In Vitro In Vivo Extrapolation and Bioequivalence Prediction for Immediate-Release Capsules of Cefadroxil Based on a...

Physiologically based pharmacokinetic (PBPK) modeling is a mechanistic concept, which helps to judge the effects of biopharmceutical properties of drug product such as in vitro dissolution on its pharmacokinetic and in vivo performance. With the application of virtual bioequivalence (VBE) study, the drug product development using model-based approach can help in evaluating the possibility of extending BCS-based biowaiver. Therefore, the current study was intended to develop PBPK model as well as in vitro in vivo extrapolation (IVIVE) for BCS class III drug i.e. cefadroxil. A PBPK model was created in GastroPlus™ 9.8.3 utilizing clinical data of immediate-release cefadroxil formulations. By the examination of simulated and observed plasma drug concentration profiles, the predictability of the proposed model was assessed for the prediction errors. Furthermore, mechanistic deconvolution was used to create IVIVE, and the plasma drug concentration profiles and pharmacokinetic parameters were predicted for different virtual formulations with variable cefadroxil in vitro release. Virtual bioequivalence study was also executed to assess the bioequivalence of the generic verses the reference drug product (Duricef^®). The developed PBPK model satisfactorily predicted C_max and AUC_0-t after cefadroxil single and multiple oral dose administrations, with all individual prediction errors within the limits except in a few cases. Second order polynomial correlation function obtained accurately predict in vivo drug release and plasma concentration profile of cefadroxil test and reference (Duricef^®) formulation. The VBE study also proved test formulation bioequivalent to reference formulation and the statistical analysis on pharmacokinetic parameters reported 90% confidence interval for C_max and AUC_0-t in the FDA acceptable limits. The analysis found that a validated and verified PBPK model with a mechanistic background is as a suitable approach to accelerate generic drug development.