Fraction of a dose absorbed estimation for structurally diverse low solubility compounds

Area of Science:

• Pharmacokinetics and Drug Metabolism
• Computational Chemistry
• Pharmaceutical Sciences

Background:

• Accurate prediction of oral drug absorption is crucial for efficient drug discovery and development.
• Low solubility drugs present significant challenges in predicting in vivo absorption.
• Mechanistic modeling offers a promising approach to overcome these challenges.

Purpose of the Study:

• To evaluate the prediction accuracy of the fully mechanistic Gastrointestinal Unified Theoretical (GUT) framework.
• To assess the GUT framework's ability to predict in vivo oral absorption of low solubility drugs.
• To determine the practical applicability of the GUT framework in drug discovery versus drug development.

Main Methods:

• Utilized solubility, molecular weight, logP(oct), pK(a), Caco-2 permeability, dose, and particle size as input parameters.
• Included undissociable/free acids and free base drugs, considering stomach pH effects.
• Collated 110 Fa% data points from literature for 29 diverse compounds in humans and dogs.

Main Results:

• The GUT framework achieved prediction accuracy within a 2-fold error in approximately 80% of cases.
• The model successfully captured dose and particle size dependency of fraction absorbed (Fa%), accounting for particle drifting.
• The framework demonstrated practical predictability for drug discovery, but not yet for drug development.

Conclusions:

• The validated GUT framework shows practical predictability for oral absorption of low solubility drugs during the drug discovery phase.
• The model's accuracy suggests its utility in early-stage pharmaceutical research.
• Further validation is needed for salt forms and specialized formulations like solid dispersions and emulsions.