Establishment of Virtual Bioequivalence via DoE-PBPM Model: A Donepezil Case Study
Frederico S. Martins(1), Renê Oliveira do Couto(2), Grace Fraczkiewicz(1), Sherwin S.Sy(3), Osvaldo Freritas(4)
(1)Research, Simulations Plus, Inc., Lancaster, California, United States; (2) Federal University of São João del-Rei, Midwest Campus, Divinópolis, MG, Brazil; (3)Department of Statistics, State University of Maringá, Paraná, Brazil; (4) University of São Paulo, Ribeirão Preto, Brazil.
Objectives: Donepezil (DZP) is a medication used to treat Alzheimer's disease. It works by inhibiting the breakdown of acetylcholine in the brain, which is a neurotransmitter important for memory and cognitive function. The immediate release (IR) tablets of donepezil (Aricept) were approved by the Food and Drug Administration in 1996, and an extended release (XR) formulation was approved in 2010. The XR tablet is different from the IR formulation in that it has a slower time to peak concentration following oral ingestion. One way to deliver drugs over an extended period through oral consumption is to use hydrophilic matrix tablets, which are made by incorporating water-swellable polymers that quickly expand and form a gel layer around the dry core, regulating the rate of drug release as it moves through the gastrointestinal tract. The goal of this work was to develop a new formulation of donepezil XR that performs as well as the commercial product. To achieve this, the researchers used Design of Experiments (DoE) and Physiologically Based Biopharmaceutics Modeling (PBBM) to predict the effects of formulation changes on in vivo pharmacokinetics during the early stages of XR tablet development. This approach could potentially save time and resources required for the development of SR formulations.
Methods: The impact of excipients on drug release rate were studied using a 3-factors, 3-levels Box-Behnken design (BBD). The independent variables were HPMC100cps, HPMC4000cps, and NaCMC, lactose was used as filler. The dependent variables were release at 1 h, 2.5 h, 5.0 h, and 13 h. PBBM modeling and simulations were performed using the GastroPlus® software. The donepezil model was developed by implementing a stepwise sequential modeling strategy, in line with previously published literature and regulatory guidelines. The virtual bioequivalence trials were designed as two-sequence, two treatment, two-period, crossover studies.
Results: The dissolution of all formulations were fitted by the Weibull function with the correlation coefficient values of ≥ 0.98 (r2). ANOVA and correlation analyses were performed and the response surface analysis allowed the fitting of polynomial equations of the dependent variables as a function of the significant factors for predicting quality indicators. The optimized formulation was composed for 20 % of HPMC100, 20% of HPMC4000 and 5 % of NaCMC with an observed release 1h = 22%, 2.5h = 55%, and 13h = 76%. The PBBM model performance was verified with nine observed datasets, the mean predicted Cmax and AUC0-t values were within 1.25-fold of the respective mean observed. The IVIVE-PBBM model was used in a stepwise risk assessment of bioequivalence criteria for the optimized formulation. The parametric 90% confidence intervals for ratio T/R ranged from 0.87 – 1.2 (point estimate 0.95-1.08) for AUC0–24, 0.89-1.14 (point estimate 0.98-1.09) for Cmax, respectively, and were entirely included within the bioequivalence acceptance limits 80 - 125 %.
Conclusions: In summary the DoE-PBBPM was successfully used to optimize and establish the vBE between 2 donepezil SR formulations. The formulation made with 40% of HPMC and 5% of NaCMC is BE with Aricept XR. However future studies on an impact of tablet compression force could contribute to development of formulation specifications. The DoE-PBBM has shown to be an alternative to complementary formulation development and BE studies
References:
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