Abstract
Predicting oral bioavailability remains a central challenge in pharmaceutical sciences, primarily limited by the phenomenological nature of traditional predictive models that provide correlations without mechanistic insight. While molecular dynamics (MD) simulations provide detailed atomistic insights into drug-membrane interactions, they require rigorous experimental validation. Conversely, biorelevant assayssuch as Caco-2 monolayers and everted gut sacssupply essential biological end points but with limited mechanistic granularity. This review systematically evaluates the strengths and limitations of disparate approaches, from static quantitative structure-property relationship (QSAR) models to physics-based molecular simulations. We propose an integrated framework that synergistically combines the physical resolution of multiscale MD modeling with the biological relevance of hierarchical experimental validation. Using a representative molecule with a divergent pharmacokinetic profilecharacterized by high predicted permeability yet substantial metabolic instabilityas an exemplary case, we present a mechanistic workflow for resolving such discrepancies. This integrated approach transforms the validation process from a binary outcome into a diagnostic tool for mechanistic deconstruction, ultimately guiding the rational design of next-generation orally bioavailable therapeutics.