Work

Optimization of Bottom‐Up PBPK Model Development in SIMCYP via Retrospective Analysis of Clinical Human PK Data

Year: 2025

Type: article

Abstract: ABSTRACT Physiologically‐based pharmacokinetic (PBPK) modeling has become a major tool in drug discovery and development. Here, we describe the bottom‐up PBPK modeling approaches employed at AbbVie using Simcyp Simulator and evaluate the impact of three system parameters, GI physiology, P‐gp Relative Expression Factor (REF), and recombinant CYP enzyme (rCYP) intersystem extrapolation factor (ISEF), independently and in combination, on PBPK prediction performance through retrospective analysis of 8 clinical assets. Overall, the application of New GI physiology resulted in a considerable improvement in the prediction of oral absorption for most compounds compared to the Original GI physiology (C max : 76% vs. 43% within 3‐fold) when using the default P‐gp REF (1.5) and adjusted ISEF. Decreasing P‐gp REF to 0.5 resulted in additional improvement in the predictions of C max for P‐gp substrates (86% within 3‐fold). The observed plasma exposure‐time profiles and AUC INF are better predicted using the default rCYP ISEF values instead of individually adjusted values (48% vs. 43% within 3‐fold) when using the Original GI and default P‐gp REF (1.5). The combination of optimized parameters (New GI physiology, P‐gp REF of 0.5 and rCYP default ISEF) predicted the plasma exposures (AUC INF and C max ) within 3‐fold for 81% and 86% of the tested simulations, respectively. In conclusion, the present study proposes an optimized strategy for bottom‐up PBPK model development in Simcyp Simulator. Retrospective comparison with observed clinical PK data is vital for model verification as well as further improvement in prospective predictions for future drug candidates.

Source: Clinical and Translational Science

DOI: 10.1111/cts.70417