Linking in vitro–in vivo extrapolations with physiologically based modeling to inform drug and formulation development

Abstract

Linking in vitro-in vivo extrapolations with physiologically based modeling to inform drug and formulation developmentQuantitative in vitro-in vivo extrapolations (IVIVE) have been applied extensively to predict drug metabolism and transporter kinetics (Sodhi & Benet, 2021;Wood et al., 2017;Zamek-Gliszczynski et al., 2013). However, initially, IVIVE were mainly based on mean in vitro data, giving no estimation of between or within subject variability (BSV/WSV) and, therefore, have a limited ability to address the extremes of risk in real patients or replicate scenarios such as bioequivalence. In other words, ADME properties were estimated considering an average subject, if such a subject exists, under a constant non-variant condition for all the physiology and biology. Integrating IVIVE with PBPK modeling enables predictions in virtual cohorts including estimation of BSV (Rostami-Hodjegan & Tucker, 2007), and some recent advances were also made to address the WSV that are essential elements of virtual bioequivalence studies (Bego et al., 2022). Historically, Monte Carlo simulations are used when developing population PBPK models which commonly do not consider the parameter's inter-dependencies. However, it is imperative to mechanistically incorporate covariates in these models and to employ correlated Monte Carlo simulations instead (Jamei, 2016;Jamei et al., 2009). In doing so, the predicted PK properties are inherently affected by the relevant covariates (Rostami-Hodjegan & Tucker, 2007). However, translation of in vitro ADME properties Research activities in the Center for Applied Pharmacokinetic Research Center (CAPKR) at the University of Manchester are funded by a consortium of pharmaceutical companies.