOmet (35.10 ±
3.31).
This may probably due to the fact that sodium alginate had fewer tendencies to sustain drug
release than modified starch [176-182]
127
In SGF, the release of metformin from AMS5%NANOmet had a significantly (P <
0.05) higher profile when compared with release from GG1%NANOmet, GG5%NANOmet
(42.95 ± 4.70) and all the nanocomposites containing sodium alginate; NaALG1%NANOmet
(21.68 ± 1.04), NaALG3%NANOmet (28.10 ± 4.29), NaALG5%NANOmet (35.10 ± 3.31).
AMS5%NANOmet had the highest release profile. GG1%NANOmet (28.88 ± 3.43) release
the drug by a lower profile than AMS3%NANOmet, AMS5%NANOmet (56.95 ± 6.34),
GG3%NANOmet (53.10 ± 7.14), GG5%NANOmet (42.95 ± 4.70) and XG3%NANOmet.
AMS1%NANOmet, NaALG1%NANOmet, NaALG3%NANOmet and GG1%NANOmet had
similar (P > 0.05) release profile. The release profile of metformin from GG3%NANOmet
was significantly (P < 0.05) higher than the release profiles from AMS1%NANOmet,
GG1%NANOmet, NaALG1%NANOmet, NaALG3%NANOmet and NaALG5%NANOmet
However, the release profile of metformin from GG3%NANOmet was not significantly (P >
0.05) different from the release profiles from AMS5%NANOmet, AMS3%NANOmet,
GG5%NANOmet and XG3%NANOmet. GG5%NANOmet released metformin by a
significantly (P < 0.05) less profile than AMS5%NANOmet but by a significantly (P < 0.05)
higher profile than GG1%NANOmet, NaALG1%NANOmet and NaALG3%NANOmet.
The release profile of metformin from GG5%NANOmet was similar (P > 0.05) to those from
AMS1%NANOmet, AMS3%NANOmet and GG3%NANOmet. NaALG5%NANOmet and
XG3%NANOmet were also similar in release profile. It is worthy to note here that from the
result of this research, the release profile of metformin from guar gum stabilized
nanoparticles is concentration dependent. Increase in polymer concentration leads to increase
in release profile for guar gum stabilized nanoparticles. NaALG1%NANOmet (21.68 ±1.04)
released the drug in vitro in a profile significantly (P < 0.05) less than AMS stabilized
nanoparticles. The drug release from NaALG1%NANOmet was not significantly (P > 0.05)
different from release from GG1%NANOmet and NaALG3%NANOmet. The release profile
128
of metformin from NaALG3%NANOmet (28.10 ± 4.29) was significantly (P<0.05) different
from release those of AMS3%NANOmet, AMS5%NANOmet, GG3%NANOmet,
NaALG5%NANOmet and XG3%NANOmet.
However the drug release from NaALG3%NANOmet was similar (P > 0.05) to release from
AMS1%NANOmet, GG1%NANOmet and NaALG3%NANOmet. NaALG5%NANOmet
release the metformin by a significantly (P < 0.05) less profile than AMS3%NANOmet,
AMS5%NANOmet, GG3%NANOmet, GG5%NANOmet, XG1%NANOmet (46.15 ± 5.88),
XG3%NANOmet (48.93 ± 4.18) and XG5%NANOmet (42.08±4.88) but by a significantly
(P<0.05) higher profile than NaALG1%NANOmet. The release profile of metformin from
NaALG5%NANOmet was similar (P > 0.05) to AMS1%NANOmet, GG1%NANOmet,
GG5%NANOmet, and NaALG3%NANOmet.
In SGF, the release profile of metformin from nanocomposites stabilized with sodium
alginate was found to be concentration dependent. The higher the polymer concentration, the
higher the release profile; NaALG1%NANOmet (21.68 ± 1.04), NaALG3%NANOmet
(28.10± 4.29) and NaALG5%NANOmet (35.10 ± 3.31).
Release of metformin from xanthan gum stabilized nanocomposite; XG1%NANOmet
(46.15 ± 5.88), XG3%NANOmet (48.93 ± 4.18) and XG5%NANOmet (42.08 ± 4.88) were
significantly (P < 0.05) higher than release from nanocomposites stabilized with sodium
alginate; NaALG1%NANOmet (21.68 ± 1.04), NaALG3%NANOmet (28.10 ± 4.29) and
NaALG5%NANOmet (35.10 ± 3.31). XG3%NANOmet released metformin by a profile
significantly (P < 0.05) higher than AMS1%NANOmet and GG1%NANOmet. There was
also significant (P < 0.05) difference in the release profile of metformin from the various
nanocomposite formulations when studies were carried out in SIF. Post Hoc test was carried
out using SPSS v17 to detect the level of significance. Metformin release from AMS1%
NANOmet (45.19 ±7.21) had a significantly less release profile than GG1%NANOmet
129
(75.28 ± 4.91), GG3%NANOmet (66.73 ± 8.66), NaALG1%NANOmet (67.86 ± 4.32),
NaALG3%NANOmet (67.25 ± 5.14), and NaALG5%NANOmet (71.23 ± 5.82). The release
profile of AMS1% NANOmet in comparison with AMS3%NANOmet (55.42 ± 6.37),
AMS5%NANOmet (56.21 ± 6.57), GG5%NANOmet (47.88 ±7.12), XG1%NANOmet
(50.89±6.62), XG3%NANOmet (46.88 ± 5.70) and XG5%NANOmet (43.95 ± 6.14) were
not significantly (P > 0.05) different.
Release of Metformin from AMS3%NANOmet (55.42 ± 6.37) had a similar (P >
0.05) profile to other nanocomposites apart from GG1%NANOmet (75.28±4.91) which had a
significantly (P < 0.05) higher release profile in SIF. AMS5%NANOmet (56.21 ± 6.57),
nanocomposites prepared with sodium alginate like NaALG1%NANOmet (67.86 ± 4.32),
NaALG3%NANOmet (67.25 ± 5.14) and NaALG5%NANOmet (71.23 ± 5.82) had similar
release profile. The release of metformin from AMS5%NANOmet also had similar (P > 0.05)
profile as release from AMS1%NANOmet, AMS3%NANOmet, GG3%NANOmet (66.73 ±
8.66), GG5%NANOmet (47.88 ±7.12).
The release profile of metformin from AMS 5%NANOmet was however, significantly (P <
0.05) lower than release from GG1%NANOmet (75.28 ± 4.91)
From the results so far, it is observed that there is no significant difference in the release
profile of metformin from nanocomposites stabilized with AMS (AMS1%NANOmet
(45.19±7.21), AMS3%NANOmet (55.42 ± 6.37) and AMS5%NANOmet (56.21 ± 6.57)
when release studies was carried out in SIF. The release of metformin from AMS
nanocomposites was not polymer concentration dependent.
The release of the metformin from GG1%NANOmet had the highest profile. This
profile was higher than those from all AMS stabilized nanocomposites; AMS1%NANOmet
(45.19±7.21), AMS3%NANOmet (55.42 ± 6.37) and AMS5%NANOmet (56.21 ± 6.57).
Others are GG5%NANOmet (47.88±7.12) and XG3%NANOmet (46.88 ± 5.70). The release
130
profile of metformin from GG3%NANOmet (66.73 ± 8.66) and (NaALG1%NANOmet
(67.86 ± 4.32), NaALG3%NANOmet (67.25 ± 5.14), NaALG5%NANOmet (71.23±5.82)
was not significantly (P>0.05) different from that of GG1%NANOmet (75.28 ± 4.91).
Drug release from GG3%NANOmet (66.73 ± 8.66) was significantly (P < 0.05)
higher than from AMS1%NANOmet, GG5%NANOmet (47.88 ± 7.12) and XG3%NANOmet
(46.88 ± 5.70). The release of metformin from this nanocomposite (GG3%NANOmet) was
quite similar (P > 0.05) to AMS3%NANOmet, AMS5%NANOmet, GG1%NANOmet and all
sodium alginate stabilized nanocomposites (NaALG1%NANOmet (67.86 ± 4.32),
NaALG3%NANOmet (67.25 ± 5.14), NaALG5%NANOmet (71.23 ± 5.70).
Metformin release profile from GG5%NANOmet had a significantly (P < 0.05) lower profile
compared to release from GG1%NANOmet, GG3%NANOmet, NaALG1%NANOmet (67.86
± 4.32), NaALG3%NANOmet (67.25 ± 5.14), and NaALG5%NANOmet (71.23 ± 5.70).
When compared with release profiles from XG3%NANOmet, AMS1%NANOmet (45.19 ±
7.21), AMS3%NANOmet (55.42 ± 6.37) and AMS5%NANOmet (56.21 ± 6.57) were similar
when release studies were carried out in SIF.
It is interesting to note that the release profile of Metformin from guar gum stabilized
nanocomposites was inversely proportional to polymer concentration when studies were
carried out in SIF. The lower the concentration of polymer, the higher the release profile of
the drug. GG1%NANOmet, GG3%NANOmet, GG5%NANOmet had release profiles of
75.28 ± 4.91, 66.73 ± 8.66 and 47.88 ±7.12 respectively.
Sodium alginate stabilized metformin loaded nanoparticles; NaALG1%NANOmet
(67.86 ± 4.32), NaALG3%NANOmet (67.25 ± 5.14), NaALG5%NANOmet (71.23 ± 5.70)
have similar profiles (P > 0.05) in the release of metformin from the nanocomposites. The
metformin release profile from these nanocomposites composed of sodium alginate was
significantly (P < 0.05) higher than release from AMS1%NANOmet (45.19 ± 7.21),
131
GG5%NANOmet (47.88 ± 7.12) and XG3%NANOmet (46.88 ± 5.70). The release profile
was not different from AMS3%NANOmet, AMS5%NANOmet, GG1%NANOmet and
GG3%NANOmet. The concentration of polymer did not have significant (P > 0.05) effect on
the release profile of Metformin.
XG1%NANOmet (50.89 ± 6.62), XG3%NANOmet (46.88 ± 5.70) and XG5%NANOmet
(43.95 ± 6.14) release metformin in a profile similar (P> 0.05) to all AMS stabilized
nanocomposites ; AMS1%NANOmet (45.19 ± 7.21), AMS3%NANOmet (55.42 ± 6.37) and
AMS5%NANOmet (56.21 ± 6.57) and GG5%NANOmet (47.88±7.12) but significantly
(P<0.05) less than GG1%NANOmet (75.28±4.91), GG3%NANOmet (66.73 ± 8.66) and all
sodium alginate stabilized nanocomposites namely ; NaALG1%NANOmet (67.86 ± 4.32),
NaALG3%NANOmet (67.25 ± 5.14) , NaALG5%NANOmet (71.23 ± 5.70).
During studies in SIF, the release of Metformin from AMS and Xanthan gum
nanocomposites was not polymer concentration dependent.
3.16. Comparison of nanocomposites using similarity factor (f2)
The similarity factor (f2) calculated based on excel template gave the value of 27,
which is less than 50. The two NANOmet formulations were not considered similar (95).
They have different release profiles.
The difference factor (f1) between AMS1%NANOmet and AMS5%NANOmet was
27 while the similarity factor was 35. The f2 was still outside the range of 50 to 100 which
indicates in the sample pairs evaluated [225]
The f2 value for the pair of AMS3%NANOmet and AMS5%NANOmet was 38;
which is still considered as dissimilarity in their release profiles. From the above findings, it
is observed that the release profiles of AMS NANOmets are polymer concentration
dependent. However the similarity factor increased in this order: AMS1%NANOmet and
132
AMS3%NANOmet < AMS1%NANOmet and AMS5%NANOmet < AMS3%NANOmet and
AMS5%NANOmet (27 < 35 < 38)
The dissolution profile comparison between the guar gum NANOmet stabilized with
1% and the sample stabilized with 3 % of the gum showed a similarity factor (f2) of 31. This
value confirms a difference in the dissolution profiles of the two nanocomposites
(GG1%NANOmet VS GG3%NANOmet).
The similarity factor (f2) calculated based on excel template gave the value of 16,
which is less than 50. The two NANOmet formulations were therefore not considered similar
([225]. They have different release profiles.
GG3%NANOmet VS GG5%NANOmet had a similarity factor of 26, which indicates
that the two NANOmet formulations are dissimilar in their drug release profiles.
NaALG1% NANOmet and NaALG3% had different release profile as the similarity
factor between the pair was 42; a value less than the standard for comparison which is 50 to
100 [225]
The pair of sodium alginate stabilized nanocomposites (NaALG1%NANOmet VS
NaALG5%NANOmet) had different dissolution profiles as their f2 value was 39.
Interestingly NaALG3%NANOmet VS NaALG5%NANOmet had similar release
profile. They had similarity factor f2 of 66 and difference factor f1 of 5 [225]. Among the
sodium alginate stabilized nanoparticles pairs compared, only NaALG3%NANOmet VS
NaALG5%NANOmet had similarity in their released profiles.
XG1% NANOmet and XG3% had similar release profile as the similarity factor (f2)
between the pair was 65; a value which falls within the standard for comparison which is 50
to 100 [225]. The f1 was 7.
The pair of xanthan gum stabilized nanocomposites (XG3%NANOmet VS
XG5%NANOmet) had different dissolution profiles as their f2 value was 49 while f1 was 20
133
XG3%NANOmet VS XG5%NANOmet had different release profile with similarity
factor f2 of 41 and difference factor f1 of 28.
For xanthan gum nanoparticles pairs compared, only XG1%NANOmet VS XG3%NANOmet
had similarity in their released profiles.
The similarity factor between AMS3%NANOmet and GG5%NANOmet was 34, a
value which was close to but still fell outside the acceptable range of 50 to 100 (95) for the
pair to be considered similar. Both nanocomposites were considered different in release
profiles.
The similarity factor between AMS3%NANOmet and NaALG5%NANOmet was 35,
a value which was outside the acceptable range of 50 to 100 for the pair to be considered
similar. The pair was therefore considered different in release profile.
The similarity factor for the above pair (GG3%NANOmet and NaALG5%NANOmet)
was 55. This value fell within the range. The release profiles of both NANOmets were
therefore considered similar.
The similarity factor between AMS5%NANOmet and GG3%NANOmet was 31, a
value which close to but still fell outside the acceptable range of 50 to 100 for the pair to be
considered similar. Both nanocomposites were considered different in release profiles.
The similarity factor between XG3%NANOmet and GG5%NANOmet was 43. The
pair had different release profile. This is because the value was outside the acceptable range
of 50 to 100 for the pair to be considered similar.
The similarity factor f2 between AMS3%NANOmet and XG3%NANOmet was 10.
The pair was considered to have different release profile as the value fell outside the
acceptable range of 50 to 100 for the pair to be considered similar.
In all the analyses of pairs of NANOmets, only three pairs showed similarity in their
release profiles ( NaALG3%NANOmet and NaALG5%NANOmet, GG3%NANOmet and
134
NaALG5%NANOmet) and (XG1%NANOmet and XG3%NANOmet) . The three pairs had f2
of 66, 55 and 65 respectively.
The Food and Drug Administration (FDA) and European Medicines Agency (EMEA)
defined similarity factor as a "logarithmic reciprocal square root transformation of one plus
the mean squared (the average sum of squares) differences of drug percent dissolved between
the test and the reference products" [226]. In other words, the similarity factor (f2) is a
logarithmic transformation of the sum-squared error of differences between the test Tt and
reference products Rt over all time points. It represents closeness of paired formulations.
Generally similarity factor in the range of 50-100 is acceptable according to US FDA.
Equation for calculation of similarity factor [226-227]
f2 = 50 + log {[1+ (1/n) nt=1 * n (Rt-Tt)2]-0.5 *100}.............(eq. 1)
Where Rt and Tt are the cumulative percent released at each of the selected n time points of
the paired products respectively
The primary purpose of Similarity factor is to compare the closeness of two products under
evaluation. The wide application of similarity factor signifies it as an efficient tool for
comparison of dissolution profiles. Similarity factor finds its main application as; response or
dependent variable usually for optimization purposes, e.g. to compare manufacturing
processes for establishing experimental conditions maximizing similarity between
formulations. Part of a decision criterion to establish similarity of two formulations. The
regulatory suggestion "decide similarity if (the sample) f2 exceeds 50" is applied in a literal
sense. This method is more appropriate when more than three or four dissolution time points
are available. The f2 may become invariant with respect to the location change and the
consequence of failure to take into account the shape of the curve and the unequal spacing
between sampling time points lead to errors. It is difficult to formulate a statistical
135
hypothesis for the assessment of dissolution similarity since f2 is only a sample statistic that
further complicates to evaluate false positive and false negative rates of decisions for
approval of drug products based on f2.
It may be too liberal in concluding similarity between dissolution profiles. Nevertheless, with
a slight modification in the statistical analysis, similarity factor would definitely serves as an
efficient tool for reliable comparison of dissolution profiles.
3.17: Antimicrobial Studies
Minimum inhibitory concentration values of nanocomposites tested against the
pathogens are presented in Table7. The minimum inhibitory concentration values of the
nanocomposites against tested microorganisms ranged from 2500–5000 μg/mL.
Ciprofloxacin had an MIC range of 0.5 –1.0 μg/mL against bacteria; Rifampicin had an MIC
of 0.625 μg/mL against Mycobacterium tuberculosis while Fluconazole had an MIC of 2.0
μg/mL against C. albicans
The MIC values of optimized nanocomposites against tested pathogens were in the
range of 2500- 5000 μg/mL. K.pneumonia, E.coli, S.aereus, P.aeruginosa, S.paratyphi and
C. albicans showed the MIC of 5000 μg/ mL for GG5%NANOme, while M.tuberculosis
showed the MIC of greater than 5000 μg/ mL for the same nanocomposite.
The MIC of NaALG5%NANOmet against tested microorganisms was also 5000 μg/
mL, with the exception of S.paratyphi which the NANOmet presented MIC of 2500 μg/ mL
The MIC values of XG5%NANOmet against tested pathogens was in the range of
2500-5000 μg/mL.The MIC values for XG5%NANOmet is same for GG5%NANOmet while
K.pneumonia, E.coli, S.aereus, P.aeruginosa, S.paratyphi and C. albicans showed the MIC
136
value of 5000 μg/ mL for this NANOmet, M.tuberculosis gave MIC of more than 5000 μg/
mL.The MIC of AMS5%NANOmet against tested microorganisms was also 5000 μg/ mL
with the exception of Pseudomonas aeruginosa to which the NANOmet presented MIC of
2500 μg/ mL.
In addition, AMS5%NANOmet presented MIC value of 3800 μg/mL, which is significantly
less (P < 0.05) than MIC for other NANOmet, against Mycobacterium tuberculosis.
Antimicrobial activity of silver nanoparticles has been demonstrated in several investigations,
but the reported MIC varies over a wide range [228]. Hence, it is difficult to compare results
obtained with nanoparticles, because there is no standard protocol for evaluation of
antimicrobial activity of nanoparticles and different methods have been used by different
researchers [228]. Silver is one of the most universal antimicrobial.Nanotechnology enables
us to expand the surface area of silver particles markedly. Several mechanisms have been
proposed to explain the inhibitory effect of silver nanoparticles on microbes. It is assumed
that the high affinity of silver towards sulfur and phosphorus is the key element of the
antimicrobial effect. Due to the abundance of sulfur-containing proteins on the bacterial cell
membrane, silver nanoparticles can react with sulfur-containing amino acids inside or outside
the cell membrane, which in turn affects bacterial cell viability [229]. It was also proposed
that silver ions (particularly Ag+) released from silver nanoparticles can interact with
phosphorus moieties in DNA, resulting in inactivation of DNA replication, or can react with
sulfur-containing proteins, leading to the inhibition of enzyme functions [230-232]. The
assumption is that Ag nanoparticle of less than 20 nm diameters get attached to sulfur-
containing proteins of bacterial cell membranes leading to higher permeability of the
membrane, which leads to bacteria lysis [231]. The dose dependent effect of silver
nanoparticles (15 nm) on the Gram-negative and Gram-positive pthogens has been
investigated [232]. At micro molar levels of Ag+ ions have been reported to uncouple
137
respiratory electron transport from oxidative phosphorylation, inhibit respiratory chain
enzymes, or interfere with the membrane permeability to protons and phosphate [233]. Also,
higher concentrations of Ag+ ions have been shown to interact with cytoplasmic components
and nucleic acids [234].
The silver nanocomposites synthesized and evaluated in this study showed moderate
antimicrobial activity against all the tested pathogens. The results of MIC tests revealed a
significantly (P < 0.05) higher MIC value for M.tuberculosis compared to the other tested
pathogens.
It is proper to state that the silver nanocomposites had broad spectrum of antimicrobial
activity with moderate effect on both gram positive and gram negative bacteria. They also
showed activity against yeast (Candida albicans)
138
Table 7: Minimum inhibitory concentration (MIC) of nanocomposites
MIC (µg /mL)
K.Pneumonia E.coli S.aerues Ps.aeruginosa S.paratyphi C.albicans M.tuberculosis AMS5%NANOmet 5000 5000 5000 2500 5000 5000 3800 GG55%NANOmet 5000 5000 5000 5000 5000 5000 >5000 XG5%NANOmet 5000 5000 5000 5000 5000 5000 >5000 NaALG5%NANO
met 5000 5000 5000 5000 2500 5000 3800
Ciprofloxacin 1.0 0.5 0.5 1.0 0.5 - - Fluconazole - - - - - 2.0 - Rifampicin - - - - - - 0.625
KEY AMS5%NANOmet = 5%W/V modified starch (AMS) and Metformin GG5%NANOmet = 5%W/V Guar gum and Metformin XG5%NANOmet = 5%W/V Xanthan gum and Metformin NaALG5%NANOmet = 5%W/V Sodium alginate and Metformin
139
3.18: Effect of nanocomposites in Glucose Loaded hyperglycemic rats
The oral glucose loading method was used. Normal Saline was used as negative
control while metformin served as positive control. For estimation of glucose levels in rats
treated with nanocomposites, blood samples were taken from tail veins at 0, 15, 30, 60, 90,
and 120 min after the glucose meal for the assay of glucose with ACUU – CHEK
glucometer and corresponding test strips.
At baseline, GG5%NANOmet (82.0±0.58) had the optimum glucose lowering effect.
At a dose of 500mg/Kg, this nanocomposite produced significant (P < 0.001) decrease in
elevated blood glucose level in hyperglycemic rats when compared to control (92.40 ± 0.31).
Metformin (90.60 ± 0.31) and other nanocomposites treated groups; AMS5%NANOmet
(106.80 ± 0.42), NaALG5%NANOmet (97.40 ± 1.30), and XG5%NANOmet (88.40 ± 1.22).
At baseline, AMS1%NANOmet produced the highest blood glucose level. This is probably
due to the presence of starch in the formulation as AMS is modified starch.
After 15 mins, the glucose lowering effect of GG5%NANOmet (144.60 ± 1.33) was
still significantly (P< 0.05) better than the control, metformin and other nanocomposites. The
glucose lowering effect of control, normal saline, NaALG5%NANOmet (161.40 ± 0.87),
XG5%NANOmet (164.00 ± 1.15) and Metformin (165.20 ± 1.91) were similar (P > 0.05).
Interestingly AMS5%NANOmet produced a significant decrease in blood compared to
(normal saline) (165 ± 1.73) NaALG5%NANOmet (161.4 ± 0.87), XG5%NANOmet (164.00
± 1.15) and Metformin (165.20 ± 1.91)
After 30 min, the glucose lowering effect of GG5%NANOmet (104.80 ± 1.74) was
still optimum. Its glucose lowering effect was significantly (P < 0.05) better than the control,
metformin and other formulations. The glucose lowering effect of NaALG5%NANOmet
(161.40 ± 0.87), XG5%NANOmet (164.00 ± 1.15) and Metformin (165.20 ± 1.91) were
140
similar (P > 0.05). The least effect on blood glucose lowering was observed with normal
saline which served as control (160.60 ± 2.39)
After 1h, the plasma glucose lowering effect of GG5%NANOmet (84.40 ± 1.30) was
optimum. Its glucose lowering effect was significantly (P < 0.05) better in comparison with
control, metformin and other NANOmet formulations..The glucose lowering effect of
Metformin (94.2.0±2.46), the standard drug, NaALG5%NANOmet (97.60 ± 1.22) and
AMS5%NANOmet (102.20 ± 0.92) were similar (P > 0.05). The least effect on blood glucose
lowering was still observed with normal saline which served as control (153.80 ± 0.42)
GG5%NANOmet (83.60 ± 0.70) had the optimum glucose lowering effect, followed
by Metformin (88.20 ± 1.00) and AMS5%NANOmet (97.60 ± 0.92). At a dose of 500mg/Kg,
GG5%NANOmet produced significant (P < 0.001) decrease in elevated blood glucose level
in hyperglycemic rats when compared to control. Metformin and other NANOmet treated
groups. There was no significant (P > 0.05) difference between NaALG5%NANOmet
(102.6±1.78) and XG5%NANOmet (104.4±1.78). As expected, normal saline (146.40 ± 1.83)
had the least effect on blood glucose lowering.
After 2 h, the results showed similar trend to glucose lowering effect after 90 min .with little
improvement. GG5%NANOmet (76.60 ± 0.83) had the optimum glucose lowering effect,
followed by Metformin (82.00 ± 0.23) and AMS5%NANOmet (89.60 ± 1.78). There was no
significant (P > 0.05) difference between NaALG5%NANOmet (93.40 ± 0.70) and
XG5%NANOmet (93.60 ± 1.78). As expected, normal saline (139.00 ± 1.53) had the least
effect on blood glucose lowering. The plasma glucose levels of the normal rats reached a
peak at 15 minutes after the oral administration of glucose and gradually decreased to the pre-
prandial level, (Table 8).
141
Guar gum, the stabilizing polymer for GG5%NANOmet, has been reported to reduce
postprandial absorption from the small intestine and glucose level in systemic circulation
[235]
142
Table 8: Effect of nanocomposites in glucose loaded hyperglycemic rats
Treatment(500mg/kg)
Plasma glucose levels (Mg/dl)
Baseline 15 min 30 min 60 min 90 min 120 min
Normal saline 92.4±0.31 165.0±1.73 160.6±2.39 153.8±0.42 146.4±1.83 139.0±1.53
AMS5%NANOmet 106.8±0.42 149.2±1.40 145.2±2.44 102.2±0.92 97.6±1.14 89.6±1.78
NaALG5%NANOmet 97.4±1.30 161.4±0.87 131.0±2.08 97.6±1.22 102.6±1.78 93.6±0.70
XG5%NANOmet 88.4±1.22 164.0±1.15 150.2±1.97 110.8±1.91 104.4±1.83 93.4±0.83
Metformin 90.64±0.31 165.2±1.91 138.8±1.67 94.2±2.46 82.2±1.00 82.0±0.23
GG5%NANOmet 82.0±0.58 144.6±1.33 104.8±1.74 84.4±1.30 83.6±0.70 76.6±0.83
KEY AMS5%NANOmet = 5%W/V modified starch (AMS) and Metformin GG5%NANOmet = 5%W/V Guar gum and Metformin XG5%NANOmet = 5%W/V Xanthan gum and Metformin NaALG5%NANOmet = 5%W/V Sodium alginate and Metformin
143
CHAPTER FOUR
CONCLUSION
In this research work, Metformin loaded silver nanocomposites were synthesised successfully
using ecofriendly method with neem as reducing agent and two natural polymers; Guar gum,
xanthan gum, Sodium alginate, and a semi- synthetic polymer as stabilizing agents. There is
no record of this research finding in literature.
UV-vis spectroscopy confirmed the formation of silver nanoparticles with absorption
peak at 371nm for all the nanocompoaites except XG5%NANOmet with peak at 335 nm. The
particle size ranged from 188 nm to 689 nm. The nanocomposites showed extended and
controlled release profiles.The kinetics of release was predominantly zero order for most of
the nanocomposites.
Nanocomposites did not have significant antimicrobial properties. However, in vivo anti
hyperglycemia studies in rats revealed that guar gum stabilized nanocomposites showed
significant reduction in blood glucose when compared to metformin.
Nanocomposite prepared from guar gum (GG5%NANOmet) can replace metformin in the
control of diabetes mellitus. The polymer, guar gum used in the synthesis is biocompatible,
cheap and readily available.
144
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164
APPENDIX
AMS1%NANOmet Release Profile
TIME(H) SGF SGF SIF SIF
Percent Release in SGF
Percent Release in SIF
ABS CONC ABS CONC 0.5 0.581 0.0054 0.466 0.0043 17.9982 14.3319
1 0.754 0.0071 0.646 0.0068 23.6643 22.6644 1.5 0.926 0.0087 0.737 0.0069 28.9971 22.9977
2 0.983 0.0092 0.816 0.0077 30.6636 25.6641 2.5 1.012 0.0095 0.986 0.0085 31.6635 28.3305
3 1.058 0.0099 1.008 0.0095 32.9967 31.6635 3.5 1.089 0.01027 1.077 0.0101 34.22991 33.6633
4 1.094 0.0103 1.078 0.0102 34.3299 33.9966 4.5 1.095 0.01032 1.161 0.0109 34.39656 36.3297
5 1.097 0.01034 1.248 0.0118 34.46322 39.3294 5.5 1.233 0.0116 1.617 0.0153 38.6628 50.9949
6 1.284 0.0121 1.627 0.0154 40.3293 51.3282 6.5 1.4 0.0132 2.19 0.0268 43.9956 89.3244
7 1.578 0.0149 3.115 0.0296 49.6617 98.6568 7.5 1.715 0.0162 3.115 0.0296 53.9946 98.6568
AMS3%NANOmet Release Profile
TIME(H) SGF SGF SIF SIF
Percent Release in SGF
Percent Release in SIF
ABS CONC ABS CONC 0.5 0.572 0.0053 0.227 0.002 17.6649 6.666
1 1.07 0.0101 1.018 0.0096 33.6633 31.9968 1.5 1.148 0.0108 1.296 0.0122 35.9964 40.6626
2 1.256 0.0119 1.471 0.0139 39.6627 46.3287 2.5 1.316 0.0124 1.501 0.0142 41.3292 47.3286
3 1.557 0.0147 1.665 0.0157 48.9951 52.3281 3.5 1.57 0.0148 1.672 0.0158 49.3284 52.6614
4 1.747 0.0165 1.787 0.0169 54.9945 56.3277 4.5 1.79 0.0169 1.803 0.0171 56.3277 56.9943
165
5 1.813 0.0172 1.828 0.0172 57.3276 57.3276 5.5 1.86 0.0176 1.95 0.0184 58.6608 61.3272
6 1.908 0.0181 2.113 0.02 60.3273 66.66 6.5 1.93 0.0183 3.151 0.0299 60.9939 99.6567
7 1.932 0.0183 3.151 0.0299 60.9939 99.6567 AMS5%NANOmet Release Profile
TIME(H) SGF SGF SIF SIF
Percent Release in SGF
Percent Release in SIF
ABS CONC ABS CONC 0.5 0.571 0.0053 1.044 0.0098 17.66 32.66
1 0.942 0.0089 1.142 0.0108 29.66 36.00 1.5 1.078 0.0101 1.162 0.0109 33.66 36.33
2 1.093 0.0103 1.165 0.011 34.33 36.66 2.5 1.191 0.0112 1.36 0.0128 37.33 42.66
3 1.575 0.0149 1.42 0.0134 49.66 44.66 3.5 1.6 0.0151 1.476 0.0139 50.33 46.33
4 1.944 0.0184 1.665 0.0157 61.33 52.33 4.5 2.263 0.0214 1.676 0.0158 71.33 52.66
5 2.464 0.0234 1.701 0.0161 77.99 53.66 5.5 2.628 0.0249 1.71 0.0162 82.99 53.99
6 2.644 0.0251 3.151 0.0299 83.66 99.66 6.5 2.644 0.0251 3.151 0.0299 83.66 99.66
7 2.644 0.0251 3.151 0.0299 83.66 99.66
166
GG1%NANOmet Release Profile
TIME(H) SGF SGF SIF SIF
Percent Release in SGF
Percent Release in SIF
ABS CONC ABS CONC
0.5 0.083 0.0007 1.227 0.0116 2.8 46.4 1 0.23 0.0021 1.285 0.0121 8.4 48.4
1.5 0.373 0.0034 1.461 0.0138 13.6 55.2 2 0.511 0.0047 1.544 0.0146 18.8 58.4
2.5 0.583 0.0054 1.596 0.0151 21.6 60.4 3 0.636 0.0059 1.604 0.0152 23.6 60.8
3.5 0.692 0.0065 1.781 0.0168 26 67.2 4 0.718 0.0067 2.129 0.0202 26.8 80.8
4.5 0.721 0.0068 2.249 0.0213 27.2 85.2 5 0.733 0.0069 2.436 0.0231 27.6 92.4
5.5 0.836 0.0078 2.505 0.0237 31.2 94.8 6 0.951 0.0089 2.505 0.0237 35.6 94.8
6.5 1.235 0.0116 46.4 7 1.236 0.0117 46.8
7.5 1.242 0.0117 46.8 8 1.251 0.0118 47.2
8.5 1.278 0.012 48 9 1.31 0.0124 49.6
9.5 1.322 0.0125 50 10 1.341 0.0126 50.4
GG3%NANOmet Release Profile
) SGF SGF SIF SIF
Percent Release in SGF
Percent Release in SIF
TIME(H ABS CONC ABS CONC 0.5 0.152 0.0013 0.337 0.0031 5.20 12.40
1 0.453 0.0042 0.655 0.0061 16.80 24.40 1.5 0.77 0.0072 0.978 0.0092 28.80 36.80
2 1.109 0.0105 1.214 0.0114 42.00 45.60 2.5 1.343 0.0127 1.631 0.0154 50.80 61.60
3 1.475 0.0139 1.903 0.018 55.60 72.00 3.5 1.829 0.0173 2.155 0.0204 69.20 81.60
4 1.904 0.018 2.302 0.0226 72.00 90.40 4.5 1.95 0.0185 2.484 0.0235 74.00 94.00
5 1.956 0.0185 2.484 0.0235 74.00 94.00 5.5 1.96 0.0186 2.484 0.0235 74.40 94.00
167
6 1.962 0.0186 2.484 0.0235 74.40 94.00 7 1.962 0.0186 2.484 0.0235
GG5%NANOmet Release Profile SGF SGF SIF SIF
TIME(H) ABS CONC ABS CONC % RELEASE IN SGF
% RELEASE IN SIF
0.5 0 0 0.285 0.0026 12.4 10.40 1 0.337 0.0031 0.454 0.0042 22.8 16.80
1.5 0.689 0.0057 0.662 0.0062 28 24.80 2 0.751 0.007 0.849 0.008 34 32.00
2.5 0.905 0.0085 1.033 0.0097 34.4 38.80 3 0.918 0.0086 1.148 0.0108 36.8 43.20
3.5 0.984 0.0092 1.236 0.0117 38.8 46.80 4 1.027 0.0097 1.311 0.0124 48.4 49.60
4.5 1.281 0.0121 1.457 0.0138 52 55.20 5 1.374 0.013 1.515 0.0143 62.4 57.20
5.5 1.648 0.0156 1.534 0.0145 62.8 58.00 6 1.658 0.0157 2.5 0.0237 62.8 94.80 7 1.658 0.0157 2.5 0.0237 62.8 94.80
NaALG1%NANOmet Release Profile SGF SGF SIF SIF
168
TIME(H) ABS CONC ABS CONC % RELEASE IN SGF
% RELEASE IN SIF
0.5 0.225 0.002 0.546 0.0051 10 25.5 1 0.393 0.0036 1.015 0.0096 18 48
1.5 0.434 0.004 1.231 0.0116 20 58 2 0.443 0.0041 1.316 0.0124 20.5 62
2.5 0.476 0.0044 1.382 0.013 22 65 3 0.489 0.0045 1.42 0.0134 22.5 67
3.5 0.49 0.0045 1.47 0.0139 22.5 69.5 4 0.494 0.0046 1.541 0.0146 23 73
4.5 0.499 0.0046 1.59 0.015 23 75 5 0.508 0.0047 1.602 0.0151 23.5 75.5
5.5 0.515 0.0048 1.67 0.0158 24 79 6 0.525 0.0049 1.719 0.0163 24.5 81.5
6.5 0.542 0.005 1.803 0.0171 25 85.5 7 0.542 0.005 1.803 0.0171 25 85.5
NaALG3%NANOmet Release Profile
SGF SGF SIF SIF % RELEASE IN SGF
% RELEASE IN SIF
TIME(H) ABS CONC ABS CONC 0.5 0.145 0.0013 0.48 0.0045 5.2 18
1 0.324 0.003 0.92 0.0087 12 34.8 1.5 0.464 0.0043 1.243 0.0117 17.2 46.8
2 0.565 0.0053 1.465 0.0138 21.2 55.2 2.5 0.641 0.006 1.645 0.0155 24 62
3 0.677 0.0063 1.807 0.0171 25.2 68.4 3.5 0.701 0.0066 1.861 0.0176 26.4 70.4
4 0.704 0.0066 1.912 0.0181 26.4 72.4 4.5 0.72 0.0067 1.97 0.0186 26.8 74.4
5 0.725 0.0068 1.975 0.0187 27.2 74.8 5.5 0.739 0.0069 1.978 0.0187 27.6 74.8
6 0.748 0.007 1.981 0.0188 28 75.2 6.5 0.749 0.007 1.991 0.0188 28 75.2
7 0.751 0.007 2.093 0.0198 28 79.2 7.5 1.096 0.0103 2.531 0.024 41.2 96
8 2.248 0.0213 2.592 0.0246 85.2 98.4
169
NaALG5%NANOmet Release Profile
SGF SGF SIF SIF % RELEASE IN SGF
% RELEASE IN SIF
TIME(H) ABS CONC ABS CONC 0.5 0.176 0.0016 0.364 0.0034 6.4 13.6
1 0.317 0.0029 0.841 0.0079 11.6 31.6 1.5 0.477 0.0044 1.238 0.0117 17.6 46.8
2 0.649 0.0061 1.514 0.0143 24.4 57.2 2.5 0.83 0.0078 1.7 0.0161 31.2 64.4
3 0.974 0.0092 1.854 0.0175 36.8 70 3.5 1.022 0.0096 1.976 0.0187 38.4 74.8
4 1.048 0.0099 2.098 0.0199 39.6 79.6 4.5 1.07 0.0101 2.162 0.0205 40.4 82
5 1.095 0.0103 2.266 0.0215 41.2 86 5.5 1.129 0.0106 2.288 0.0217 42.4 86.8
6 1.162 0.011 2.291 0.0217 44 86.8 6.5 1.181 0.0111 2.3 0.0218 44.4 87.2
7 1.191 0.0112 2.304 0.0218 44.8 87.2 7.5 1.304 0.0123 2.317 0.022 49.2 88
8 1.306 0.0123 2.365 0.0244 49.2 97.6 XG1%NANOmet Release Profile
TIME(H) SGF SGF SIF SI|F
% RELEASE IN SGF
% RELEASE IN SIF
0.5 0.320 0.154 0.0029 0.0014 8 4 1 0.364 0.270 0.0034 0.0025 12.6 8.5
170
1.5 0.443 0.445 0.0041 0.0041 16.7 15.9 2 0.522 0.574 0.0049 0.0054 24.5 22
2.5 0.579 0.842 0.0054 0.0079 28 26 3 0.643 1.010 0.0060 0.0095 29.5 28
3.5 0.801 1.087 0.0075 0.0102 33.5 30.5 4 0.963 1.146 0.0091 0.0108 39 43
4.5 1.244 1.232 0.0118 0.0116 43.6 47.5 5 1.365 1.269 0.0129 0.0120 50 49.8
5.5 1.553 1.540 0.0147 0.0146 52 53 6 1.565 1.666 0.0148 0.0158 54.4 55
6.5 1.713 1.807 0.0162 0.0171 57 59.2 7 1.762 1.935 0.0167 0.0183 60 61.272
7.5 1.824 1.984 0.0173 0.0188 63 64.5 8 1.920 2.226 0.0182 0.0211 71 89
8.5 1.960 2.342 0.0186 0.0222 72.5 90 XG3%NANOmet Release Profile SGF SGF SIF SIF
TIME(H) ABS CONC ABS CONC % RELEASE IN SGF
% RELEASE IN SIF
0.5 0.26 0.0024 0.129 0.0011 10.212 4.6805 10.21 1 0.475 0.0044 0.241 0.0022 18.722 9.361 18.72
1.5 0.646 0.0068 0.467 0.0043 28.934 18.2965 28.93 2 0.836 0.0078 0.684 0.0064 33.189 27.232 33.19
2.5 1.04 0.0098 0.854 0.008 41.699 34.04 41.70 3 1.153 0.0109 0.988 0.0093 46.3795 39.5715 46.38
3.5 1.291 0.0122 1.089 0.0103 51.911 43.8265 51.91 4 1.329 0.0126 1.162 0.011 53.613 46.805 53.61
4.5 1.375 0.013 1.224 0.0115 55.315 48.9325 55.32 5 1.392 0.0131 1.284 0.0121 55.7405 51.4855 55.74
5.5 1.406 0.0133 1.349 0.0127 56.5915 54.0385 56.59 6 1.42 0.0134 1.447 0.0137 57.017 58.2935 57.02
6.5 1.451 0.0137 1.507 0.0142 58.2935 60.421 58.29 7 1.46 0.0138 1.519 0.0144 58.719 61.272 58.72
7.5 1.616 0.0153 1.656 0.0157 65.1015 66.8035 65.10 8 1.629 0.0154 1.903 0.018 65.527 76.59 65.53
8.5 1.862 0.0176 2.363 0.0224 74.888 95.312 74.89
171
XG5%NANOmet Release Profile
SGF SGF SIF SIF
% RELEASE IN SGF
% RELEASE IN SIF
TIME(H) ABS CONC ABS CONC 0.5 0.209 0.110 0.0019 0.0009 8 4
1 0.322 0.221 0.0030 0.0020 12.6 8.5 1.5 0.423 0.403 0.0039 0.0037 16.7 15.9
2 0.616 0.554 0.0058 0.0052 24.5 22 2.5 0.702 0.653 0.0066 0.0061 28 26
3 0.739 0.702 0.0069 0.0066 29.5 28 3.5 0.838 0.764 0.0079 0.0072 33.5 30.5
4 0.973 1.072 0.0092 0.0101 39 43 4.5 1.087 1.183 0.0102 0.0112 43.6 47.5
5 1.244 1.240 0.0118 0.0117 50 49.8 5.5 1.294 1.318 0.0122 0.0125 52 53
6 1.353 1.368 0.0128 0.0129 54.4 55 6.5 1.417 1.471 0.0134 0.0139 57 59.2
7 1.491 1.522 0.0141 0.0144 60 61.272 7.5 1.565 1.602 0.0148 0.0152 63 64.5
8 1.762 2.206 0.0167 0.0209 71 89 8.5 1.799 2.231 0.0170 0.0212 72.5 90
172
y = 104.95x + 0.0113
R2 = 0.9998
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
0 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018
Conc (mg/mL)
Ab
sorb
ance
Calibration curve for metformin Hcl