Full Terms & Conditions of access and use can be found athttp://www.tandfonline.com/action/journalInformation?journalCode=iddi20

Download by: [Shashank Jain] Date: 22 April 2016, At: 16:08

Drug Development and Industrial Pharmacy

ISSN: 0363-9045 (Print) 1520-5762 (Online) Journal homepage: http://www.tandfonline.com/loi/iddi20

Application of Design of Experiments forFormulation Development and MechanisticEvaluation of Iontophoretic Tacrine HydrochlorideDelivery

Niketkumar Patel, Shashank Jain, Parshotam Madan & Senshang Lin

To cite this article: Niketkumar Patel, Shashank Jain, Parshotam Madan & Senshang Lin(2016): Application of Design of Experiments for Formulation Development and MechanisticEvaluation of Iontophoretic Tacrine Hydrochloride Delivery, Drug Development and IndustrialPharmacy, DOI: 10.1080/03639045.2016.1181646

To link to this article: http://dx.doi.org/10.1080/03639045.2016.1181646

Accepted author version posted online: 21Apr 2016.

Submit your article to this journal

View related articles

View Crossmark data

Application of Design of Experiments for Formulation Development and

Mechanistic Evaluation of Iontophoretic Tacrine Hydrochloride Delivery

Running Head: Transdermal iontophoresis of tacrine hydrochloride

Niketkumar Patel, Shashank Jain, Parshotam Madan and Senshang Lin*

College of Pharmacy and Health Sciences

St. John’s University, Queens, NY, USA

*Corresponding Author

Senshang Lin, Ph.D.

8000 Utopia Parkway, Queens, NY 11439, USA

Tel: (001) (718) 990 5344

Fax: (001) (718) 990 1877

E-mail: linse@stjohns.edu

Keywords:

Design of experiment; central composite design; transdermal iontophoresis; Alzheimer’s disease;

tacrine hydrochloride; conductivity

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Abstract

Objective: The objective of this investigation is to develop mathematical equation to understand

the impact of variables and establish statistical control over transdermal iontophoretic delivery of

tacrine hydrochloride. In addition, possibility of using conductivity measurements as a tool of

predicting ionic mobility of the participating ions for the application of iontophoretic delivery

was explored.

Method: Central composite design was applied to study effect of independent variables like

current strength, buffer molarity, and drug concentration on iontophoretic tacrine permeation

flux. Molar conductivity was determined to evaluate electro migration of tacrine ions with

application of Kohlrausch’s law.

Results: The developed mathematic equation not only reveals drug concentration as the most

significant variable regulating tacrine permeation, followed by current strength and buffer

molarity, but also is capable to optimize tacrine permeation with respective combination of

independent variables to achieve desired therapeutic plasma concentration of tacrine in treatment

of Alzheimer’s disease. Moreover, relative higher mobility of sodium and chloride ions was

observed as compared to estimated tacrine ion mobility.

Conclusion: This investigation utilizes the design of exprement approach and extends the

primary understanding of imapct of electronic and formulation variables on the tacrine

permeation for the formulation development of iontophoretic tacrine delivery. JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Introduction

The worldwide prevalence of Alzheimer’s disease was more than 35 million in 2010,

predicted to be more than 65.7 million in 2030 and 115.4 million by 20501. Tacrine (1, 2, 3, 4-

tetrahydro-5 aminoacridine) is a potent, centrally active, reversible cholinesterase inhibitor was

the first drug used to treat the symptoms of mild to moderate dementia of Alzheimer’s disease.

However, oral administration of tacrine has been associated with extensive first pass metabolism,

rapid clearance from the systemic circulation, dose-dependent hepatotoxicity, gastrointestinal

side effects and peripheral cholinenergic side effects2. With advancement in cholinesterase

inhibitors research, other more selective inhibitors, such as donepezil, rivastigmine and

galantamine, than tacrine are the current choice for the treatment of Alzheimer’s disease. Since

tacrine is a potent inhibitor of both acetylcholinesterase and pseudocholinesterase, it has been

proved efficacious molecule for Alzheimer’s treatment when it is available in systemic

circulation. To overcome such limitations administered orally, iontophoresis, where externally

applied current acts as a driving force, could be used to push tacrine ions through the stratum

corneum and subsequently enhance tacrine permeation through skin. Small doses required to

reach therapeutic concentration and physicochemical characteristics of tacrine make it a suitable

candidate for iontophoresis. In addition to the enhanced tacrine permeation, iontophoretic

delivery of tacrine could be advantageous in terms of patient compliance as it can be combined

with pre-programmed externally current controlled device for pre-programmed controlled

delivery to the patients automatically.

Review of literature reveals promising but scattered published work in the field of

iontophoretic delivery of tacrine hydrochloride. However, the primary focus of these studies are

evaluation of ion-exchange fibers3,4

and comparison of various enhancement methods used to

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

increased tacrine transdermal delivery5. Furthermore, although in vivo transdermal iontophoretic

delivery as a potential way to administer tacrine and the application of response surface

methodology to explain tacrine iontophoretic delivery in vitro have been reported2,6

, it still lacks

the systemic investigation of tacrine hydrochloride to achieve therapeutically effective tacrine

delivery. Relying on the published reports of promising possibility of delivering tacrine through

transdermal iontophoretic route, efforts in the direction of gaining formulation and delivery

knowledge have been undertaken in order to provide a platform for pre-programmed tacrine

delivery. As a part of these efforts, effect of various electronic and formulation variables was

studied on iontophoretic tacrine permeation across permeation membrane in detail in the earlier

published report7. Unfortunately, iontophoresis is a complex process and successful

iontophoretic drug delivery is dependent on multiple electronic and formulation variables. It

would be advantageous to apply current understanding of the effect of major variables on tacrine

permeation into quantification of their impact on permeation flux and subsequently the

therapeutic drug concentration. This understanding and quantization would allow formulators to

alter in vitro permeation flux to reach therapeutic drug concentration as per their need in future

studies. Furthermore, it is always better to achieve the required plasma concentration with

minimum current strength application in order to avoid any patient incompliance8,9

. With better

understanding and quantization of various effects on tacrine permeation, other variables can be

altered to compensate for the reduction in permeation flux with lowering current strength, if

required.

The design of experiment approach has been successfully utilized to optimize

compositions and to study the interactions of iontophoresis of lisinopril and methotrexate10,11

as

well as for other pharmaceutical application such as solid dispersions, solid lipid nanoparticles

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

and ethosomes12-14

. Among various designs, the advantage of central composite design is that

adding center points and star points to the initial factorial design allow the fitting of observed

data to a quadratic model and response surfaces analysis15

. Once the quadratic model is

established, it can be used to understand the interaction among the formulation variables and to

predict response variables for a known formulation composition. With a well-defined

experimental design, varied combination of formulation variables can be derived to achieve

desired permeation flux to reach therapeutic concentration in vivo.

In vitro tacrine permeation flux across various permeation membranes would provide an

estimation of prediction of steady-state plasma tacrine concentration by following equation2,16

.

Css = A K0/Cl (1)

where Css is the steady-state concentration of drug, A is the surface area available for drug

absorption, K0 is the zero-order drug permeation flux across the skin, and Cl is the clearance of

drug. Tacrine clearance is reported to be approximate 150 L/h and therapeutic effective tacrine

concentration of 5-30 ng/ml and 5-70 ng/ml was reported respectively by two different groups2,6

.

According to equation 1, iontophoretic delivery of tacrine having permeation flux in the range of

75-450 μg/cm2/h or 30-420 μg/cm

2/h with iontophoretic patch area of 10 cm

2 or 25 cm

2 has

potential to reach therapeutic concentration of 5-30 ng/ml or 5-70 ng/ml, respectively. The goal

of iontophoretic tacrine delivery should be to achieve this range of plasma concentration at

minimum current strength application with reasonable patch size.

The objective of this investigation is to use the design of experiments as a tool to extend

earlier gained tacrine permeation knowledge to define design space for iontophoretic tacrine

permeation and develop statistical control by modulation of electronic and formulation variables

to achieve desired drug permeation flux. These experiments will serve as a bridge between the

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

single factor at a time in vitro studies and future in vivo studies and allow formulators in a better

position to modulate the tacrine delivery with statistical control developed to achieve effective in

vivo results. In addition, the possibility of conductivity measurements as a tool of predicting the

ionic mobility of the participating ions for the application of transdermal iontophoretic delivery

was explored.

Materials and methodology

Materials

Tacrine hydrochloride powder (MW 198.26) was purchased from Sigma-Aldrich (St.

Louis, MO). Acetonitrile, methanol and triethlyamine were purchased from Fisher Scientific

(Hanover Park, IL). Monobasic potassium phosphate, sodium hydroxide and potassium chloride

were purchased from VWR International (Aurora, CO). Silver wire and silver chloride electrodes

were purchased from Warner Instruments (Hamden, CT) and In vivo Metric (Healdsburg, CA).

The Phoresor IITM

units were generous gifts from Iomed Inc. (Salt Lake City, UT). De-ionized

water was used for prepare solutions for all studies. All chemicals were HPLC or technical grade

and were used as received without further treatment.

In vitro permeation studies

The in vitro permeation studies were carried out using side-by-side glass permeation cells

having 0.64 cm2 surface area (Perme Gear, Hellerttown, PA). Freshly excised full thickness

abdominal skin from Sprague-Dawley rats (5–6 weeks old, 200–250 g) obtained from Charles

River Laboratories Inc. (Wilmington, MA) was used for permeation studies. Donor and receptor

compartments were clamped together, with rat skin sandwiched in-between, to avoid any leakage

from either of the compartments. Phosphate buffer solution (PBS; 50 mM, pH 7.4, 4 ml) was

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

used as receptor medium for all the experiments. Tacrine hydrochloride in PBS (4 ml) was then

introduced to the donor compartment. The contents of both compartments were continuously

stirred to achieve homogenous mixing of the solutions and the temperature of both compartments

was maintained at 32 ºC with a jacketed water bath. Care was taken to remove deposition of air

bubbles at the skin surface during the experiment. A pair of silver wire and silver chloride

electrode was used for the application of current and the setup of wire and electrode have been

described elsewhere7. Tacrine was delivered under anodal iontophoresis (basic drug, pKa 9.95).

Constant current strength of 0.1 mA (0.16 mA/cm2) to 0.3 mA (0.47 mA/cm

2) was generated by

the Phoresor IITM

. Samples (500 µl) were withdrawn at predetermined time intervals from the

receptor compartment and replaced with an equal volume of fresh PBS. The samples were then

analyzed by the HPLC method.

As a part of effort in correlating in vitro iontophoretic drug permeation profiles and

plasma profiles obtained from animal, SD rat skin was selected in this investigation due to the

fact that SD rats are easy to handle during the animal studies. Although the use of SD rats might

not correlate well with the use of human skin, the results obtained in this investigation would

allow researchers in a better position for the product development related to the iontophoretic

tacrine delivery via skin.

Analytical methodology

In vitro samples were analyzed for tacrine concentration using the HPLC modified from a

method published in literature2. HP 1100 series (Agilent Technologies, Wilmington, DE) with a

C18

Nova-Pak column (5.0 µm, 3.9 × 150 mm) were used. The mobile phase consisted of

acetonitrile, distilled water, and triethylamine at a ratio of 22:76:2 (v/v/v) was prepared and the

pH of the mixture was adjusted to 6.5 using acetic acid. The flow rate was set at 1 ml/min.

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Tacrine was detected at 320 nm with a retention time of 2.5 min. Calibration plots of tacrine

hydrochloride in the range of 1-500 µg/ml were developed. The peak area was observed to

increase linearly with respect to the increase in concentration of tacrine with a correlation

coefficient (r2) of 0.9998.

Application of design of experiments to optimize tacrine permeation

To depict the influence of electronic and formulation variables on tacrine permeation and

to optimize tacrine permeation flux further, a face-centered central composite design was used.

According to the face-centered design (alpha value of ± 1), the total number of experimental

combinations is 2k +2k + n0, where k is the number of independent variables and n0 is the number

of repetitions of the experiments at the center point17,18

. Current strength, buffer molarity and

drug concentration were found to be most influencing factors in single-factor-at-a-time studies

reported earlier7. Based on these results, current strength (0.1-0.3 mA), buffer molarity (25-100

mM), and drug concentration (1-20 mg/ml corresponding to 4.3-85.2 mM) were selected in the

design and tacrine permeation flux was evaluated as a response variable (Table 1). For number of

independent variables being 3 with 6 repetitions of the experiments at the center point, the design

containing 20 runs [8 (i.e., 23) factorial points and 6 (i.e., 2×3) star points plus 6 center points]

was generated and shown in Table 2. All other formulation and processing parameters were kept

invariant throughout the study. Tacrine permeation flux, as a response variable, was determined

experimentally across fresh abdominal rat skin described in the permeation studies. The observed

permeation flux was further analyzed by the statistical software package Design-Expert software

(Stat-Ease Inc., Minneapolis, MN). Each run based on the face-centered central composite design

was carried out in triplicate.

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

For the statistical analysis, the experimental variables Xi have been coded as xi according

to the following transformation equation:

ᵡi =Xi− Xo

δx (2)

where xi is the dimensionless coded value of the variable Xi, X0 is the value of Xi at the center

point and δX is the step change. This conversion of different levels of independent variables into

coded level helps to determine the relative magnitude of the independent variables impacting

tacrine permeation flux.

The response surface of tacrine permeation flux (Y) as a function of independent

variables (X1, X2, X3) can be expressed as Y = f(X1, X2, X3). Tacrine permeation flux was analyzed

by multiple regressions through the least squares method to fit the following polynomial

equation:

Y = b0 + b1X1 + b2X2 + b3X3 + b12X1 X2 + b13X1 X3 + b23X2 X3 + b11X1 2 + b22X2

2 +

b33X3 2 (3)

where Y is the tacrine permeation flux; b0 is the intercept; b1 to b33 are the regression coefficients

computed from the observed values of Y; and X1, X2 and X3 are the coded levels of independent

variables. The terms XiXj (i, j = 1, 2 or 3) and Xi2 (i = 1, 2, or 3) representing the interaction and

quadratic terms, respectively, are used to simulate the curvature of the design space.

Furthermore, the tacrine permeation flux was statistically analyzed by applying ANOVA at 0.05

level to determine the significance and the magnitude of the effects of independent variables in

Design-Expert software. Predictor equations for measured response containing only the

significant quadratic terms were generated using backward elimination procedure. The

significance of each of the coefficients for the quadratic terms in the empirical polynomial

equation was either selected or rejected based on the p value obtained. The quadratic terms

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

statistically found non-significant (p > 0.05) were removed from the initial polynomial equation

and the observed data were refitted until the final polynomial equation with reduced quadratic

terms was acquired11,13

. The accuracy and general ability of the polynomial equation could be

evaluated by the coefficient of determination (r2). The selection of polynomial equation for

analyzing the tacrine permeation flux was done based on the sequential equation sum of squares

(p value), lack of fit test and equation summary statistics. Statistically significant p value (p <

0.05) and adjusted determination coefficients (Adj-r2) between 0.8-1 associated to non-

statistically significant lack of fit (p > 0.05) were the criteria for selection of the final polynomial

equation chosen11

.

The effect of current strength, buffer molarity and drug concentration on tacrine

permeation flux was presented as response surface plots generated by the software for two

variables at a time. The graph was plotted to evaluate effect of tacrine concentration and buffer

molarity on tacrine permeation flux at different current strengths applied. Furthermore, by

intensive grid search performed over the whole observed region, seven checkpoint formulations

to achieve in vitro tacrine permeation flux in the range of 150-350 μg/cm2/h were selected for the

validation of the chosen experimental domain and the final polynomial equation (Table 3). The

checkpoint formulation variables were evaluated for permeation flux and the resultant observed

values of the permeation flux were quantitatively compared with the predicted values.

Mechanistic evaluation of iontophoretic tacrine permeation

In order to explore the possibility of establishing conductivity measurement as potential

tool to predict ionic mobility, simple conductivity measurements were carried and results were

evaluated to determine tacrine ionic mobility with and without the presence of sodium ions

(positive counter-ions). This method has an added advantage of simplicity and can be used to

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

screen the mediums causing the least hindrance to drug ion permeation in studies of

iontophoresis.

The specific conductivity of drug solutions (1-200 mM of tacrine hydrochloride) and the

same strength of sodium chloride in de-ionized water were determined at room temperature

using a digital conductivity meter (Traceable, Friendswood, TX). The specific conductance of

de-ionized water was measured in order to check the presence of any ionic impurities

(conductivity should not be more than 10 µS/cm). The molar conductivities (m), the specific

conductivity normalized by the concentration, of tacrine hydrochloride and sodium chloride

solutions were estimated from the measured specific conductance using the following

expression19,20

.

m = 1000 × K

Cs (4)

where k is the specific conductance and CS is the solute concentration.

The representation of molar conductivity (values from equation 5) as a function of the

square root of the molar concentration allowed estimation of molar conductivity at infinite

dilution for each salt. Molar conductivity of sodium chloride at the infinite dilutions was

determined in the similar manner and compared with the literature value to validate the

employed method. The molar conductivity of tacrine ions at infinity was deduced by the

application of the Kohlrausch’s law of independent migration of ions19,20

.

at infinity = C+at infinity+ + C−at infinity

− (5)

Finally, the mobility of tacrine ions was estimated by dividing its molar ionic conductivity by the

Faraday constant.

μ(mobility) = at infinity

F− μ(mobility) Cl− (6)

ttacrine = μtacrine

/(μtacrine

+ μcl

−) (7)

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Data analysis

The cumulative amount of tacrine permeated across the membranes was plotted as a

function of time. Permeation flux was calculated from the slope of linear portion of the plot

between 1-6 or 2-6 h of iontophoresis, in most cases. All results were expressed as mean ±

standard deviations of triplicate experiments. Student’s t-test was used when only two groups

were being compared. One-way ANOVA followed by Newman-Keuls multiple comparison test

was used for comparison of more than two groups. For all statistical analysis, the probability

value of less than 0.05 was considered to be significant.

Results and discussion

Application of design of experiments to optimize tacrine permeation

Design of experiments was applied to study iontophoretic tacrine permeation flux with

two major objectives: to understand the relative influence of electronic and formulation variables

on tacrine permeation flux and to quantify their effect to predict tacrine permeation flux, with

varied variable range, on the development of iontophoretic delivery of tacrine in human. The

polynomial equations, derived with application of design of experiments, would give an idea

about either positive or negative impact of the independent variables and their interactions on

tacrine permeation flux. The previous studies, based on one factor at time (OFAT) approach,

provided primary information about the effect of electronic and formulation variables on tacrine

permeation flux7. OFAT approach would help the formulator to screen the important

independent variables under the application of iontophoresis. The results obtained with OFAT

approach work best when there are no interactions among the independent variables. However,

OFAT, time- and labor-consuming strategy, may be ineffective if there is any potential

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

interactions between independent variables which can lead to unreliable results, inaccurate

conclusions and consequently unable to determine optimal administration of therapeutic

drug21,22

. Alternatively, statistical approach such as design of experiments provides the

understanding of interactions among independent variables with a minimum number of

experiments for a large number of independent variables evaluated. The statistical methods such

as response surface method (RSM) use quantitative data from appropriate design of experiments

to build a mathematical model21,23

.

From the results obtained in previous studies, the key independent variables, such as

current strength, drug concentration and buffer molarity, impacting iontophoretic tacrine

permeation were identified7. Lowest buffer molarity to maintain the pH of tacrine hydrochloride

solutions in the donor compartment was found to be 25 mM, the maximum concentration of

tacrine hydrochloride to achieve maximum tacrine permeation flux was 22.25 mg/ml, and the

current strength lower than 0.5 mA/cm2 (0.32 mA/0.64 cm

2 in this investigation) can be used

without potential patient incompliance. However, their interactive impact on tacrine permeation

was not studied. Based on these observations, the levels of 0.1-0.3 mA for current strength, 25-

100 mM for buffer molarity, 1-20 mg/ml for drug concentration were selected to define design

space of face-centered central composite design to study their relative impact on tacrine

permeation flux (Table 1). The tacrine permeation flux of twenty experimental runs, based on

central composite design, showed considerable variation ranging from 47.84 ± 11.90 to 477.09 ±

19.65 μg/cm2/h (Table 2). The results clearly indicate that tacrine permeation flux was strongly

affected by the independent variables selected and wide range of tacrine permeation flux was

observed within this design space. It would allow the formulator to further optimize tacrine

permeation efficiently with modulation of these independent variables to achieve therapeutic

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

plasma concentration of tacrine. It implies that the optimal tacrine permeation flux could be

achieved with more than one combination of independent variables. Depending upon the patient

acceptability and other factors, level of the independent variables could be adjusted and optimal

permeation flux could be customized.

By applying multiple regression analysis on the data collected, second order quadratic

equation was derived to explain tacrine permeation flux. Lower p value (0.0028) for F statistics,

low standard deviation (20.64), high adjusted r2 value (0.9646), and higher lack of fit p value

(0.0009) associated with quadratic equation suggest the sufficiency of quadratic equation for

further analysis. A lower value of coefficient of variation (8.93) indicates a better precision and

reliability of the experiments.

The polynomial equation, derived from multiple regression analysis, would give an idea

about if any interaction among the independent variables had either positive or negative impact

on tacrine permeation flux. The polynomial equation in coded variables could be used to study

the comparative effect of each independent variable on response variable. Coded variable

equation uses normalized values for each independent variable for prediction of the relative

impact of the independent variables irrespective of the input values. Equation in terms of coded

variables (regression equation for the fitted quadratic model) was found to be:

Y = 262.17 + 89.00 X1 − 37.80 X2 + 104.40 X3 + 33.00 X1X3 − 54.64 X32 (8)

where Y is the tacrine permeation flux; X1, X2 and X3 are current strength, buffer molarity, and

drug concentration, respectively. All the coefficients, except for X1X2, X2X3, X12 and X2

2, had a

statistically significant effect on tacrine permeation flux (p < 0.05) and were retained in the

equation. Coefficients with more than one independent variable represent an interaction effect,

whereas those with higher order terms denote quadratic relationships. A positive sign signifies a

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

synergistic effect while a negative sign signifies an antagonistic effect10,13

. The coefficients

obtained in the equation reflect the comparative effect of each independent variable and their

interactions on tacrine permeation flux. As shown in equation 8, regression coefficient of drug

concentration (X3) was larger than any other regression coefficients, and hence drug

concentration was the main independent variable having a positive impact on the iontophoretic

tacrine permeation flux. Current strength (X1) also indicates the highly positive effect on tacrine

permeation flux. Current provides driving force for the movement of tacrine ions across the skin

and drug concentration determines the transport number of tacrine ions, as discussed in details in

previously published report, could explain the higher tacrine permeation flux7. However,

negative coefficient of buffer molarity (X2) suggests that tacrine permeation flux was decreased

with increase in buffer molarity. Increase in co-ion competition to tacrine ions to carry current

with increase in buffer molarity resulted in decreased permeation. The lower coefficient

observed with buffer molarity indicates low prominence of buffer molarity in the presence of

other two variables to impact tacrine permeation. Other interaction and quadratic terms, X1X3 and

X32, show their positive and negative effect on tacrine permeation, respectively. It is interesting

to note that current strength was the main factor having a positive impact of tacrine permeation,

better than tacrine concentration, which is in agreement with the literature2. More influencing

impact of tacrine concentration over current strength on tacrine permeation in this study

reiterates the importance of using derived equations within the defined design space and

possibility of change in the relative impact of variable with change in design space.

Furthermore, the polynomial equation (uncoded) obtained from multiple regression

analysis, once properly validated, could be useful to predict the tacrine permeation flux with

varied range of independent variables within the design space. The equation with actual terms

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

considers the input values and predicts permeation flux without any normalization. Equation in

terms of uncoded independent variables (actual input values) was found to be:

Y = 57.75 + 254.20 𝑋1 − 0.72 𝑋2 + 16.45 𝑋3 + 34.73 X1X3 − 0.65 X32 (9)

where Y is the tacrine permeation flux; X1, X2 and X3 are current strength, buffer molarity, and

drug concentration, respectively. The equation in uncoded independent variables could be used

to obtain tacrine permeation flux with actual input values of current strength (X1), buffer molarity

(X2) and drug concentration (X3). The correlation plot between observed and predicted tacrine

permeation flux based on the quadratic equation used in face-centered central composite design

was shown in Figure 1. With the range of buffer molarity (25-100 mM) and tacrine concentration

(1-20 mg/ml) used in this design space, predicted permeation flux of 27.67-229.07 μg/cm2/h,

64.85-349.25 μg/cm2/h, and 122.67-490.07 μg/cm

2/h at current strength of 0.1 mA, 0.2 mA, and

0.3 mA were observed, respectively.

Response surface analysis

The relationship between tacrine permeation flux and independent variables was further

illustrated using response surface plot, which is useful to illustrate the interaction effects of the

independent variables on tacrine permeation flux. Equation 9 was used to construct the response

surface plot eliciting the effect of current strength (X1), buffer molarity (X2) and drug

concentration (X3) and their interactions on tacrine permeation flux (Figure 2). All presented

surfaces represent the effect of tacrine concentration and buffer molarity on tacrine permeation

flux at different current strengths of 0.1, 0.2 and 0.3 mA, respectively. The response surface plot

suggests that increase in tacrine concentration from 1 to 20 mg/ml increased permeation flux at

each applied current strength. Though the magnitude of the increase in permeation flux, with

increase in concentration from 1 to 20 mg/mL, was different at each current strength. Increase in

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

magnitude of permeation flux was observed with an increase in drug concentration regardless the

current strength applied. On the other hand, increasing buffer molarity had not shown significant

magnitude of decrease in permeation flux. Thus, the positive impact of drug concentration on

tacrine permeation flux augmented with increase in current strength, whereas almost similar

impact of buffer molarity on permeation flux was observed irrespective of the current strength

applied. This observation is supported with the presence of interaction between current density

and drug concentration as well as the absence of interaction between current strength and buffer

molarity shown in equation 9.

Synergistic effect of drug concentration and antagonistic effect of buffer molarity with

different magnitude at different current strength determine the shape of the response surfaces as

shown in Figure 2. The structure of the skin and permeability of the skin is affected by the

current strength as reported in the previous study7. With the application of 0.3 mA, skin is much

more permeable compared to that of 0.1 mA. With similar drug concentration in formulation, the

difference in the status of skin at different current strength application could be responsible for

the higher magnitude of permeation flux at higher current strength. Thus, apart from their direct

impact on permeation, interaction of drug concentration and current strength indicates their

positive impact on tacrine permeation flux. This can explain the presence of significant

interaction term X1X3 in the equation 8. The negative higher order concentration term can be

explained by the saturation of ion conductive pathways at higher concentration, resulting in

saturation of tacrine permeation7. On the other hand, the impact of change in drug concentration

was almost similar on tacrine permeation, irrespective of buffer molarity indicating the

insignificance of the interaction term X2X3. Similarities in the permeation flux at different current

strengths supported insignificance of X1X2 term in the equation 8.

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Validation of design of experiments

The goal of developing the quadratic equation 9 resulted from the design of experiments

was to predict the iontophoretic tacrine permeation flux at different combination of independent

variables within the design space. It is necessary to validate if the fitted mathematic model

provides an adequate approximation to the real system. Unless the mathematic model shows an

adequate fit, proceeding with the investigation and prediction of other responses within the

design space would likely to provide poor or misleading information. The equation predictability

was validated, within the range of 150-350 μg/cm2/h, with seven checkpoint formulations. The

composition and predicted responses of checkpoint formulations are listed in Table 3 for

validation of quadratic equation. Comparison of observed and predicted responses for the

checkpoint formulations indicates adequate ability of equation (r2

= 0.9767) to predict

permeation flux within the designed space (Figure 3). With the point optimization prediction

technique, equation 9 can be used to derive the independent variable levels to achieve desired

permeation flux. However, in predicting new observations and in estimating the mean response

at a given point, extrapolating beyond the region containing the original observations should be

concerned. It is very much possible that a model that fits well within the region (defined space)

of the original data will no longer fit well outside the region21,23

.

This validation indicates that equation 9 would able us to formulate different combination

of variables to achieve the desired tacrine permeation flux to reach therapeutic concentration in

vivo. In addition, overlap of resultant tacrine permeation flux at different current strengths would

allow adjusting other variables depending upon patient compliance at the desired current

densities. Selection of other variable at the desired current strength (lower current strength is

always preferred) would help to develop efficacious and patient acceptable combinations for

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

iontophoretic application. It is important to note that if higher/lower tacrine permeation flux

outside of the predicted range, at different current densities, is required, then defined independent

variables used for the design space should be adjusted. That includes the change in electrodes,

the use of alternate buffer system or further lowering buffer molarity (less than 25 mM) at the

expense of change in pH. With new defined experimental variables and conditions; new design

space can be defined and regression model can be achieved in the similar manner. In addition,

although the derived equations 8 and 9 from the permeation results across the SD rat skin would

not hold the same independent variable coefficients as compared to tacrine permeated across

human skin, these equations could provide some valuable information prior to animal and/or

clinical studies.

Mechanistic evaluations of tacrine iontophoretic permeation

Iontophoresis enhances the transdermal transport of charged and neutral molecules across

the skin under the application of a low electric field by means of passive permeation, electro-

osmosis and electro-migration24

. Moreover, evaluation of mechanical aspects of iontophoretic

tacrine delivery in an experiment concluded that electro migration is the primary mechanism

having 70-91% contribution to total tacrine permeation in the range of drug concentration from 1

to 20.0 mg/ml (data not included). In addition, it has been reported that iontophoretic tacrine

permeation drops in the presence of small ions due to ionic competition7. Tacrine ion migration

and conductivity of ions in a given medium under the current application mainly depends on the

similar physicochemical properties such as molecular weight, molecular size and the ionic

mobility of tacrine ions and henceforth estimation of molar conductivity would help to

understand tacrine ion behavior in the medium in presence of other ions and its relationship to

tacrine permeation25

.

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

The plot of molar conductivities as a function of the square root of molar concentration

reveals that molar conductivity decreased from 98.9 to 33.03 ohm-1

cm2mol

-1 with increase in

tacrine hydrochloride concentration from 1 to 200 mM (Figure 4). The same increase in sodium

chloride concentration resulted in decrease in molar conductivity of sodium chloride from 126.77

to 82.91 ohm-1

cm2mol

-1. The decrease in molar conductivity with increase in tacrine or sodium

ion concentration may be attributed to slower movement of ions in concentrated solutions. The y-

intercept of backward extrapolation of linear line indicates the molar conductivity of each

solution at the infinite dilution. Molar conductivity at infinite dilution of sodium chloride was

determined to be 130 ohm−1

cm2 mol

−1, a value close to reported value of 126-128 ohm

−1cm

2

mol−1

in literature25

. Whereas, molar conductivity of tacrine solution at infinite dilution was

determined to be 103.5 ohm−1

cm2mol

−1. The difference between molar conductivity of sodium

chloride and tacrine hydrochloride (26.5 ohm−1

cm2mol

−1) corresponded to the difference

between the molar ionic conductivities of sodium ions and tacrine ions at infinite dilution

(equation 5). Higher molar conductivity values for sodium chloride compared to tacrine

hydrochloride could be related to higher ionic mobility of sodium ions compare to tacrine

ions26,27

. When current is applied, higher mobility of sodium ions due to smaller ionic volume

and ionic weight makes them counter ions for tacrine ions during tacrine permeation across the

skin.

With reference value of ionic conductivity of sodium ions (50.11 ohm−1

cm2mol

−1)28

, a

molar ionic conductivity of 23.61 ohm−1

cm2mol

−1 can be estimated for tacrine ions which

calculates tacrine ionic mobility of 2.4 × 10−4

cm2 s

−1 V

−1 (equations 6 and 7). With reported

chloride ion mobility of 7.9×10−4

cm2 s

−1 V

−1 and calculated sodium ion mobility of 5.2 × 10

−4

cm2 s

−1 V

−1, ionic mobility ratio of ~ 2 for pair of Na

+/TH

+ and ~ 3.5 for pair of Cl

−/TH

+ can be

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

estimated28

. These estimated relative values (in the order of Cl- > Na

+ > TH

+ ) of ionic mobility

of the ions in the donor compartment could help to understand ionic competition provided by the

co-ions to tacrine ions resulting in decreased permeation.

Estimation of ionic mobility of drug ions might be a useful method to predict

iontophoretic permeation flux based on the ability of drug ions to conduct in the given medium.

However, the results obtained in this investigation do not provide the exact ionic mobility of

tacrine ion rather provide a platform to understand the possible reduction of tacrine permeation

flux in the presence of other co-ions and to estimate the iontophoretic permeation of other drug

based upon their ability to conduct in the medium. Obviously, more research is required to

understand the intriguing relationship between ionic mobility and iontophoretic permeation flux

and to extrapolate it to formulation benefit.

Conclusion

The results of this investigation utilizing the design of exprement approach extends the

primary understanding of imapct of electronic and formulation variables on the tacrine

permeation for the formulation development of iontophoretic tacrine delivery. Furthermore,

simple conductivity measurement is proven to be the potential tool to predict the tacrine and

other participating ionic mobility. Modulation of independent variables resulted in range of

tacrine permeation flux that suggests the feasiblity of approach to reach therapeutic tacrine

concentration levels in human.

Acknowledgements

The authors acknowledge St. Johns’ University for providing financial assistance and

research facilities to carry this research.

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Declaration of interest

The author declares no conflict of interest (monetary or otherwise) in conducting this

research. The authors alone are responsible for the content and writing of the paper.

References

1. Hebert LE, Weuve J, Scherr PA, et al. Alzheimer disease in the United States (2010-2050)

estimated using the 2010 census. Neurology 2013;80(19):1778-83.

2. Upasani RS, Banga AK. Response surface methodology to investigate the iontophoretic

delivery of tacrine hydrochloride. Pharm Res 2004;21(12):2293-9.

3. Jaskari T, Vuorio M, Kontturi K, et al. Controlled transdermal iontophoresis by ion-

exchange fiber. J Control Release 2000;67(2-3):179-90.

4. Vuorio M, Murtomaki L, Hirvonen J, et al. Ion-exchange fibers and drugs: a novel device

for the screening of iontophoretic systems. J Control Release 2004;97(3):485-92.

5. Hirsch AC, Upasani RS, Banga AK. Factorial design approach to evaluate interactions

between electrically assisted enhancement and skin stripping for delivery of tacrine. J

Control Release 2005;103(1):113-21.

6. Kankkunen T, Sulkava R, Vuorio M, et al. Transdermal iontophoresis of tacrine in vivo.

Pharm Res 2002;19(5):704-7.

7. Patel N, Jain S, Madan P, et al. Influence of electronic and formulation variables on

transdermal iontophoresis of tacrine hydrochloride. Pharm Dev Technol 2015;20(4):442-

457.

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

8. Chien YW, Banga AK. Iontophoretic (transdermal) delivery of drugs: overview of historical

development. J Pharm Sci 1989;78(5):353-4.

9. Dixit N, Bali V, Baboota S, et al. Iontophoresis - an approach for controlled drug delivery: a

review. Curr Drug Deliv 2007;4(1):1-10.

10. Gannu R, Yamsani VV, Yamsani SK, et al. Optimization of hydrogels for transdermal

delivery of lisinopril by Box-Behnken statistical design. AAPS PharmSciTech

2009;10(2):505-14.

11. Vemulapalli V, Banga AK, Friden PM. Optimization of iontophoretic parameters for the

transdermal delivery of methotrexate. Drug delivery 2008;15(7):437-42.

12. Ghareeb MM, Abdulrasool AA, Hussein AA, et al. Kneading technique for preparation of

binary solid dispersion of meloxicam with poloxamer 188. AAPS PharmSciTech

2009;10(4):1206-15.

13. Shah MK, Madan P, Lin S. Preparation, in vitro evaluation and statistical optimization of

carvedilol-loaded solid lipid nanoparticles for lymphatic absorption via oral administration.

Pharm Dev Technol 2014;19(4):475-85.

14. Jain S, Patel N, Madan P, et al. Quality by design approach for formulation, evaluation and

statistical optimization of diclofenac-loaded ethosomes via transdermal route. Pharm Dev

Technol 2015:(20)4:473-489.

15. Ferreira SL, Bruns RE, da Silva EG, et al. Statistical designs and response surface

techniques for the optimization of chromatographic systems. J Chromatography A

2007;1158(1-2):2-14.

16. Hadgraft J, Guy RH. Transdermal Drug Delivery: Developmental Issues and Research

Initiatives: Marcel Dekker Inc; 1989.

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

17. Rosales E, Sanroman MA, Pazos M. Application of central composite face-centered design

and response surface methodology for the optimization of electro-Fenton decolorization of

Azure B dye. Environ Sci Pollut Res Int 2012;19(5):1738-46.

18. Liu S, Li J, Jin R, et al. Optimization of cataplasm matrix with face-centered design-

response surface method China journal of Chinese materia medica. 2009;34(24):3211-3.

19. Mudry B, Guy RH, Delgado-Charro MB. Electromigration of ions across the skin:

determination and prediction of transport numbers. J Pharm Sci 2006;95(3):561-9.

20. Gangarosa LP, Park NH, Fong BC, et al. Conductivity of drugs used for iontophoresis. J

Pharm Sci 1978;67(10):1439-43.

21. Ferreira SLC, Bruns RE, da Silva EGP, et al. Statistical designs and response surface

techniques for the optimization of chromatographic systems. J Chromatography A

2007;1158(1–2):2-14.

22. Singh B, Chakkal SK, Ahuja N. Formulation and optimization of controlled release

mucoadhesive tablets of atenolol using response surface methodology. AAPS

PharmSciTech 2006;7(1):E3.

23. Bezerra MA, Santelli RE, Oliveira EP, et al. Response surface methodology (RSM) as a tool

for optimization in analytical chemistry. Talanta. 2008;76(5):965-77.

24. Kalia YN, Naik A, Garrison J, et al. Iontophoretic drug delivery. Adv Drug Deliv Rev

2004;56(5):619-58.

25. Luzardo-Alvarez A, Delgado-Charro MB, Blanco-Mendez J. Iontophoretic delivery of

ropinirole hydrochloride: effect of current density and vehicle formulation. Pharm Res

2001;18(12):1714-20.

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

26. Saito Y, Nakagawa M, Yamada M, et al. Estimation of ionic mobility of sodium ion

conductor by scanning electron microscopy observation of sodium metal deposition. J Mater

Sci Lett 1996;15(10):898-901.

27. Tabrizchi M. Thermal ionization ion mobility spectrometry of alkali salts. Anal Chem

2003;75(13):3101-6.

28. Atkins PW, editor. Molecules in motion: ion transport and molecular diffusion, Physical

chemistry. 6th ed. Oxford: Oxford universtiy press; 1978.

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Table 1. Coded and actual levels of electronic and formulation variables used in the face-

centered central composite design.

Independent variable Lower level

(-1)

Middle level

(0)

High level

(+1)

X1: current strength (mA) 0.1 0.2 0.3

X2: buffer molarity (mM) 25 62.5 100

X3: drug concentration (mg/ml) 1.0 10.5 20

Response variable (Y): tacrine permeation flux (μg/cm2/h); Y = f(X1,X2,X3)

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Table 2. Coded and actual levels of electronic and formulation variables as well as the observed

iontophoretic tacrine permeation flux based on the face-centered central composite design (data

represent mean ± SD, n = 3).

Run No.

X1: current

strength

(mA)

X2: buffer

molarity

(mM)

X3: drug

concentration

(mg/ml)

Observed permeation

flux

(μg/cm2/h)

1 0 (0.2) 1 (100) 0 (10.5) 190.79 ± 5.92

2 0 (0.2) 0 (62.5) -1 (1) 75.77 ± 9.95

3 0 (0.2) 0 (62.5) 0 (10.5) 267.38 ± 25.76

4 -1 (0.1) 0 (62.5) 0 (10.5) 156.68 ± 16.87

5 0 (0.2) 0 (62.5) 0 (10.5) 267.38 ± 25.76

6 1 (0.3) 0 (62.5) 0 (10.5) 364.67 ± 20.12

7 1 (0.3) -1 (25) -1 (1) 219.57 ± 30.11

8 0 (0.2) 0 (62.5) 0 (10.5) 278.66 ± 29.74

9 -1 (0.1) -1 (25) 1 (20) 229.89 ± 20.98

10 -1 (0.1) -1 (25) -1 (1) 92.22 ± 10.06

11 0 (0.2) 0 (62.5) 0 (10.5) 270.89 ± 33.22

12 1 (0.3) -1 (25) 1 (20) 477.09 ± 19.65

13 0 (0.2) 0 (62.5) 1 (20) 315.14 ± 12.23

14 1 (0.3) 1 (100) 1 (20) 405.20 ± 23.32

15 0 (0.2) 0 (62.5) 0 (10.5) 270.89 ± 33.22

16 0 (0.2) -1 (25) 0 (10.5) 312.96 ± 24.48

17 -1 (0.1) 1 (100) -1 (1) 47.84 ± 11.90

18 1 (0.3) 1 (100) -1 (1) 129.77 ± 13.65

19 0 (0.2) 0 (62.5) 0 (10.5) 278.66 ± 29.74

20 -1 (0.1) 1 (100) 1 (20) 180.45 ± 23.80

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Table 3. Composition of checkpoint formulations with observed and predicted iontophoretic

tacrine permeation fluxes (data represent mean ± SD, n = 3).

Checkpoint formula composition

(X1:X2:X3)

Permeation flux (μg/cm2/h)

Observed Predicted

(0.1:50:10) 156.37 ± 7.91 189.58

(0.2:85:10) 245.46 ± 14.43 235.77

(0.3:50:10) 366.57 ± 27.71 368.85

(0.2:50:5) 186.67 ± 5.08 196.33

(0.2:50:15) 308.93 ± 13.97 309.51

(0.2:35:10) 303.92 ± 14.67 282.53

(0.1:100:10) 164.54 ± 9.43 152.46

X1: current strength (mA); X2: buffer molarity (mM); X3: drug concentration (mg/ml)

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Figures Legend

Figure 1. Correlation between actual observed and predicted iontophoretic tacrine permeation

flux based on the quadratic equation resulted from face-centered central composite

design.

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Figure 2. Response surface plot representing the effect of drug concentration and buffer molarity

on iontophoretic tacrine permeation flux at different current strengths of 0.1 mA, 0.2 mA

and 0.3 mA, respectively. The bottom surface is at 0.1 mA, followed by at 0.2 mA and

top one at 0.3 mA.

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Figure 3. Correlation between observed and predicted iontophoretic tacrine permeation flux from

the checkpoint formulations for the validation of design of experiments used (data

represent mean ± SD, n = 3).

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016

Figure 4. Correlation between molar conductivity and molar concentration of tacrine or sodium

chloride solutions; the y-intercepts indicate molar conductivities value at infinite dilution

(data represent mean ± SD, n = 3).

JUST A

CCEPTED

Dow

nloa

ded

by [

Shas

hank

Jai

n] a

t 16:

08 2

2 A

pril

2016