formulation & in vitro evaluation of floating tablet · pdf filemultiple regression...

Vol-3, Issue-4, Suppl-1, Nov 2012 ISSN: 0976-7908 Soni et al

www.pharmasm.com IC Value – 4.01 2477

PHARMA SCIENCE MONITOR

AN INTERNATIONAL JOURNAL OF PHARMACEUTICAL SCIENCES

FORMULATION & IN VITRO EVALUATION OF FLOATING TABLET OF

TOLPERISONE HCl

Ravi Soni*, Mukesh Patel, Kanu Patel, Natubhai Patel

Shri B.M.Shah College of Pharmaceutical Education and Research, Dhansura road, College campus, Modasa, Gujarat, India-383315.

ABSTRACT This investigation describes the development of a Floating matrix tablet for Tolperisone HCl. The 32 full factorial design was employed to evaluate effect of total polymer content (X1) and hydroxypropyl methyl cellulose HPMC K4M/HPMC K100M ratio (X2) on drug release from HPMC matrices. Tablets were prepared using direct compression technique. Formulations were evaluated for in vitro buoyancy and drug release study using United States Pharmacopeia (USP) 24 paddle type dissolution apparatus using 0.1N HCl as a dissolution medium. Multiple regression analysis was performed for factorial design batches to evaluate the response. All formulations had floating lag times below 2 minutes and total floating time (TFT) more than 24 hours. It was found that polymer content and polymer ratio affect percentage drug release at 6 hours, percentage drug release at 12 hours, percentage drug release at 18 hours, percentage drug release at 24 hours, release rate constant(k), and diffusion exponent(n). Both formulation variables were found to be significant for the release properties (P < .05). Kinetic treatment to dissolution profiles revealed drug release ranges from anomalous transport to case 1 transport, which was mainly dependent on both the independent variables. Keywords: hydroxypropyl methylcellulose (HPMC), 32 factorial design, floating tablets. INTRODUCTION[1-5]

Tolperisone, a centrally acting muscle relaxant agent, which has been in therapeutic use

for more than three decades, has been widely used as spasmolytics of choice. It is

recently launched drug in India for acute and chronic back pain and spasticity of

neurological origin. It has also been used in treatment of condition which includes

dysmenorrhoea, climacteric complaints, lockjaw, and neurolatyrism.[1]

Tolperisone hydrochloride is a “Class-I” drug according to Biopharmaceutics

Classification System (BCS), possessing both high solubility and high permeability

absorption characteristics. Tolperisone hydrochloride is rapidly and completely absorbed

from the gastrointestinal tract. Peak plasma concentrations are reached 0.9-1.0 hours after

oral dosing and its elimination half-life ranges from 1.5 to 2.5 hr. [2]



Tolperisone hydrochloride has a short elimination half- life and rapidly absorbed from

gastrointestinal tract. [2] If it is formulated by conventional tablets, it will require multiple

daily administrations (2-3 times daily) which ultimately results into inconveniency to the

patients and possibility of reduced compliance with prescribed therapy. Tolperisone

conventional tablets are unable to ensure a constant concentration of the active substance

(tolperisone) in the blood. However, especially in cases of spastic muscle cramps, a

constant efficacy throughout the night is very important to the quality of life of the

patients. Known tablet formulations release the active substance tolperisone in the

intestine at pH 4 to 7. In this pH range, tolperisone breaks down into 4-MMPPO and

piperidine, this can be demonstrated in laboratory tests. Thus, the patient is exposed to an

uncontrollable quantity of 4-MMPPO [2methyl-1-(4methylphenyl)-propanone]. Proposed

are floating tolperisone tablets with the controlled release of the active substance

tolperisone in the stomach at pH 1 to 2. For tolperisone, a floating tablet based on the

effervescent approach having a lower density than the gastric juice was developed. By

adding acid adjuvant, such as citric acid, it is possible to produce a GRDDS (Gastro

Retentive Drug Delivery System) that is free from 4-MMPPO. [3]

The present investigation describes the formulation development of an floating drug-

delivery system for Tolperisone HCl. It will be evaluated for buoyancy property, content

uniformity, and In-Vitro drug release for 24 hours.

MATERIALS AND METHODS

Materials

Tolperisone HCl was received as a gift sample from Themis medicare Ltd. (Vapi, India).

Methocel K4M (4000 mPa.s) and Methocel K100M (100000 mPa.s) were received as a

gift sample from Colorcon Asia Pvt Ltd (Goa, India). Sodium bicarbonate and fumaric

acid were purchased from Finar Chemicals Ltd. (Ahmedabad, India). Poly vinyl

pyrollidone was purchased from Oxford chemicals Ltd (Mumbai, India). All ingredients

used in study are of analytical grade.

Methods

Preparation of Tolperisone HCl floating matrix tablets



Tablets were prepared by direct compression technique. Tolperisone HCl was mixed with

the required components except magnesium stearate by geometric mixing. The powder

blend was then lubricated with magnesium stearate (1%) and manually compressed on 10

station rotary tablet machine using 12 mm standard concave face punch. The tablet

characteristics were shape, round and concave: size, average diameter of 12 ± 0.1 mm

and thickness of 4.0 ± 0.2 mm; and hardness, range of 6 to 7 kg/cm2.

In vitro buoyancy study

The in vitro buoyancy was characterized by floating lag time (FLG) and total floating

time (TFT). The test was performed using USP 24 type II paddle apparatus using 900 of

0.1 N HC1 at 100 rpm at 37±0.5°C. The time required for tablet to rise to surface of

dissolution medium and duration of time the tablet constantly float on dissolution

medium were noted as FLG and TFT, respectively (n=3).

In vitro drug release study

The in vitro drug release was performed using USP 24 type II paddle apparatus using 900

ml of 0.1 N HC1 at 100 rpm at 37±0.5°C. The samples were withdrawn at predetermined

time intervals for period of 12 hr and replaced with the fresh medium. The samples were

filtered through 0.45 µm membrane filter, suitably diluted and analyzed at 260 nm using

double beam UV/Vis spectrophotometer. The content of drug was calculated using

calibration curve.

Full Factorial Design

The goal of pharmaceutical formulation and development centre is to develop an

acceptable pharmaceutical formulation in the shortest possible time using minimum

number of personnel, time and raw materials. The formulae developed by the formulation

and development centre is then tried at the pilot plant scale and manufacturing scale.

Ideally, minor changes are to be made during scale up. It is therefore very essential to

study the formulation from all perspectives[4, 5]. In addition to the art of formulation,

statistical techniques are available that can aid in the pharmacist's choice of formulation

components which can optimize one or more formulation attribute[6]. It is well known

that the traditional experiments involve a good deal of efforts and time especially when

complex formulations are to be developed. A very efficient way to enhance the value of



research and to minimize the process development time is through various experimental

designs[7, 8]. Factorial designs are used in experiments, where the effects of different

factors or conditions on experimental results are to be evaluated[9].

In factorial designs, levels of factor are independently varied, each factor at two or more

levels. A factor is an assigned variable such as concentration, temperature, lubricating

agent, drug treatment or diet. Factor may be qualitative or quantitative. The levels of a

factor are the values or designations assigned to the factors. The runs or trials that

comprise full factorial experiments consist of all combinations of all levels of all factors.

The effect of a factor is the change in response caused by varying the levels of the factor.

The important objective of a factorial experiment is to characterize the effect of changing

the levels of factor or combination of factors on the response variable. The predictions

based on results of an undersigned experiment will be less variable. The optimization

procedure is facilitated by construction of an equation that describes the experimental

results as a function of the factors.

A 32 randomized full factorial design was used in development of dosage form. In this

design, two factors were evaluated each at three levels and experimental trials were

performed at all possible nine combinations. The content of polymer (X1) and ratio of

HPMC K4M to HPMC K100M (X2) were selected as independent variables. Percentage

drug release at 2 hr (Q2), 6 hr (Q6), 12 hr (Q12), 18 hr (Q18), 24 hr (Q24), release rate

constant (K) and diffusion exponent (n) were selected as dependent variables. The

content of polymer was evaluated at 125mg, 150mg, and 175mg while the ratio of HPMC

K4M and HPMC K100M was evaluated at 75:25, 50:50 and 25:50. The experimental

design with corresponding formulations is outlined in Table 2, 3, 4. A statistical model

incorporating interactive and polynomial terms was utilized to evaluate the response

(equation 1) [9]

Y = bo + b1X1 + b2X2 + bl2X1X2 + b11X1X1 + b22X2X2 (1)

Where Y is the dependent variable, βo is the arithmetic mean response of the 9 runs, and

bi is the estimated coefficients for the factor X. The main effect (X1 and X2) represents

the average result of changing one factor at a time from its low to high value. The

interaction term (X1X2) shows how the response changes when two factor are change



simultaneously. The polynomial term (X1X1, X2X2) are included to investigate

nonlinearity. The magnitude of the coefficients represents the relative importance of each

factor. Once the polynomial equation has been established, an optimum formulation can

be found by grid analysis.

Statistical Analysis

The statistical analysis of the factorial design batches was performed by multiple

regression analysis using Microsoft Excel. To evaluate the contribution of each factor

with different levels on responses, 2-way analysis of variance (ANOVA) followed by

Tukey test was performed using Sigma Stat software (Sigma Stat 2.03, SPSS, Chicago,

IL). To demonstrate graphically the influence of each factor on responses, the response

surface plots were generated using Sigma Plot software Version 8.0, (Jandel Scientific

Software, San Rafael, CA). The P < .05 was considered to be significant.

TABLE 1: FORMULATION LAYOUT FOR FACTORIAL BATCHES

Batch Coded value Uncoded value

X1 X2 X1 (mg) X2 (mg)

F1 -1 -1 125 93.75:31.25

F2 -1 0 125 62.5:62.5

F3 -1 1 125 31.25:93.75

F4 0 -1 150 112.5:37.5

F5 0 0 150 75:75

F6 0 1 150 37.5:112.5

F7 1 -1 175 131.75:43.75

F8 1 0 175 87.5:87.5

F9 1 1 175 43.75:131.75

All batches contain 450mg Tolperisone Hcl, 10% sodium bicarbonate, 10% Fumaric acid, 1% magnesium stearate, 1% aerosil.



TABLE 2: RESULT OF TABLET FOR FACTORIAL BATCHES Batch code

Assay (%)

± S.D

Average weight

(mg) ± S.D (n=20)

Hardness (Kg/cm2)

± S.D (n=5)

Friability (%)

Buoyancy characteristics

FLT (sec)

TFT (hr)

F1 100.2± 0.21 758 ± 1.29 6.6 ± 0.15 0.40 32 >24 F2 98.65±0.17 761 ± 1.74 6.7 ± 0.12 0.79 30 >24 F3 99.30±0.13 757 ± 1.18 6.8 ± 0.15 0.66 35 >24 F4 100.43±0.26 788 ± 1.49 6.6 ± 0.14 0.76 30 >24 F5 100.21±0.11 786 ± 1.19 6.8 ± 0.19 0.38 35 >24 F6 97.25±0.17 789 ± 1.19 6.7 ± 0.15 0.76 34 >24 F7 99.86±0.25 820 ± 1.35 6.7 ± 0.23 0.24 36 >24 F8 101.54±0.44 819 ± 1.28 6.9 ± 0.17 0.37 34 >24 F9 101.45±0.31 821 ± 1.19 6.7 ± 0.21 0.49 35 >24

TABLE 3: RESULT OF DEPENDENT VARIABLES FOR FACTORIAL DESIGN BATCHES

Batch code

Percentage drug release Release rate constant

(k)

Diffusion exponent

(n) Q2 Q6 Q12 Q18 Q24 F1 41.12 61.55 94.09 100.69 100.69 0.2620 0.5022 F2 34.03 53.17 79.37 100.19 100.19 0.2300 0.5013 F3 29.01 48.03 70.31 97.06 101.55 0.2034 0.5140 F4 35.15 54.20 83.30 100.34 100.34 0.2257 0.5161 F5 22.09 47.44 67.92 88.43 100.73 0.1650 0.5792 F6 21.70 41.25 65.64 81.66 93.06 0.1503 0.5817 F7 23.24 44.21 70.25 91.28 101.48 0.1617 0.5916 F8 21.79 42.33 63.56 80.53 93.31 0.1502 0.5798 F9 18.48 29.79 45.31 62.26 78.58 0.1201 0.5558



TABLE 4: MULTIPLE REGRESSION OUTPUT FOR DEPENDENT VARIABLES

Parameter Coefficient of Regression Parameter

b0 b1 b2 b11 b22 b12 R2 p Q2

FM 24.882 -6.777 -5.054 1.630* 2.148* 1.837* 0.944 0.043 RM 27.401 -6.777 -5.054 - - - 0.886 0.001

Q6 FM 48.391 -7.738 -6.815 -1.112* -1.143* -0.225* 0.972 0.015 RM 46.887 -7.738 -6.815 - - - 0.964 0.000

Q12 FM 71.485 -10.776 -11.063 -1.801* 1.198* -0.290* 0.955 0.031 RM 71.083 -10.776 -11.063 - - - 0.948 0.000

Q18 FM 90.704 -10.645 -8.554 -1.476* -0.838* -6.347 0.988 0.004 RM 89.162 -10.645 -8.554 - - -6.347 0.984 0.000

Q24 FM 99.460 -4.843 -4.887 -2.077* -2.124* -5.938 0.969 0.018 RM 96.659 -4.843 -4.887 - - -5.938 0.930 0.003

k FM 0.177 -0.044 -0.029 0.008* 0.005* 0.004* 0.967 0.019 RM 0.185 -0.044 -0.029 - - - 0.953 0.000

n FM 0.566* 0.035* 0.007* -0.018* -0.010* -0.012* 0.785 0.276

*Indicate the value is insignificant at P = 0.05; FM: full model, RM: reduced model.



TABLE 5: RESULTS OF ANALYSIS OF VARIANCE FOR MEASURED

RESPONSE

Source Model DF SS MS F R2 FCAL FCRI Q2

Regression FM 5 456.90 91.38 10.06 0.94

1.03 9.28 RM 2 428.85 214.42 23.27 0.89

Error FM 3 27.24 9.08 - - RM 6 55.29 9.21 - -

Q6

Regression FM 5 643.17 128.63 20.88 0.97

0.29 9.28 RM 2 637.88 318.94 80.49 0.96

Error FM 3 18.49 6.16 - - RM 6 23.77 3.96 - -

Q12

Regression FM 5 1440.83 288.17 12.65 0.95

0.14 9.28 RM 2 1431.13 715.57 55.02 0.95

Error FM 3 68.34 22.78 - - RM 6 78.03 13.00 - -

Q18

Regression FM 5 1285.86 257.17 49.94 0.99

0.56 9.55 RM 3 1280.10 426.70 100.60 0.98

Error FM 3 15.45 5.15 - - RM 5 21.21 4.24 - -

Q24

Regression FM 5 442.71 88.54 18.77 0.97

1.87 9.55 RM 3 425.06 141.69 22.28 0.93

Error FM 3 14.15 4.72 - - RM 5 31.80 6.36 - -

k

Regression FM 5 0.0169 0.0034 17.81 0.97

0.43 9.28 RM 2 0.0167 0.0084 61.26 0.95

Error FM 3 0.0006 0.0002 - - RM 6 0.0008 0.0001 - -

DF: degree of freedom, SS: sum of squares, MS: mean of squares, F: Fischer’s ratio, R2: regression coefficient.



Figure 1 Influence of polymer blend and content of SLS on (A) Q2 (B) Q6 (C) Q12 (D) Q18 (E)

Q24 (F) n and (G) k.



Figure 2 Effect of ratio of polymer (HPMC K100M ) on release rate constant at total polymer

content of (a) 125mg (b) 150mg (c) 175mg.



TABLE 6: RESULT OF TUKEY TEST PERFORMED USING TWO WAY

ANOVA

Response Comparison

for levels

P

Total polymer content

(X1)

Ratio of HPMC K15M to HPMC K100M

(X2)

Q2

-1 vs 1 0.014 0.038

-1 vs 0 0.068 0.105

0 vs 1 0.234 0.555

Q6

-1 vs 1 0.002 0.004

-1 vs 0 0.043 0.068

0 vs 1 0.016 0.023

Q12

-1 vs 1 0.007 0.006

-1 vs 0 0.117 0.048

0 vs 1 0.044 0.09

Q18

-1 vs 1 0.037 -

-1 vs 0 0.314 -

0 vs 1 0.179 -

Q24

-1 vs 1 - -

-1 vs 0 - -

0 vs 1 - -

K

-1 vs 1 0.003 0.011

-1 vs 0 0.017 0.06

0 vs 1 0.053 0.167

n

-1 vs 1 - -

-1 vs 0 - -

0 vs 1 - -



RESULTS AND DISCUSSION In the present investigation, total content of polymer and the ratio of HPMC K15M to

HPMC K100M were studied using 32 full factorial designs. Tablets of all formulations

had floating lag time below 2 minutes regardless of ratio of HPMC K15M to HPMC

K100M and content of polymer. Also, all formulations had to constantly float on

dissolution medium for more than 24 hours. All batches of tablet have desirable physical

properties and meet the terms of assay of Tolperisone HCl, weight variation and friability

test according to USP 28 (Table 2). The Q2, Q6, Q12, Q18, Q24, release rate constant (k),

and diffusion exponent (n) showed wide variation (Table 3). The data clearly indicate that

the dependent variables are strongly dependent on the independent variables. The fitted

equation relating the response Q2, Q6, Q12, Q18, Q24, k, and n to the transformed factor

are shown in Equation 2 to Equation 8.

Q2 = 24.9 - 6.78 X1 - 5.05 X2 + 1.63 X11 + 2.15 X22 + 1.84 X12 (2)

Q6 = 48.4 - 7.74 X1 - 6.81 X2 - 1.11 X11 - 1.14 X22 - 0.22 X12 (3)

Q12 = 71.5 - 10.8 X1 - 11.1 X2 - 1.80 X11 + 1.20 X22 - 0.29 X12 (4)

Q18 = 90.7 - 10.6 X1 - 8.55 X2 - 1.48 X11 - 0.84 X22 - 6.35 X12 (5)

Q24 = 99.5 - 4.84 X1 - 4.89 X2 - 2.08 X11 - 2.12 X22 - 5.94 X12 (6)

k = 0.177 - 0.043 X1 - 0.029 X2 + 0.0075 X11 + 0.0054 X22 + 0.0042 X12 (7)

The high values of correlation coefficient for the dependent variables indicate a good fit

of the model (R2 > 0.9). The negative sign of b1 and b2 coefficient indicates that as the

level of X1 and X2 increases the drug release decreases. The coefficient of X1 (b1) is

greater than coefficient of X2 (b2) indicating that drug release retarding effect of X1 is

more than factor X2.

To demonstrate graphically the effect of total content of polymer and the ratio of HPMC

K15M to HPMC K100M, the response surface plots (Figure 1) were generated for the

dependent variables, using statastica software. Multiple regression analysis was

performed using Microsoft Excel. Results of multiple regression analysis showed that the

total content of polymer and the ratio of HPMC K15M to HPMC K100M have significant

influence on percentage drug release at 2, 6, 12 and 18 hours (P < 0.05, Table 4). Results



of ANOVA for the measured responses are provided in Table 6. To evaluate the

contribution of different levels of factor (X1) and factor (X2), 2-way ANOVA followed

by Tukey test was performed using Sigma Stat software (Table 6). For factor X1, it was

found that there is a statistically significant difference between the 1 and -1 level as well

as 0 and 1 level except (between 0 and 1 for Q8, Q16), (P < 0.05). For factor X2, it was

found that there is a statistically significant difference between levels 1 and -1 (P < 0.05,

Table 5.13). A significant influence of polymer weight on drug release was observed

when polymer weight was shifted from 125 mg to 175 mg, which might be due to the

formation of strong gel layer build up at higher polymer content. A significant influence

of ratio of polymers on drug release was observed when ratio of HPMC K15M to HPMC

K100M was shifted from 75:25 to 25:75. This test was not performed for Q24, k because

X1 and X2 both were found to be insignificant at p>0.05.

There has been considerable interest in using different grades of HPMC in controlled-

release drug-delivery systems because of their hydrophilic nature and fast hydration[10].

The release profiles appear to be biphasic with initial burst effect followed by a polymer-

controlled slower release in the second phase. The difference in burst effect of the initial

time is a result of the difference in the viscosity of the polymeric mixtures[11] as well as

the amount of polymer, which mainly contributes to the dissolution of drug in the initial

period. The polymeric system with higher content of HPMC K15M yielded a faster initial

burst effect. Dortunc and Gunal[12] have reported that increased viscosity resulted in a

corresponding decrease in the drug release, which might be to the result of thicker gel

layer formation. On other hand, the apparent drug release rate observed in the second

phase from different polymeric mixtures is quite similar, which indicates that once the gel

layer forms there is no difference in the release rate from drug-delivery system.

Dissolution profiles were fitted with the power law equation given by Korsmeyer and

Peppas equation. Diffusion exponent ranges from 0.5013 to 0.5916, while release rate

constant ranges from 0.1201 to 0.2620, which indicates non-fickian drug release from

formulation. Both variables significantly affect the release rate constant (P < .05, Table 5)

Linear relationship was obtained between fraction of HPMC K100M and release rate

constant. It was observed that as the fraction of HPMC K100M increased, the rate of drug



release was retarded at all the 3 levels of polymer content which might be due to higher

viscosity of polymeric

CONCLUSION

In this study the attempt was made to develop once a day floating matrix tablet of

Tolperisone HCl using different grade of hydroxy propyl methyl cellulose as a matrix

forming polymer. Tablets had desired buoyancy characteristics. It was found that total

content of had dominant role on retardation of drug release from floating matrix tablets

compared to polymer ratio of HPMC K15M to HPMC K100M, although the presence of

later component in formulation is essential to improve the integrity of tablet. Use of

combination of polymer in tablet reduces the total content of polymer used. From the

conducted investigation it can be concluded that once a day Tolperisone HCl delivery is

feasible using hydroxy propyl methyl cellulose floating matrix tablet.

ACKNOWLEDGMENTS

Authors are thankful to Themis medicare Ltd. (Vapi, India) for providing gift sample of

Tolperisone HCl, Colorcon Asia Pvt Ltd (Goa, India), Finar Chemicals Ltd. (Ahmedabad,

India) and Oxford chemicals Ltd (Mumbai, India) for providing excipients.

REFERENCES

1. Cims India, Update – 3, July – October 2011, pp 39

2. www.ogyi.hu/kiseroirat/ph/ph_0000027201.pdf

3. Welzig S, Rothenburger J, Kälz B, Gungl J, Gerdes K. Tolperisone controlled

release tablet. European patent 2010; 2 228 056

4. Gabrielsson, J, lindberg NO and Lundstedt T. Multivariate methods in

pharmaceutical applications J.Chernometrics 2002;16:141-160,

5. Ford JL, Rubinstein MH, McCaul F, Hogan JE and Edgar PJ. Importance of drug

type, tablet shape and added diluents on drug release kinetics from hydroxypropyl

methyl cellulose matrix tablets. Int. J. Pharm. 1987;40:223-234.



6. Takahara J, Takayama K and Nagal T. Multiobjective simultaneous optimization

technique based on an artificial neural network in sustained release formulations.

J. Con. Rel. 1997;49:11-20.

7. Kramar A, Turk S, and Vrecer F. Statistical optimization of diclofenac sustained

release pellets coated with polymethacrylic films. Int J. pharm. 2003;256:43-52 .

8. Lunstedt T, Seifert E, Abramo L, Thelin B, Nystrom A, Pettersen J and Bergman

R. Experimental design and optimization. Chem. Intell. Lab. Sys. 1998;42:3-40.

9. Hamed E, and Sakr A. Application of multiple response optimization technique to

extended release formulation design. J.con. Rel. 2001;73:329-338.

10. Colombo P, Bettini R, Peppas NA. Observation of swelling process and diffusion

front position during swelling in HPMC matrices containing soluble drug. J

Control Release. 1999;61:83-91.

11. Dow Chemical Co. Methocel: Cellulose Ethers Technical Handbook. San Diego,

CA, USA: Dow Chemical Co; 1996:18-20.

12. Dortunc B, Gunal N. Release of acetazolamide from swellable HPMC matrix

tablets. Drug Dev Ind Pharm. 1997; 23:1245-1249.

For Correspondence: Ravi Soni Email: [email protected]

formulation & in vitro evaluation of floating tablet · pdf filemultiple regression...

Documents