Biowaiver Approach for Biopharmaceutics Classification System Class 3 Compound Metformin Hydrochloride Using In Silico Modeling JOHN R. CRISON,1 PETER TIMMINS,2 ANTHER KEUNG,3 VIJAY V. UPRETI,3 DAVID W. BOULTON,3 BARRY J. SCHEER4 1
Drug Product Science and Technology, Bristol–Myers Squibb, New Brunswick, New Jersey 08901
2
Drug Product Science and Technology, Bristol–Myers Squibb, Moreton, Merseyside CH46 1QW, United Kingdom
3
Discovery Medicine and Clinical Pharmacology, Bristol–Myers Squibb, Princeton, New Jersey 08540
4
Analytical and Bioanalytical Development, Bristol–Myers Squibb, New Brunswick, New Jersey 08901
Received 30 June 2011; revised 21 December 2011; accepted 4 January 2012 Published online 14 February 2012 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/jps.23063 ABSTRACT: The dependency of metformin in vivo disposition on the rate and extent of dissolution was studied. The analysis includes the use of fundamental principles of drug input, permeability, and intestinal transit time within the framework of a compartmental absorption transit model to predict key pharmacokinetic (PK) parameters and then compare the results to clinical data. The simulations show that the maximum plasma concentration (Cmax ) and area under the curve (AUC) are not significantly affected when 100% of drug is released within 2 h of oral dosing, which was confirmed with corresponding human PK data. Furthermore, in vitro dissolution profiles measured in aqueous buffers at pH values of 1.2, 4.5, and 6.8 were slower than in vivo release profiles generated by deconvolution of metformin products that were bioequivalent. On the basis of this work, formulations of metformin that release 100% in vitro in a time period equal to or less than two hours are indicated to be bioequivalent. The use of modeling offers a mechanistic-based approach for demonstrating acceptable bioperformance for metformin formulations without having to resort to in vivo bioequivalence studies and may be more robust than statistical comparison of in vitro release profiles. This work further provides a strategy for considering Biopharmaceutics Classification System (BCS) Class 3 compounds to be included under biowaiver guidelines as for BCS Class 1 compounds. © 2012 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:1773–1782, 2012 Keywords: oral absorption; Biopharmaceutics Classification System (BCS); mathematical model; dissolution; permeability
INTRODUCTION Metformin is a biguanide with antihyperglycemic properties that is widely used in the treatment of type II diabetes, being recommended as first-line therapy in all newly diagnosed patients regardless of age.1 It is available as its hydrochloride salt in both immediate and modified release dosage forms. It is a relatively low-molecular-weight (MW) hydrophilic base (MW = 129.17 Da, pKa 11.5), has a logD of −3.37 at pH 4, and an aqueous solubility greater than 100 mg/mL throughout the physiological pH range.2 Correspondence to: John R. Crison (Telephone: +732-227-5890; Fax: +732-227-3986; E-mail:
[email protected]) Journal of Pharmaceutical Sciences, Vol. 101, 1773–1782 (2012) © 2012 Wiley Periodicals, Inc. and the American Pharmacists Association
As such it might be expected to have limited, passive diffusion through cell membranes and, based on Caco-2 studies, the proposed mechanism of absorption is passive paracellular, that is, 91%–95% paracellular and 5%–9% transcellular.3,4 The major site of absorption for metformin is the proximal small intestine and the primary route of elimination is via the kidneys.5 Studies have suggested that metformin is a substrate for organic cation transporters (OCTs) in enterocytes, small intestine, and hepatocytes, although no specific transporter has been identified.6 The relevance of these transporters to metformin absorption is unclear as volunteers with genetic variation in expression of OCT did not show marked differences in oral absorption of metformin.6,7 The permeability of metformin in rat duodenum
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decreased by 60% when perfused with a 200 :g/mL versus 50 :g/mL solution of metformin based on single-pass in situ perfusion experiments.8 Metformin is a Biopharmaceutics Classification System Class 3 (BCS 3) compound (high solubility, poor permeability).9,10 During the development of fixed dose combination (FDC) products containing metformin for global regulatory submission, there was a need to assure equivalent bioperformance of metformin from the fixed combination product to metformin marketed in different territories. Drug release studies on metformin immediate-release tablets sourced from different markets showed diverse drug release properties. During this investigation, one of the FDC products had dissimilar in vitro dissolution profiles to the reference product, yet was demonstrated as bioequivalent in a subsequent clinical study. It was desired not to undertake multiple bioequivalence studies for a well established, widely studied drug-like metformin, but to investigate whether a biowaiver approach might be feasible. A biowaiver approach allows, on the basis of comparative in vitro release studies, the approval of changes to a drug product that are predicted not to affect in vivo performance, minimizing review burden on regulators and avoiding unnecessary clinical studies, expense, and delay for the sponsor. Several groups have argued that BCS 3 compounds should be eligible for biowaiver status in a similar fashion to BCS 1 compounds because the controlling factors in the absorption process from the drug product are not the drug substance solubility.9,11–16 Because the absorption profile of BCS 3 compounds is also affected by the gastrointestinal (GI) transit time, release times must be within the boundaries of the absorption window in the intestine for two products to be bioequivalent, and any biowaiver approach accommodating BCS 3 drugs has to consider this. To date, however, biowaivers are only broadly recognized as applicable to BCS 1, highly soluble, highly permeable, compounds, although European Medicines Agency guidelines allow application of biowaiver in the case of BCS 3 compounds under very specific conditions of excipient composition of the compared materials and where dissolution is very rapid, not less than 85% dissolved in 15 min across the physiological pH range.17 This present work represents a thorough approach using validated computer simulations from a mechanistically based in silico absorption model to predict performance for use as a biowaiver for this BCS 3 compound by modeling within the range of gastric transit times expected in human subjects in order to show the broad range of release rates that are expected to have no impact on AUC and Cmax and therefore result in bioequivalence. The model used accounts for JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 101, NO. 5, MAY 2012
the limited permeability through the intestinal membrane and the change in that profile throughout the GI tract and has shown to be predictive based on clinical data for a wide range of in vitro release times. This more detailed biopharmaceutics-based approach to a biowaiver proposal avoids the need for very rapid dissolution times and challenges of current similarity factor assessments for in vitro dissolution profiles, which may show nonsimilarity for bioequivalent drug products.
MATERIALS AND METHODS Software Commercially available software, GastroPlusTM , version 7.0 (Simulations Plus, Inc., Lancaster, California) was used to model the absorption, distribution, and elimination of metformin in humans. WinNonlin version 5.2.1 (Pharsight Corporation, Cary, North Carolina) was used to perform the statistical analysis for establishing bioequivalence between the model simulations and clinical data and between study groups.
In Vitro Drug Release Studies Dissolution was determined using United States Pharmacopeia Apparatus 1 (basket), with a rotation speed of 100 rpm in 1000 mL of dissolution medium for pH 1.2, 4.5, and 6.8. Dissolution media (1000 mL, 37◦ C) used were 50 mM potassium phosphate (pH 6.8), 50 mM sodium acetate buffer (pH 4.5), and 0.1 N HCl (pH 1.2). Samples were withdrawn at 15, 30, 45, and 60 min and filtered, and quantitation of metformin in the samples was achieved using highperformance liquid chromatography with ultraviolet detection at 232 nm. In vitro dissolution data are presented in Figures 1–4.
In Vivo Clinical Studies Descriptions of the clinical studies presented in this paper, that is, study size, test conditions, pharmacokinetics (PK) results, and so on, are provided in Table 1. The clinical data for the immediate-release formulations that are presented were dosed under fed conditions per approved dosage and administration requirements noted in the product package insert.18 The extended-release clinical data used were generated under fasted conditions.
In Silico Model Development Parameter Input The data used in developing the metformin model for a 500 mg dose were taken from the literature and the parameter input values are listed in Table 2. The DOI 10.1002/jps
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Figure 1. (a) In vitro dissolution profile for test and reference products used in clinical studies a. The f2 test values for this plot is 52. (b) In vitro dissolution profile for test and reference products used in clinical studies a. The f2 test value for this plot is 42. (c) In vitro dissolution profile for test and reference products used in clinical studies a. The f2 test values for this plot could not be calculated. (d) In vitro dissolution profile for test and reference products used in clinical studies b. The f2 test value for this plot is 57. (e) In vitro dissolution profile for test and reference products used in clinical studies b. The f2 test value for this plot is 43. (f) In vitro dissolution profile for test and reference products used in clinical studies b. The f2 test values for this plot could not be calculated. (g) In vitro dissolution profile for test and reference products used in clinical studies c. The f2 test value for this plot is 31. (h) In vitro dissolution profile for test and reference products used in clinical studies c. The f2 test value for this plot is 32. (i) In vitro dissolution profile for test and reference products used in clinical studies C. The f2 test values for this plot could not be calculated.
absorption and clearance parameters used in the model are based on literature values for intravenous dosing and data generated from a clinical study designed to determine the site-specific absorption for
DOI 10.1002/jps
a 500 mg solution of metformin.19 This study also showed that the drug was primarily absorbed in the proximal small intestine and the primary route for elimination is the kidneys, which is in agreement with
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Figure 2. In vitro dissolution profiles at pH 1.2, 4.5, and 6.8 for Study a, metformin reference.
Figure 3. In vitro dissolution profiles at pH 1.2, 4.5, and 6.8 for Study b, metformin reference.
other published results.5 The permeability parameter in the model was scaled to fit the clinical data and agrees well with jejunal permeability measurements in rats based on an established rat to human correlation.8,20 Remaining model parameters used in the model are based on the default physiology parameters in GastroPlusTM (Simulations Plus, Inc.), which are established values that have been reported in the literature. Table 1.
Study Study a Study b Study c Study d
Figure 4. In vitro dissolution profiles at pH 1.2, 4.5, and 6.8 for Study c, metformin reference.
Metformin PK is reported to be nonlinear with respect to dose and studies have suggested that metformin is a substrate for OCTs in enterocytes, small intestine, and hepatocytes, although no specific transporter has been identified.6 The relevance of these transporters to metformin absorption is unclear as volunteers with genetic variation in expression of OCT did not show marked differences in oral absorption of metformin.6,7 In the present work, however, the model developed is based on 500 mg data and therefore the simulations are limited to this dose. Data from the human bioavailability clinical studies were used in the model development and to validate the model’s capability to predict human plasma concentrations following administration of a 500 mg oral dose. The model was deemed predictive of the clinical data by performing a virtual clinical trial (defined as the test article) and comparing it statistically to the observed clinical data (defined as the reference article). Two clinical studies for immediate-release formulations were used in the model development and two different clinical studies, one immediate release and one extended release, were used as validation to confirm that the model was predictive over a wide range of drug release times. These formulations provided a wide range of in vitro release times to test the predictive capabilities of the model.
Clinical Study Details—Metformin Reference Product (Discovery Medicine and Clinical Pharmacology, Bristol–Myers Squibb)
Number of Subjects
Dose (mg)
Description
Cmax (ng/mL), Geomean (%CV)
AUC(0– T) (ng·h/mL), Geomean (%CV)
26 24 27 15
500 500 500 500
Immediate release, single dose, fed Immediate release, single dose, fed Immediate release, single dose, fed Extended release, single dose, fasted
810.1 (22.0) 974.8 (20.4) 1019.6 (26.1) 553.3 (28.8)
7497.3 (24.0) 7288.5 (17.1) 7080.8 (27.0) 4186.0 (27.4)
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Table 2.
Model Parameters Parameter
Physical–chemical
Dose log D
Physiology Permeability (jejunum)
Value 500 mg −3.37 (pH 4) 2.2 × 10−4 cm/s
Absorption scale factors Duodenum Jejunum 1 Jejunum 2 Ileum 1 Ileum 2 Ileum 3 Cecum Ascending colon
0.549 0.540 0.536 0.530 0.500 0.707 0.015 0.015
Pharmacokinetic Clearance Volume of distribution (central) K12 K21 K13 K31
0.61 [L/(h kg)] 0.578 L/kg 1.92 1/h 1.03 1/h 0.137 1/h 0.237 1/h
Deconvolution Deconvolution was performed on each individual subject plasma concentration versus time data to determine the in vivo release for the three immediaterelease formulation studies using the mechanistic absorption model developed by Simulations Plus, Inc. (IVIVCPlusTM module, Simulations Plus, Inc.). This approach does not assume a constant absorption rate throughout the GI tract as in traditional methods. The in vivo release profile was optimized such that when convoluted, it gave the best fit to observed clinical data.
Virtual Trials—Bioequivalence Testing In order to include intersubject variability into the simulations, virtual clinical trials were simulated using the “virtual trial” feature of the GastroPlusTM software (Simulations Plus, Inc.). The coefficient of variation (CV) of the model input parameters, such as clearance, volume of distribution, subject weight, and so on, was adjusted to match the variability of the clinical study data, thereby resulting in %CV for the Cmax and AUC similar to those of the clinical study. The numbers of subjects used in the virtual trial simulations were the same as the number of subjects for the clinical study being compared. Bioequivalence between the test and reference products was established for the area under the curve determined from the plasma concentration vs. time data for a specified time interval (AUC(0 –T)) and Cmax obtained from the individual subject plasma concentration–time profiles and an average bioequivalence assessment using the fixed effects model (WinDOI 10.1002/jps
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Nonlin Bioequivalence Toolkit; Pharsight Corporation) was performed. Except where noted, the test formulation was the virtual trial simulation and the reference formulation was the clinical trial data. The test and reference formulations were considered bioequivalent if the 90% confidence interval for Cmax and AUC(0–T) fell within the range of 0.80–1.25.21 Once the model was finalized, all parameters were kept constant during the simulations comparing the different release profiles. Generation of In Vitro Release Profiles for Evaluating the Effect of Drug Release Rate on Predicted In Vivo Performance Simulated drug release profiles within the range of 5 min up to 10 h for 100% of metformin to be released (Fig. 5) were used as input for the model. The Higuchi equation was used to simulate these profiles based on the following two assumptions22 : (1) the dissolution of metformin is assumed to be rapid if there are no formulation effects due to its high solubility (100% within 15 min) and (2) release of the metformin beyond 15 min is diffusion limited due to the formulation, as was evidenced from the slower releasing in vitro profiles, that is, 85% greater than 15 min, being proportional to the square root of time. The Hixson–Crowell Cube Root Law was not used for these simulations as this equation is written to assume that dissolution is primarily a function of the particle size and solubility of the drug.23 As metformin is highly soluble, much greater than 100 mg/mL, particle size does not affect the dissolution rate within the range of particle diameters that are used in the formulations. The simulations to predict the plasma concentrations of metformin for different release rates were performed as virtual clinical trials so that variance could be introduced into the predictions and the AUC and Cmax compared statistically to the clinical data.
RESULTS AND DISCUSSION The extension of previous biowaiver considerations beyond BCS 1 compounds to BCS 3 compounds has been previously studied for both metformin and cimetidine.9,12–15 A simulations approach investigating the range of absorption and elimination rate constants for typical BCS 1 and BCS 3 compounds suggested that all BCS 3 compounds might be appropriate for biowaivers.13 Comparing in vitro dissolution parameters with in vivo performance for two metformin formulations with almost identical drug release profiles across physiological pH range indicated that a biowaiver approach would be feasible for this compound, although the evaluation for dissimilar drug release profiles was not undertaken.13 That issue was pursued by Homsek et al.14 who studied two formulations of metformin with differing drug JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 101, NO. 5, MAY 2012
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a third approach of equal validity as it includes all of the key parameters that fully define the absorption profile of this compound, that is, dissolution, permeability, and GI residence time. In comparing an f2 calculation versus a modeling and simulation approach, as BCS 3 compounds have limited permeability, transit time becomes a critical factor to the total fraction dose absorbed, and a model which includes GI transit as well as dissolution and permeability should be more mechanistically accurate and a stronger tool for making bioequivalence comparisons than dissolution alone. It is based on this argument that the in silico model was considered to show that for a specific range of dissolution rates, metformin products should be bioequivalent regardless of the results of the f2 test. Confirmation of Model Predictability
Figure 5. Simulated metformin release profiles based on the Higuchi equation plus in vitro dissolution profiles from products from Studies a and d. These profiles were used as input to the PK absorption model.
release properties that were demonstrated to be bioequivalent and a good in vitro–in vivo correlation was established. Similarity factor calculations of drug release profiles failed to demonstrate similarity of the products tested, which would have obviated the possibility if a biowaiver approach as is done for BCS 1 compounds. Jantratid et al.15 showed that cimetidine formulations engineered to have different release rates could be used to define an in vitro–in vivo correlation that identified the limits of dissolution rate ranges where an effect on bioperformance might be expected.15 This allowed definition of tightly defined criteria around formulation, dissolution method, and a “rapidly dissolving” performance in that method that could be used as a basis for a biowaiver for cimetidine tablets. These existing studies have not fully considered the interaction of drug release, permeability, and GI transit time and so may still not encompass all dosage forms with quite diverse drug release characteristics that would be bioequivalent, although Tsume and Amidon16 have undertaken in silico modeling for three BCS 3 compounds, atenolol, cimetidine, and amoxicillin, and demonstrated that bioequivalence is expected when comparing products with drug release times of up to 60 min.16 Two approaches are commonly used to establish bioequivalence between two drug products, that is, statistical comparison of clinical studies and statistical comparison between sets of in vitro dissolution profiles.21,24,25 For the specific case of metformin, in silico modeling and simulation is presented to offer JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 101, NO. 5, MAY 2012
Table 3 shows the point estimates and upper and lower 90% confidence intervals comparing the model predictions to the observed clinical values for three immediate-release and one sustained-release metformin products. Studies B and C were used to build the model and then the model was used to predict the AUC(0–T) and Cmax for Study a (immediate release) and Study d (extended release). In each case, the simulations were bioequivalent confirming the accuracy of the model to predict clinical PK outcomes in multiple ways. First, it shows that model variance adequately represents the subject variability for each clinical group studied. Furthermore, as the slow release dose (extended-release formulation) is also well predicted, these results show that the model accurately represents the permeability profile and transit times throughout the entire GI tract and provides an example where the release rate of metformin begins to impact the Cmax and AUC. This model was then used to simulate the plasma profiles for drug release profiles ranging from 100% drug release in 5 min up to 100% drug release in 14 h.
In Vitro Dissolution The premise for the present work is based on the in vitro comparison of two 500 mg immediate-release metformin products (an FDC compared with a single entity) at pH values of 1.2, 4.5, and 6.8. The average data for the in vitro dissolution for the metformin products used in the clinical studies summarized in Table 1 are shown in Figures 1a–1i. Although there is considerable variability in the 60 mi dissolution for these products, all were shown to be bioequivalent to the metformin reference product. In Figures 2, 3, and 4, the in vitro dissolution profiles at the individual pH values are plotted together for each clinical study as a function of pH and time (for the immediate-release dosage forms only). As is shown in these surface plots, the pH does not impact the release of drug over 60 min DOI 10.1002/jps
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Table 3. Results of Model Simulations and Statistical Comparison of the Cmax and AUC(0– T) to Clinical Data for Four 500 mg Metformin Products Formulation 500 mg IR, fed (Study
Parameter a)a
500 mg IR, fed (Study b) 500 mg IR, fed, (Study c) 500 mg SR, fasted, (Study d)
AUC(0– T) (ng·h/mL) Cmax (ng/mL) AUC(0– T) (ng·h/mL) Cmax (ng/mL) AUC(0– T) (ng·h/mL) Cmax (ng/mL) AUC(0– T) (ng·h/mL) Cmax (ng/mL)
Point Estimate
Lower 90% CI
Upper 90% CI
0.92 1.09 0.95 0.91 1.00 0.91 1.06 0.97
0.81 0.96 0.82 0.80 0.89 0.80 0.89 0.81
1.04 1.23 1.08 1.05 1.13 1.03 1.25 1.15
a Study a are the results of model simulations and statistical comparison of the C max and AUC(0– T) to clinical data for the metformin product exhibiting dissimilar in vitro dissolution profiles (f2 = 42) and bioequivalent clinical data.
for the Study a metformin reference, whereas there is a greater dependence on pH for the metformin reference products used in Studies B and C based on the in vitro dissolution even though the products were bioequivalent. Figure 1b shows the in vitro dissolution profiles of the metformin products tested from Study a that were bioequivalent but did not meet the f2 criteria for equivalence, that is, the dissolution at pH 4.5 had an f2 = 42 and therefore did not meet the similarity criteria. Comparison of In Vitro Release Profiles to In Vivo Performance for Metformin Although generally limited to BCS 1 compounds and in vitro–in vivo correlations, comparison of in vitro release profiles has been also proposed as an argument for waiving bioequivalence studies for BCS 3 compounds. The scientific argument for BCS 3 compounds is the same as for a BCS 1 compound, that is, if two drug products have the same in vivo dissolution profile under all luminal conditions, they will have the same rate and extent of drug absorption and assumes that any difference in bioavailability between two products will be due to the release of drug from the product and not permeability.26 However, it must be noted that for BCS 3 compounds, the phrase “under all luminal conditions” is more limited than for BCS 1 compounds in that changes in the GI transit time can have a greater impact on the fraction dose absorbed due to the drug’s low permeability. As both BCS 1 and 3 compounds have high solubility throughout the luminal pH range, in vitro dissolution testing may be considered adequate to show the similarity in the dissolution of the two products. The pH values often used to represent “all” luminal conditions are 1.2, 4.5, and 6.8 and the statistical test used to determine if two profiles are the same is the f2 similarity test.25 It is important to note that although the f2 similarity test adequately determines when two dissolution profiles are similar, that is, less than 10% difference between time points, it does not provide any information pertaining to bioequivalence if the profiles are DOI 10.1002/jps
not closely similar. The test infers that if the f2 value is less than 50, the two products that are being compared are not bioequivalent. In addition to the implicit nature of this test, there are other restrictions to this calculation. The f2 calculation is based on the sum of the square of the errors and therefore is dependent on the selection of the sample points.27–29 As a result, the two products under consideration may or may not be equivalent depending on the reasons described above. Two metformin products were compared using in vitro dissolution at pH 1.2, 0.5, and 6.8. When the dissolution at pH 4.5 did not pass the f2 test, a clinical study of 24 subjects was conducted for the FDC and single entity metformin products under fed conditions. The AUC(0-T) and Cmax for the individual subjects were compared and the two products were found to be bioequivalent based on the lower and upper 90% confidence intervals being within 0.80 and 1.25, respectively (Study a, Table 4). Use of Modeling and Simulation to Establish Bioequivalence The use of in silico tools has expanded in recent years to include contributions of the dosage form, release rate, and GI and physiological properties in addition to classical compartmental PK to model and predict the drug absorption process.30,31 The advantage of using these models to predict PK outcomes is that they go beyond comparison of the in vitro dissolution data by adding GI transit time, permeability, and clearance. The model developed for this current analysis combines the dissolution rate of metformin from the formulation, GI permeability and transit, and physiological variability to provide an accurate prediction of the Cmax and AUC. Additional Considerations Regarding the Relationship Between the In Vitro Dissolution, In Vivo Release, and the Fraction Dose Absorbed To help understand why this range of in vivo release will result in no significant change to the AUC and Cmax , the in silico model was used to simulate the plasma concentration versus time curves using a wide JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 101, NO. 5, MAY 2012
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Table 4.
Clinical Trial Results Showing Bioequivalence Statistics of the Test and Reference Metformin Products Point Estimate (90% Confidence Interval)
Study #
Test and Reference Products
Cmax (ng/mL)
AUC(0– T) (ng·h/mL)
Study a Study b Study c
Metformin FDC Test versus Metformin Reference Metformin FDC Test versus Metformin Reference Metformin Test versus Metformin Reference
1.00 (0.97–1.04) 1.00 (0.93–1.08) 1.01 (0.96–1.06)
1.02 (0.96–1.08) 1.02 (0.99–1.06) 1.03 (1.00–1.07)
range (5 min up to 14 h release) of metformin release profiles as input. Figure 5 shows the simulated drug release profiles (100% released in 5 min up to 10 h) as well as the experimental in vitro dissolution profiles associated with the metformin products used in the clinical studies A (83% released in 1 h and 100% released in approximately 1.5 h) and D (93% released in 12 h and approximately 100% released in 14 h) that were used as input in the model simulations. Figures 6 and 7 show the AUC(0–T) and Cmax plotted as geometric means and SD for the different release rates. The symbols (circles) represent the clinical data (Table 3) corresponding to dissolution times observed for the products tested shown in Figure 5. In each case, the simulations were bioequivalent to the clinical data, that is, the Cmax and AUC(0–T) fell within the 0.80–1.25 range for the 90% confidence intervals. On the basis of these simulations, release times for metformin ranging from 5 min up to 2 h did not have a statistically significant effect on Cmax and AUC. Beyond 2 h, the Cmax and AUC(0–T) decreased and were no longer bioequivalent. These results are not unexpected and are substantiated by considering the wide range of in vitro release profiles presented in
Figure 6. Model simulations versus clinical data (circles) for metformin release profiles ranging from 5 min to 14 h for 100% to be released. Note that the model predictions were bioequivalent to the clinical data. JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 101, NO. 5, MAY 2012
Figure 7. Model simulations versus clinical data (circles) for metformin release profiles ranging from 5 min to 14 h for 100% to be released. Note that the model predictions were bioequivalent to the clinical data.
Figures 1a–1i that show bioequivalence and the fact that the rate-limiting step to absorption of metformin is permeability and not solubility, as has been shown by several authors. To further the understanding of the relationship between the in vitro drug release and the in vivo drug release, these values were plotted in Figure 8 as the mean ± SD for the individual data from the metformin products tested in the clinical studies along with the fraction dose absorbed This plot was constructed by determining the mean and SD for the (1) in vivo release profiles of the individual subjects from the three immediate-release studies determined via deconvolution; (2) in vitro release profiles for metformin at pH 1.2, 4.5, and 6.8; and (3) the fraction dose absorbed for the mean value of the input parameters. Comparing first the in vitro to in vivo release profiles, Figure 8 shows that although both profiles have considerable variability (20%–70% for the in vivo and 7%–35% for the in vitro during the first hour), the in vitro release is slower than the in vivo release. When these profiles are compared with the fraction dose absorbed, both are faster, thereby confirming DOI 10.1002/jps
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Although this work specifically applies to metformin, this approach may be applicable to other BCS 3 compounds that have well defined dissolution and known absorption characteristics.
REFERENCES
Figure 8. Average (± SD) in vivo release profiles for clinical studies a, b, and c, average (± SD) in vitro dissolution for metformin at all pH values, and the metformin fraction dose absorbed (mean values only).
that the permeability and transit time in the intestine are rate limiting to absorption and not solubility.32
CONCLUSIONS The modeling approach presented has defined the range of in vitro drug release profiles that map to a bioequivalent in vivo performance for metformin, accounting for release rate, permeability, and transit time. Once the initial clinical data are available to build the model, it will allow the waiving of in vivo bioequivalence studies for a metformin drug product available from multiple sources where diverse drug release properties are exhibited. This work represents a more detailed biopharmaceutics-based approach and avoids the challenges of current similarity factor assessments for in vitro dissolution profiles, which may show nonsimilarity for bioequivalent BCS 3 drug products. It was shown through modeling techniques and clinical data that there is no impact of in vitro drug release on in vivo performance over a broad, defined range of metformin release rates. This analysis also illustrates that it is possible to develop an approach for requesting a biowaiver for the BCS 3 compound metformin through the use of combining PK modeling tools with in vitro dissolution to set a range of release rates that are expected to have no impact on AUC and Cmax and therefore result in bioequivalence. DOI 10.1002/jps
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DOI 10.1002/jps
