Prospective Prediction of Food Effect Using PBPK Modeling: Is the Science On Par with Expectations?

This talk will introduce the application of Physiologically-Based Pharmacokinetic (PBPK) absorption modeling to evaluate the impact of food on absorption and pharmacokinetics from an industry perspective. The goal of the presentation is to share the experiences from IQ Food Effect PBPK Working Group and drug developers on how to use in silico approaches to predict the impact of food on relative bioavailability and support drug product development.
Within the pharmaceutical industry, significant resources are invested to predict and characterize a clinically relevant food effect. Given the complex nature of food effect, an integrated approach is required, and physiologically based absorption models have emerged as a key platform to support food effect predictions. This talk will highlight cases where high and moderate, vs. low confidence is expected in predicting food effect using a novel consistent, prospective approach, in contrast to previous retrospective analyses. Additionally, this talk also aims to provide an aligned approach to model development and validation for food effect, as well as an industry perspective on cases where modeling may be used in lieu of clinical studies. This presentation will shed light on understanding prediction success of food effect and its correlation with the mechanisms driving this effect.