Biopharmaceutical Modeling of Food Effect─Exploring the Role of Dietary Fat.

ABSTRACT

In preclinical drug discovery, simple fraction absorbed calculators are exceptionally valuable tools to better understand the potential limitations to drug absorption and how different formulation approaches may address them. These tools often struggle to accurately capture the impact of food on drug absorption. One possible reason for this is that these models overlook the potential role of dietary fat in altering drug absorption. Herein, we present a novel approach to incorporate the fat content from diet within an absorption model as an additional set of particles that can accumulate in the mucus and act to reduce the effective thickness of the unstirred water layer. Using this approach, we demonstrate improved model prediction on the extent of food effect for a range of marketed compounds comparing two historical absorption models and the new model developed in this work using published food effect data for 21 marketed compounds. We extended this work to investigate each model's ability to predict the reported food effect across a range of dose levels for Venetoclax. Finally, we investigate the new model's capability to predict food effect in both low-fat and high-fat fed states and compare these predictions to the two historical models using three model compounds Albendazole, Pazopanib, and Venetoclax.