A Workflow for Global Sensitivity Analysis of PBPK Models

TLDR

PBPK models integrate in vitro and in vivo data for toxicity testing but must account for nonlinear processes such as enzyme saturation and parameter interactions. The study seeks a sensitivity analysis method that quantifies the influence of individual parameters, their interactions, and nonlinear processes. We present a computationally feasible SA workflow that captures interactions and displays results as bar charts and Lowry plots, which are intuitive for toxicologists, risk assessors, and regulators.

Abstract

Physiologically based pharmacokinetic (PBPK) models have a potentially significant role in the development of a reliable predictive toxicity testing strategy. The structure of PBPK models are ideal frameworks into which disparate in vitro and in vivo data can be integrated and utilized to translate information generated, using alternative to animal measures of toxicity and human biological monitoring data, into plausible corresponding exposures. However, these models invariably include the description of well known non-linear biological processes such as, enzyme saturation and interactions between parameters such as, organ mass and body mass. Therefore, an appropriate sensitivity analysis (SA) technique is required which can quantify the influences associated with individual parameters, interactions between parameters and any non-linear processes. In this report we have defined the elements of a workflow for SA of PBPK models that is computationally feasible, accounts for interactions between parameters, and can be displayed in the form of a bar chart and cumulative sum line (Lowry plot), which we believe is intuitive and appropriate for toxicologists, risk assessors, and regulators.