Accepted Manuscript Title: Formulation of Extended Release Cefpodoxime proxetil Chitosan-Alginate Beads using Quality by Design Approach Author: Ali Mujtaba Mushir Ali Kanchan Kohli M. Pharma PII: DOI: Reference:
S0141-8130(14)00373-0 http://dx.doi.org/doi:10.1016/j.ijbiomac.2014.05.066 BIOMAC 4391
To appear in:
International Journal of Biological Macromolecules
Received date: Revised date: Accepted date:
4-3-2014 10-5-2014 19-5-2014
Please cite this article as: A. Mujtaba, M. Ali, K. Kohli, M. Pharma, Formulation of Extended Release Cefpodoxime proxetil Chitosan-Alginate Beads using Quality by Design Approach, International Journal of Biological Macromolecules (2014), http://dx.doi.org/10.1016/j.ijbiomac.2014.05.066 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1. Introduction Quality by Design (QbD) is a systematic approach to the pharmaceutical development that begins with predefined objectives, emphasizes product and process understanding
ip t
using statistical tools [1]. It requires an understanding how formulation and process variables influence product quality. Therefore, a very useful component of the QbD is the
cr
understanding of factors and their interaction effects by a desired set of experiments.
us
QbD encompasses the application of tools such as: critical quality attributes (CQAs); design of experiment (DOE); risk assessment; and process analytical technology (PAT)
an
to the development of pharmaceuticals. The International Conference on Harmonization illustrates in different guidelines a series of principles and tools for implementing QbD
M
[2]. One of these tools is the design of experiments (DOE), that allows for understanding
d
how formulation variables can influence the product quality by defining a ‘‘design
te
space’’. The ‘‘design space’’ is the region of the experimental space where a multidimensional combination and interaction of input variables and process parameters
Ac ce p
have been demonstrated to provide assurance of quality [3] and it can be described in terms of mathematical relationships. With the help of DOE, the relationship among different independent variables and the system performance can be found, which can never be obtained using the traditional one variable at a time (OVAT) approach [4]. Response surface methodology (RSM) is one of the most efficient DOE methods, which involves the use of different types of experimental designs to generate polynomial mathematical relationships and mapping of the response over the experimental domain to select the optimal process parameters [5]. Box–Behnken statistical design (BBD) is one type of RSM design that is an independent, rotatable or nearly rotatable, quadratic design
1
Page 1 of 36
having the treatment combinations at the midpoints of the edges of the process space and at the centre [6, 7]. BBD is a more cost-effective technique compared with other techniques such as central composite design, 3-level factorial design and D-optimal
ip t
design, which require fewer experimental runs and less time for optimization of a process.
cr
Recently, the use of natural polymers in the design of drug delivery formulation has
us
received much attention due to their excellent biocompatibility, biodegradability, bioadhesion, stability, safety and their approval for human use by the US FDA are additional
an
advantages [8, 9]. Among them, alginate and chitosan biopolymers are very promising to prepare microspheres/beads and have been widely exploited in pharmaceutical industry
M
for controlled drug release [10]. Alginate is a natural biopolymer which forms a hydrogel
d
in the presence of divalent cations like Ca2+. The inert environment within the
te
biopolymer network of alginates allows for the entrapment of a wide range of bioactive substances, cells and drug molecules, with minor interactions between them [11, 12].
Ac ce p
Chitosan, the N-deacetylated product of the polysaccharide chitin, is used either as a means of coating alginate beads in order to alter the diffusion rate of the encapsulated substances or as an additive for the bulk modification of the beads structure [13]. Multiparticulate dosage forms such as microspheres or beads have several advantages over single-unit dosage forms, such as ease of dispersion, lesser risk of dose dumping, possibility of releasing the drug more uniformly throughout the gastrointestinal tract, and greater flexibility in formulation, Less dependent on gastric emptying, resulting in less inter and intra-subject variability in gastrointestinal transit time, and better reproducible
2
Page 2 of 36
pharmacokinetic behavior [14]. Therefore, a multiparticulate system of chitosan-alginate would be a desired dosage form for extended drug delivery. To maintain antimicrobial activity, frequent administration of conventional formulations
ip t
of the antibiotics with short half-life is necessary. Otherwise, concentration under MIC occurs frequently in the course of anti-infective treatment, which induces antibiotic
cr
resistance. By maintaining a constant plasma drug concentration over MIC for a
us
prolonged period, extended-release dosage forms maximize the therapeutic effect of antibiotics while minimizing antibiotic resistance. Another advantage of extended-release
an
formulation is improved patient compliance. Cefpodoxime proxetil (CFP), an oral, broad spectrum, third generation cephalosporin, is an ester prodrug that de-esterified in vivo and
M
converted to its active metabolite, cefpodoxime. It is commonly used in the treatment of a
d
variety of infections of skin, respiratory tract, urinary tract, and systemic infections and
te
also to treat acute otitis media, pharyngitis, and sinusitis. Absolute bioavailability of CFP in humans is only about 50% and short half life (1.9–2.8 h) permits twice daily
Ac ce p
administration [15]. After 100 mg of the conventional-release dosage form of cefpodoxime is administered, the peak plasma concentration achieved is 1.2 mg/L, and this concentration slowly declines below minimum effective concentration (MEC) within 12 h [16]. In order to increase the effectiveness of CFP, reduce the dosing frequency as a single dose and increase patient compliance, research has been directed to formulate a sustained and extended release dosage form. The present study aimed at development and optimization of multiparticulate systems consisting chitosan-alginate beads containing CFP for extended delivery using design of experiments by employing Box-Behnken statistical design (BBD). The BBD-
3
Page 3 of 36
based optimization was employed to evaluate the effect of three independent process variables i.e., concentration of sodium alginate (X1), chitosan (X2) and calcium chloride (X3) on the properties of chitosan coated alginate beads containing CFP, like drug
ip t
encapsulation efficiency (DEE) (%), particle size (μm) and the time for 80% of the drug to be released (T80%). Another aim was to undertake a physicochemical characterisation
cr
of the optimal formulation in terms of release kinetics, thermal properties, infrared
us
spectroscopy, X-ray diffraction, surface morphology and antimicrobial activity. 2. Materials and methods
an
2.1. Materials
Cefpodoxime proxetil was obtained as a gift sample from Ranbaxy, Gurgaon, India.
M
Chitosan with medium molecular weight and degree of deacetylation about 85% were
d
purchased from Sigma–Aldrich, St. Louis, MO, USA. The medium viscosity sodium
te
alginate isolated from Macrocystis pyrifera, having molecular weight between 75 and 100 kDa, and mannuronic to guluronic acid ratio of 1.5 (60:40), was purchased from CDH
Ac ce p
Labs., India and Calcium chloride were procured from Merck Ltd., India. All other reagents and chemicals used were of analytical reagent grade. 2.2. Preparation of chitosan–alginate CFP beads Chitosan–alginate beads were produced by the ionotropic gelation techniques [17]. CFP (20% w/v) was added to aqueous solutions of sodium alginate and stirred to formed homogenous mixture. This solution was dropped using a 21 gauge blunt ended needle into a second solution, containing calcium chloride (CaCl2) and chitosan, previously dissolved in acetic acid solution (1% v/v) at room temperature under mechanical stirring at 200 rpm. The pH of solution was adjusted to 5 ± 0.1 using 0.1 N NaOH solutions. The
4
Page 4 of 36
flow rate of sodium alginate–CFP was maintained at a pumping rate of 10 ml/h. The beads formed immediately and were left for an hour in the coagulation fluid under stirring. Then beads were filtered, washed and dried at room temperature.
ip t
2.3. Experimental design
Systematic optimization procedures are carried out by selecting an objective function,
cr
finding the most important or contributing factors and investigating the relationship
us
between responses and factors by the so-called response surface methodology [18]. BoxBehnken design was used to statistically optimize the formulation parameters and
an
evaluate the main effects, interaction effects and quadratic effects of the formulation ingredients on the maximum drug encapsulation (DEE), particle size of the beads during
M
manufacturing and the time for 80% of the drug to be released (T80%). A 3-factor, 3-level design was used because it was suitable for exploring quadratic response surfaces and
te
d
constructing second order polynomial models for optimization using Design Expert® (Version 8.0.7.1, Stat-Ease Inc., Minneapolis, Minnesota).
Ac ce p
The non-linear quadratic model generated by the design is given as Yo = bo + b1X1 + b2X2 + b3X3 + b12X1X2 + b13X1X3 + b23X2X3+b11X21 + b22X22 + b33X23 (1)
Where Yo is the dependent variable; b0 is an intercept; b1 to b33 are regression coefficients computed from the observed experimental values of Y; and X1, X2 and X3 are the coded levels of independent variables. The terms X1X2 and Xi2 (i = 1, 2 or 3) represent the interaction and quadratic terms, respectively [19]. The dependent and independent variables selected are shown in table 1 along with their low, medium and high levels, which were selected based on the results from preliminary
5
Page 5 of 36
experiments. For the response surface methodology involving Box–Behnken design, a total of 15 experiments were designed for three factors at three levels of each parameter
2.4. Characterizations of prepared chitosan–alginate CFP beads 2.4.1. Determination of encapsulation efficiency (DEE)
ip t
shown in table 2.
cr
The CFP content in the beads was determined by a digestion method [20]. The CFP-
us
loaded beads (100 mg) were pulverized and incubated in 100 ml of 0.1N HCl (pH 1.2) at room temperature for 24 h. The suspension was then centrifuged at 6000 rpm for 30 min.
an
The supernatant was assayed spectrophotometrically (λmax = 263 nm; Shimadzu Model 1601, Tokyo Japan) for CFP content. Supernatant from the empty beads (without CFP)
d
according to the following equation:
M
was taken as blank. The determinations were made in triplicate and DEE was calculated
(2)
te
DEE (%) = (Actual drug content/Theoretical drug content) × 100 2.4.2. Particle size determination
Ac ce p
Particle size of the beads was measured by laser light scattering technique (Mastersizer 2000, Malvern, UK). The sizes of the completely dried beads of different formulations were measured. The laser obscuration range was maintained 0.00%. Each batch was analyzed in triplicate, but the average values were considered in data analysis. 2.4.3. In vitro release studies
The release profiles of CFP from chitosan–alginate beads were examined in simulated gastric fluid (SGF pH 1.2) and simulated intestinal fluid (SIF pH 6.8) as a dissolution medium. The release of CFP from chitosan–alginate beads (equivalent to 100 mg of drug) was investigated in 900 ml of the dissolution medium, thermostated at 37oC with an
6
Page 6 of 36
agitation speed of 75 rpm using the USP dissolution assembly Type-II (VEEGO dissolution apparatus VDA 8DR USP, Mumbai, India). After 4 h the dissolution medium pH was changed from 1.2 to 6.8 by adding 50 ml of concentrated phosphate buffer with
ip t
pH 12 to achieve the desired intestinal fluid pH 6.8 and was then run for the specified time. At scheduled time intervals agitation was stopped, the samples (2 ml) were
cr
withdrawn and replaced with fresh medium. The samples were diluted, filtered and the
us
drug content determined spectrophotometrically at 263 nm. The corresponding empty chitosan–alginate beads (without CFP) were taken as reference. Each experiment was
an
repeated at least three times.
2.4.4. Optimization data analysis and model-validation
M
ANOVA provision available in the software was used to establish the statistical
d
validation of the polynomial equations generated by Design Expert®. A total of 15 runs
te
with triplicate center points were generated by Box-Behnken design. Suitable models for mixture designs consisting of three components include linear, quadratic and special
Ac ce p
cubic models. The best fitting mathematical model was selected based on the comparisons of several statistical parameters including the coefficient of variation (C.V), the multiple correlation coefficient (R2), adjusted multiple correlation coefficient (adjusted R2; and the predicted residual sum of square (PRESS), proved by DesignExpert® software. Among them, PRESS indicates how well the model fits the data, and for the chosen model it should be small relative to the other models under consideration [21]. Three dimensional response surface plots were provided by the Design Expert® software, where by intensive grid search performed over the whole experimental region, three optimum checkpoint formulations were selected to validate the chosen experimental
7
Page 7 of 36
domain and polynomial equations. The optimized checkpoint formulations were prepared and evaluated for various response properties. The resultant experimental values of the responses were quantitatively compared with that of the predicted values to calculate the
ip t
percentage prediction error. Also, linear regression plots between actual and predicted
2.5. Characterisation of the optimised formulation
us
2.5.1. Differential scanning calorimetry (DSC) analysis
cr
values of the responses were produced using MS-Excel 2007.
The physical state of the drug in the samples was determined by DSC (Perkin Elmer
an
equipped with software Pyris 6.0). The instrument was calibrated using indium standards. Samples containing 3mg of the drug/placebo/formulation were placed in aluminium pans
M
and heated from 50 oC to 200 oC at a heating rate of 10 oC/min under constant purging of
d
dry nitrogen at 20 ml/min. An empty pan, sealed in the same way as the sample, was used
te
as a reference.
2.5.2. Fourier transform-infra red (FTIR) spectroscopic analysis
Ac ce p
FTIR spectra were obtained using a FT-IR-8300 spectrophotometer (Shimadzu, Japan). One to 2mg of drug/placebo/formulation were weighed and mixed perfectly with potassium bromide (0.3–0.4 g) to a uniform mixture. A small quantity of the powder was compressed into a thin semitransparent disc under a hydraulic press at 10,000 psi. Each KBr dics was scanned at 4 mm/s at a resolution of 2 cm over a wavenumber region of 400–4000 cm-1 using IR software (ver. 1.10). The characteristic peaks were recorded for different samples. 2.5.3. X-ray diffraction study
8
Page 8 of 36
Powder X-ray diffraction (PXRD) patterns of CFP, placebo beads and drug-loaded beads were recorded by using a Philips PW1729 X-ray diffractometer (Philips PW 1729 X-ray diffractometer, Netherlands). Samples were irradiated with monochromatized Cu Kα
ip t
radiation (1.542 Å) and analyzed at 2θ between 3° and 60° at a scanning speed of 15o/min. The voltage and current used were 40 kV and 40 mA, respectively. Before
cr
analysis, the placebo and optimized beads were crushed separately to obtain fine powder
us
suitable for the test. 2.5.4. Scanning electron microscopy (SEM)
an
The surface topography of the optimized beads was examined using SEM techniques (EVO LS 10 Zeiss, Carl Zeiss Inc., Germany). Beads were sputtered with gold to make
M
them conducting and placed on a copper stub. They sample were viewed operating at an
d
accelerating voltage of 20 kV under high vacuum and images were collected in secondary
te
electron mode. 2.6. Antimicrobial efficacy study
Ac ce p
For the purpose of this study, the antimicrobial activity of Optimized beads and drug alone was evaluated. Each experiment was carried out in triplicate. For the beads, samples collected from the in vitro release study of optimized beads at different time intervals (0.5, 1, 2, 4, 6, 8, 10, 12, 16, 20 and 24 h) were tested against S. aureus (ATCC29213), E. coli (ATCC25922). CFP (pure drug) at different concentrations in phosphate buffered saline (pH 6.8) (1–250 μg/mL) was also tested against the same strains. Muller–Hinton agar media was transferred to sterilized petridishes and when the temperature was around 40 °C, 0.2 ml of an overnight culture of strains mentioned were
9
Page 9 of 36
added to the petridishes. The culture was evenly distributed and the medium was allowed to solidify. Wells equidistant from each other were made in the solidified medium using a well borer, which was sterilized in the flame. All microbiological studies were performed
ip t
in an aseptic area in the laminar flow hood. After incubation the diameter (mm) of zone of growth inhibition (ZOI) surrounding each agar well was measured with the zone
cr
finder.
us
3. Results and discussion 3.1. Formation of chitosan–alginate beads
an
The preparation of chitosan–alginate beads for CFP was successfully prepared by ionotropic gelation techniques. The developed microbeads consist of CFP entrapped
M
within sodium alginate and coated with chitosan as an outer layer. The ionotropic
d
gelation process did not include emulsification step and stage of organic solvents, thereby
te
minimizing inactivation of encapsulated drugs. This is an effective and facile technique that enables the formation of spherical beads with regular shape, size and smooth surface
Ac ce p
as well as the preparation of ideal release retarding membrane. The principle for the chitosan–alginate beads formation is based on the electrostatic attraction between the cationic amino groups of chitosan (the pKa value is about 6.5) and the anionic carboxyl groups of the alginate is the main interaction leading to the formation of the beads. It is stronger than most secondary binding interactions [22]. 3.2. Experimental design According to QbD principles, DOE was used for chitosan–alginate beads formulation optimization, so that to ensure a predefined quality of the product. The components used for the beads production (alginate, chitosan, and CaCl2) was chosen as the independent
10
Page 10 of 36
variables since they were considered critical in determining the performance of the final product; the drug encapsulation efficiency (DEE%), particle size and the time for 80% of the drug to be released (T80%) were selected as the most important responses to be
ip t
maximized to improve the product quality. The experimental domain of each of the selected independent variables was set on the basis of a preliminary screening.
cr
In particular, the alginate concentration range was established between 4 and 6% w/v
us
because polymer amounts lower than 2% gave rise to sticky microparticles of irregular shape, While soft, weak and non-spherical microparticles were obtained at 3% alginate
an
concentration due to poor molecular packing and cross-linking, while solutions containing alginate amounts greater than 6% were excessively viscous and difficult to be
M
regularly dropped with the syringe. In case of chitosan, 0.5% w/v was chosen as the
d
lowest value of this polymer, and 2% w/v as the highest value. As for the CaCl2
te
concentration range, 10% w/v was fixed as the upper value, in order to avoid possible negative effects due to an excess of free Ca2+ ions [23], while 5% w/v was chosen as the
Ac ce p
lowest value, since lesser amounts did not allow obtainment of beads with an adequate consistency. Thus, the chosen independent variables ranged as follows: X1 = % sodium alginate: 4–6% w/v; X2 = % chitosan: 0.5–2% w/v; X3 = % calcium chloride: 5–10% w/v.
For the response surface methodology involving Box-Behnken design, a total of 15 experiments (BB1–BB15) were performed for three factors at three levels each. This number is equal to the mid-point of each edge and the three replicated center points of the cube. The experiment runs with independent variables and the observed responses for the 15 formulations are shown in table 2.
11
Page 11 of 36
3.3. Fitting data to model All the responses observed for 15 formulations prepared were simultaneously fitted to different models using Design-Expert®. The fit summary for each response was shown in
ip t
table 3. In order to evaluate the effect of formulation ingredients on the each of responses Y1–Y3, the causal factor and response variables were related using polynomial equation
cr
with statistical analysis. The comparative values of multiple correlation coefficient (R2),
us
adjusted multiple correlation coefficient (adjusted R2), S.D., %C.V. and the predicted residual sum of squares (PRESS) are presented in table 3. Responses Y1, Y2 and Y3 were
an
found to follow quadratic and linear model, respectively because its PRESS was smallest. Only statistically significant (p < 0.05) coefficients are included in the equations.
M
Predicted residual sum of squares (PRESS) is a measure of the fit of the model to the
d
points in the design. The smaller the PRESS statistic is, the better the model fits to the
te
data points [24]. The model showed a statistically insignificant lack of fit. The adequacy of the model was also confirmed with residual plot tests of regression models. Analysis
Ac ce p
of variance (ANOVA) was applied to estimate the significance of the model at the 5% significance level.
3.4. Contour plots and response surface analysis by polynomial Equation Two-dimensional contour plots and three dimensional response surface plots, as presented in fig. 1, are very useful to see interaction effects of the factors on the responses. These types of plots show effects of two factors on the response at a time. In all the presented figures, the third factor was kept at level zero. 3.4.1. Effect on T80%: response 1 (Y1) The following polynomial equation was generated for T80% of CFP loaded microbeads.
12
Page 12 of 36
Y1 (T80%) = 18.32 + 3.03 X1 + 1.30 X2 + 0.97 X3 + 0.20X1X3 + 0.20 X2X3 -0.46 X12 -1.61 X22 + 0.34 X32
(3)
whereT80% is the time for 80% of the drug to be released, X1, X2 and X3 are the
ip t
concentration of sodium alginate, chitosan and CaCl2 respectively. The Model F-value of 154.73 implies the model is significant. The "Lack of Fit F-value" of 0.20 implies the
cr
Lack of Fit is not significant (p
S0141-8130(14)00373-0 http://dx.doi.org/doi:10.1016/j.ijbiomac.2014.05.066 BIOMAC 4391
To appear in:
International Journal of Biological Macromolecules
Received date: Revised date: Accepted date:
4-3-2014 10-5-2014 19-5-2014
Please cite this article as: A. Mujtaba, M. Ali, K. Kohli, M. Pharma, Formulation of Extended Release Cefpodoxime proxetil Chitosan-Alginate Beads using Quality by Design Approach, International Journal of Biological Macromolecules (2014), http://dx.doi.org/10.1016/j.ijbiomac.2014.05.066 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1. Introduction Quality by Design (QbD) is a systematic approach to the pharmaceutical development that begins with predefined objectives, emphasizes product and process understanding
ip t
using statistical tools [1]. It requires an understanding how formulation and process variables influence product quality. Therefore, a very useful component of the QbD is the
cr
understanding of factors and their interaction effects by a desired set of experiments.
us
QbD encompasses the application of tools such as: critical quality attributes (CQAs); design of experiment (DOE); risk assessment; and process analytical technology (PAT)
an
to the development of pharmaceuticals. The International Conference on Harmonization illustrates in different guidelines a series of principles and tools for implementing QbD
M
[2]. One of these tools is the design of experiments (DOE), that allows for understanding
d
how formulation variables can influence the product quality by defining a ‘‘design
te
space’’. The ‘‘design space’’ is the region of the experimental space where a multidimensional combination and interaction of input variables and process parameters
Ac ce p
have been demonstrated to provide assurance of quality [3] and it can be described in terms of mathematical relationships. With the help of DOE, the relationship among different independent variables and the system performance can be found, which can never be obtained using the traditional one variable at a time (OVAT) approach [4]. Response surface methodology (RSM) is one of the most efficient DOE methods, which involves the use of different types of experimental designs to generate polynomial mathematical relationships and mapping of the response over the experimental domain to select the optimal process parameters [5]. Box–Behnken statistical design (BBD) is one type of RSM design that is an independent, rotatable or nearly rotatable, quadratic design
1
Page 1 of 36
having the treatment combinations at the midpoints of the edges of the process space and at the centre [6, 7]. BBD is a more cost-effective technique compared with other techniques such as central composite design, 3-level factorial design and D-optimal
ip t
design, which require fewer experimental runs and less time for optimization of a process.
cr
Recently, the use of natural polymers in the design of drug delivery formulation has
us
received much attention due to their excellent biocompatibility, biodegradability, bioadhesion, stability, safety and their approval for human use by the US FDA are additional
an
advantages [8, 9]. Among them, alginate and chitosan biopolymers are very promising to prepare microspheres/beads and have been widely exploited in pharmaceutical industry
M
for controlled drug release [10]. Alginate is a natural biopolymer which forms a hydrogel
d
in the presence of divalent cations like Ca2+. The inert environment within the
te
biopolymer network of alginates allows for the entrapment of a wide range of bioactive substances, cells and drug molecules, with minor interactions between them [11, 12].
Ac ce p
Chitosan, the N-deacetylated product of the polysaccharide chitin, is used either as a means of coating alginate beads in order to alter the diffusion rate of the encapsulated substances or as an additive for the bulk modification of the beads structure [13]. Multiparticulate dosage forms such as microspheres or beads have several advantages over single-unit dosage forms, such as ease of dispersion, lesser risk of dose dumping, possibility of releasing the drug more uniformly throughout the gastrointestinal tract, and greater flexibility in formulation, Less dependent on gastric emptying, resulting in less inter and intra-subject variability in gastrointestinal transit time, and better reproducible
2
Page 2 of 36
pharmacokinetic behavior [14]. Therefore, a multiparticulate system of chitosan-alginate would be a desired dosage form for extended drug delivery. To maintain antimicrobial activity, frequent administration of conventional formulations
ip t
of the antibiotics with short half-life is necessary. Otherwise, concentration under MIC occurs frequently in the course of anti-infective treatment, which induces antibiotic
cr
resistance. By maintaining a constant plasma drug concentration over MIC for a
us
prolonged period, extended-release dosage forms maximize the therapeutic effect of antibiotics while minimizing antibiotic resistance. Another advantage of extended-release
an
formulation is improved patient compliance. Cefpodoxime proxetil (CFP), an oral, broad spectrum, third generation cephalosporin, is an ester prodrug that de-esterified in vivo and
M
converted to its active metabolite, cefpodoxime. It is commonly used in the treatment of a
d
variety of infections of skin, respiratory tract, urinary tract, and systemic infections and
te
also to treat acute otitis media, pharyngitis, and sinusitis. Absolute bioavailability of CFP in humans is only about 50% and short half life (1.9–2.8 h) permits twice daily
Ac ce p
administration [15]. After 100 mg of the conventional-release dosage form of cefpodoxime is administered, the peak plasma concentration achieved is 1.2 mg/L, and this concentration slowly declines below minimum effective concentration (MEC) within 12 h [16]. In order to increase the effectiveness of CFP, reduce the dosing frequency as a single dose and increase patient compliance, research has been directed to formulate a sustained and extended release dosage form. The present study aimed at development and optimization of multiparticulate systems consisting chitosan-alginate beads containing CFP for extended delivery using design of experiments by employing Box-Behnken statistical design (BBD). The BBD-
3
Page 3 of 36
based optimization was employed to evaluate the effect of three independent process variables i.e., concentration of sodium alginate (X1), chitosan (X2) and calcium chloride (X3) on the properties of chitosan coated alginate beads containing CFP, like drug
ip t
encapsulation efficiency (DEE) (%), particle size (μm) and the time for 80% of the drug to be released (T80%). Another aim was to undertake a physicochemical characterisation
cr
of the optimal formulation in terms of release kinetics, thermal properties, infrared
us
spectroscopy, X-ray diffraction, surface morphology and antimicrobial activity. 2. Materials and methods
an
2.1. Materials
Cefpodoxime proxetil was obtained as a gift sample from Ranbaxy, Gurgaon, India.
M
Chitosan with medium molecular weight and degree of deacetylation about 85% were
d
purchased from Sigma–Aldrich, St. Louis, MO, USA. The medium viscosity sodium
te
alginate isolated from Macrocystis pyrifera, having molecular weight between 75 and 100 kDa, and mannuronic to guluronic acid ratio of 1.5 (60:40), was purchased from CDH
Ac ce p
Labs., India and Calcium chloride were procured from Merck Ltd., India. All other reagents and chemicals used were of analytical reagent grade. 2.2. Preparation of chitosan–alginate CFP beads Chitosan–alginate beads were produced by the ionotropic gelation techniques [17]. CFP (20% w/v) was added to aqueous solutions of sodium alginate and stirred to formed homogenous mixture. This solution was dropped using a 21 gauge blunt ended needle into a second solution, containing calcium chloride (CaCl2) and chitosan, previously dissolved in acetic acid solution (1% v/v) at room temperature under mechanical stirring at 200 rpm. The pH of solution was adjusted to 5 ± 0.1 using 0.1 N NaOH solutions. The
4
Page 4 of 36
flow rate of sodium alginate–CFP was maintained at a pumping rate of 10 ml/h. The beads formed immediately and were left for an hour in the coagulation fluid under stirring. Then beads were filtered, washed and dried at room temperature.
ip t
2.3. Experimental design
Systematic optimization procedures are carried out by selecting an objective function,
cr
finding the most important or contributing factors and investigating the relationship
us
between responses and factors by the so-called response surface methodology [18]. BoxBehnken design was used to statistically optimize the formulation parameters and
an
evaluate the main effects, interaction effects and quadratic effects of the formulation ingredients on the maximum drug encapsulation (DEE), particle size of the beads during
M
manufacturing and the time for 80% of the drug to be released (T80%). A 3-factor, 3-level design was used because it was suitable for exploring quadratic response surfaces and
te
d
constructing second order polynomial models for optimization using Design Expert® (Version 8.0.7.1, Stat-Ease Inc., Minneapolis, Minnesota).
Ac ce p
The non-linear quadratic model generated by the design is given as Yo = bo + b1X1 + b2X2 + b3X3 + b12X1X2 + b13X1X3 + b23X2X3+b11X21 + b22X22 + b33X23 (1)
Where Yo is the dependent variable; b0 is an intercept; b1 to b33 are regression coefficients computed from the observed experimental values of Y; and X1, X2 and X3 are the coded levels of independent variables. The terms X1X2 and Xi2 (i = 1, 2 or 3) represent the interaction and quadratic terms, respectively [19]. The dependent and independent variables selected are shown in table 1 along with their low, medium and high levels, which were selected based on the results from preliminary
5
Page 5 of 36
experiments. For the response surface methodology involving Box–Behnken design, a total of 15 experiments were designed for three factors at three levels of each parameter
2.4. Characterizations of prepared chitosan–alginate CFP beads 2.4.1. Determination of encapsulation efficiency (DEE)
ip t
shown in table 2.
cr
The CFP content in the beads was determined by a digestion method [20]. The CFP-
us
loaded beads (100 mg) were pulverized and incubated in 100 ml of 0.1N HCl (pH 1.2) at room temperature for 24 h. The suspension was then centrifuged at 6000 rpm for 30 min.
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The supernatant was assayed spectrophotometrically (λmax = 263 nm; Shimadzu Model 1601, Tokyo Japan) for CFP content. Supernatant from the empty beads (without CFP)
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according to the following equation:
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was taken as blank. The determinations were made in triplicate and DEE was calculated
(2)
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DEE (%) = (Actual drug content/Theoretical drug content) × 100 2.4.2. Particle size determination
Ac ce p
Particle size of the beads was measured by laser light scattering technique (Mastersizer 2000, Malvern, UK). The sizes of the completely dried beads of different formulations were measured. The laser obscuration range was maintained 0.00%. Each batch was analyzed in triplicate, but the average values were considered in data analysis. 2.4.3. In vitro release studies
The release profiles of CFP from chitosan–alginate beads were examined in simulated gastric fluid (SGF pH 1.2) and simulated intestinal fluid (SIF pH 6.8) as a dissolution medium. The release of CFP from chitosan–alginate beads (equivalent to 100 mg of drug) was investigated in 900 ml of the dissolution medium, thermostated at 37oC with an
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agitation speed of 75 rpm using the USP dissolution assembly Type-II (VEEGO dissolution apparatus VDA 8DR USP, Mumbai, India). After 4 h the dissolution medium pH was changed from 1.2 to 6.8 by adding 50 ml of concentrated phosphate buffer with
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pH 12 to achieve the desired intestinal fluid pH 6.8 and was then run for the specified time. At scheduled time intervals agitation was stopped, the samples (2 ml) were
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withdrawn and replaced with fresh medium. The samples were diluted, filtered and the
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drug content determined spectrophotometrically at 263 nm. The corresponding empty chitosan–alginate beads (without CFP) were taken as reference. Each experiment was
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repeated at least three times.
2.4.4. Optimization data analysis and model-validation
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ANOVA provision available in the software was used to establish the statistical
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validation of the polynomial equations generated by Design Expert®. A total of 15 runs
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with triplicate center points were generated by Box-Behnken design. Suitable models for mixture designs consisting of three components include linear, quadratic and special
Ac ce p
cubic models. The best fitting mathematical model was selected based on the comparisons of several statistical parameters including the coefficient of variation (C.V), the multiple correlation coefficient (R2), adjusted multiple correlation coefficient (adjusted R2; and the predicted residual sum of square (PRESS), proved by DesignExpert® software. Among them, PRESS indicates how well the model fits the data, and for the chosen model it should be small relative to the other models under consideration [21]. Three dimensional response surface plots were provided by the Design Expert® software, where by intensive grid search performed over the whole experimental region, three optimum checkpoint formulations were selected to validate the chosen experimental
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domain and polynomial equations. The optimized checkpoint formulations were prepared and evaluated for various response properties. The resultant experimental values of the responses were quantitatively compared with that of the predicted values to calculate the
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percentage prediction error. Also, linear regression plots between actual and predicted
2.5. Characterisation of the optimised formulation
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2.5.1. Differential scanning calorimetry (DSC) analysis
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values of the responses were produced using MS-Excel 2007.
The physical state of the drug in the samples was determined by DSC (Perkin Elmer
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equipped with software Pyris 6.0). The instrument was calibrated using indium standards. Samples containing 3mg of the drug/placebo/formulation were placed in aluminium pans
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and heated from 50 oC to 200 oC at a heating rate of 10 oC/min under constant purging of
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dry nitrogen at 20 ml/min. An empty pan, sealed in the same way as the sample, was used
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as a reference.
2.5.2. Fourier transform-infra red (FTIR) spectroscopic analysis
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FTIR spectra were obtained using a FT-IR-8300 spectrophotometer (Shimadzu, Japan). One to 2mg of drug/placebo/formulation were weighed and mixed perfectly with potassium bromide (0.3–0.4 g) to a uniform mixture. A small quantity of the powder was compressed into a thin semitransparent disc under a hydraulic press at 10,000 psi. Each KBr dics was scanned at 4 mm/s at a resolution of 2 cm over a wavenumber region of 400–4000 cm-1 using IR software (ver. 1.10). The characteristic peaks were recorded for different samples. 2.5.3. X-ray diffraction study
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Powder X-ray diffraction (PXRD) patterns of CFP, placebo beads and drug-loaded beads were recorded by using a Philips PW1729 X-ray diffractometer (Philips PW 1729 X-ray diffractometer, Netherlands). Samples were irradiated with monochromatized Cu Kα
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radiation (1.542 Å) and analyzed at 2θ between 3° and 60° at a scanning speed of 15o/min. The voltage and current used were 40 kV and 40 mA, respectively. Before
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analysis, the placebo and optimized beads were crushed separately to obtain fine powder
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suitable for the test. 2.5.4. Scanning electron microscopy (SEM)
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The surface topography of the optimized beads was examined using SEM techniques (EVO LS 10 Zeiss, Carl Zeiss Inc., Germany). Beads were sputtered with gold to make
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them conducting and placed on a copper stub. They sample were viewed operating at an
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accelerating voltage of 20 kV under high vacuum and images were collected in secondary
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electron mode. 2.6. Antimicrobial efficacy study
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For the purpose of this study, the antimicrobial activity of Optimized beads and drug alone was evaluated. Each experiment was carried out in triplicate. For the beads, samples collected from the in vitro release study of optimized beads at different time intervals (0.5, 1, 2, 4, 6, 8, 10, 12, 16, 20 and 24 h) were tested against S. aureus (ATCC29213), E. coli (ATCC25922). CFP (pure drug) at different concentrations in phosphate buffered saline (pH 6.8) (1–250 μg/mL) was also tested against the same strains. Muller–Hinton agar media was transferred to sterilized petridishes and when the temperature was around 40 °C, 0.2 ml of an overnight culture of strains mentioned were
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added to the petridishes. The culture was evenly distributed and the medium was allowed to solidify. Wells equidistant from each other were made in the solidified medium using a well borer, which was sterilized in the flame. All microbiological studies were performed
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in an aseptic area in the laminar flow hood. After incubation the diameter (mm) of zone of growth inhibition (ZOI) surrounding each agar well was measured with the zone
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finder.
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3. Results and discussion 3.1. Formation of chitosan–alginate beads
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The preparation of chitosan–alginate beads for CFP was successfully prepared by ionotropic gelation techniques. The developed microbeads consist of CFP entrapped
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within sodium alginate and coated with chitosan as an outer layer. The ionotropic
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gelation process did not include emulsification step and stage of organic solvents, thereby
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minimizing inactivation of encapsulated drugs. This is an effective and facile technique that enables the formation of spherical beads with regular shape, size and smooth surface
Ac ce p
as well as the preparation of ideal release retarding membrane. The principle for the chitosan–alginate beads formation is based on the electrostatic attraction between the cationic amino groups of chitosan (the pKa value is about 6.5) and the anionic carboxyl groups of the alginate is the main interaction leading to the formation of the beads. It is stronger than most secondary binding interactions [22]. 3.2. Experimental design According to QbD principles, DOE was used for chitosan–alginate beads formulation optimization, so that to ensure a predefined quality of the product. The components used for the beads production (alginate, chitosan, and CaCl2) was chosen as the independent
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variables since they were considered critical in determining the performance of the final product; the drug encapsulation efficiency (DEE%), particle size and the time for 80% of the drug to be released (T80%) were selected as the most important responses to be
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maximized to improve the product quality. The experimental domain of each of the selected independent variables was set on the basis of a preliminary screening.
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In particular, the alginate concentration range was established between 4 and 6% w/v
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because polymer amounts lower than 2% gave rise to sticky microparticles of irregular shape, While soft, weak and non-spherical microparticles were obtained at 3% alginate
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concentration due to poor molecular packing and cross-linking, while solutions containing alginate amounts greater than 6% were excessively viscous and difficult to be
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regularly dropped with the syringe. In case of chitosan, 0.5% w/v was chosen as the
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lowest value of this polymer, and 2% w/v as the highest value. As for the CaCl2
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concentration range, 10% w/v was fixed as the upper value, in order to avoid possible negative effects due to an excess of free Ca2+ ions [23], while 5% w/v was chosen as the
Ac ce p
lowest value, since lesser amounts did not allow obtainment of beads with an adequate consistency. Thus, the chosen independent variables ranged as follows: X1 = % sodium alginate: 4–6% w/v; X2 = % chitosan: 0.5–2% w/v; X3 = % calcium chloride: 5–10% w/v.
For the response surface methodology involving Box-Behnken design, a total of 15 experiments (BB1–BB15) were performed for three factors at three levels each. This number is equal to the mid-point of each edge and the three replicated center points of the cube. The experiment runs with independent variables and the observed responses for the 15 formulations are shown in table 2.
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3.3. Fitting data to model All the responses observed for 15 formulations prepared were simultaneously fitted to different models using Design-Expert®. The fit summary for each response was shown in
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table 3. In order to evaluate the effect of formulation ingredients on the each of responses Y1–Y3, the causal factor and response variables were related using polynomial equation
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with statistical analysis. The comparative values of multiple correlation coefficient (R2),
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adjusted multiple correlation coefficient (adjusted R2), S.D., %C.V. and the predicted residual sum of squares (PRESS) are presented in table 3. Responses Y1, Y2 and Y3 were
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found to follow quadratic and linear model, respectively because its PRESS was smallest. Only statistically significant (p < 0.05) coefficients are included in the equations.
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Predicted residual sum of squares (PRESS) is a measure of the fit of the model to the
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points in the design. The smaller the PRESS statistic is, the better the model fits to the
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data points [24]. The model showed a statistically insignificant lack of fit. The adequacy of the model was also confirmed with residual plot tests of regression models. Analysis
Ac ce p
of variance (ANOVA) was applied to estimate the significance of the model at the 5% significance level.
3.4. Contour plots and response surface analysis by polynomial Equation Two-dimensional contour plots and three dimensional response surface plots, as presented in fig. 1, are very useful to see interaction effects of the factors on the responses. These types of plots show effects of two factors on the response at a time. In all the presented figures, the third factor was kept at level zero. 3.4.1. Effect on T80%: response 1 (Y1) The following polynomial equation was generated for T80% of CFP loaded microbeads.
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Y1 (T80%) = 18.32 + 3.03 X1 + 1.30 X2 + 0.97 X3 + 0.20X1X3 + 0.20 X2X3 -0.46 X12 -1.61 X22 + 0.34 X32
(3)
whereT80% is the time for 80% of the drug to be released, X1, X2 and X3 are the
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concentration of sodium alginate, chitosan and CaCl2 respectively. The Model F-value of 154.73 implies the model is significant. The "Lack of Fit F-value" of 0.20 implies the
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Lack of Fit is not significant (p
