Physiologically‐Based Pharmacokinetic Modeling in Renal and Hepatic Impairment Populations: A Pharmaceutical Industry Perspective

TLDR

The study evaluated PBPK model predictions for renal and hepatic impairment using clinical data from 29 compounds across 106 study arms collected from 19 industry partners. PBPK models predicted AUC ratios within twofold of observed values for >90% of renal impairment and >70% of hepatic impairment cases, though moderate to severe hepatic impairment tended to be overestimated; these results suggest PBPK can guide study design, timing, and potential waivers for mild impairment.

Abstract

The predictive performance of physiologically‐based pharmacokinetics (PBPK) models for pharmacokinetics (PK) in renal impairment (RI) and hepatic impairment (HI) populations was evaluated using clinical data from 29 compounds with 106 organ impairment study arms were collected from 19 member companies of the International Consortium for Innovation and Quality in Pharmaceutical Development. Fifty RI and 56 HI study arms with varying degrees of organ insufficiency along with control populations were evaluated. For RI, the area under the curve (AUC) ratios of RI to healthy control were predicted within twofold of the observed ratios for > 90% ( N = 47/50 arms). For HI, > 70% ( N = 43/56 arms) of the hepatically impaired to healthy control AUC ratios were predicted within twofold. Inaccuracies, typically overestimation of AUC ratios, occurred more in moderate and severe HI. PBPK predictions can help determine the need and timing of organ impairment study. It may be suitable for predicting the impact of RI on PK of drugs predominantly cleared by metabolism with varying contribution of renal clearance. PBPK modeling may be used to support mild impairment study waivers or clinical study design.