Application of IVIVE and PBPK modeling in prospective prediction of clinical pharmacokinetics: strategy and approach during the drug discovery phase with four case studies

TLDR

Prospective IVIVE and PBPK simulations of human PK parameters are becoming essential in drug discovery and development. The paper outlines a strategy to use IVIVE and PBPK modeling to support clinical candidate nomination by integrating all available preclinical data to predict absorption, distribution, and clearance. The authors employ a three‑stage approach—parameter evaluation, model selection, and scenario simulation—implemented in the Simcyp® simulator and illustrated with four case studies to predict absorption, distribution, and clearance. Prospective predictions generally matched observed clinical data, with Cmax and AUC within two‑fold for all compounds after a single dose and three of four after multiple doses, tmax within two‑fold for all, but Clast was less accurate and AUC and Clast tended to be overestimated, especially for compound 2 due to likely clearance underestimation.

Abstract

Prospective simulations of human pharmacokinetic (PK) parameters and plasma concentration-time curves using in vitro in vivo extrapolation (IVIVE) and physiologically based pharmacokinetic (PBPK) models are becoming a vital part of the drug discovery and development process. This paper presents a strategy to deliver prospective simulations in support of clinical candidate nomination. A three stage approach of input parameter evaluation, model selection and multiple scenario simulation is utilized to predict the key components influencing human PK; absorption, distribution and clearance. The Simcyp® simulator is used to illustrate the approach and four compounds are presented as case studies. In general, the prospective predictions captured the observed clinical data well. Predicted C(max) was within 2-fold of observed data for all compounds and AUC was within 2-fold for all compounds following a single dose and three out of four compounds following multiple doses. Similarly, t(max) was within 2-fold of observed data for all compounds. However, C(last) was less accurately captured with two of the four compounds predicting C(last) within 2-fold of observed data following a single dose. The trend in results was towards overestimation of AUC and C(last) , this was particularly apparent for compound 2 for which clearance was likely underestimated via IVIVE. The prospective approach to simulating human PK using IVIVE and PBPK modeling outlined here attempts to utilize all available in silico, in vitro and in vivo preclinical data in order to determine the most appropriate assumptions to use in prospective predictions of absorption, distribution and clearance to aid clinical candidate nomination.