Predictive models for oral drug absorption: from in silico methods to integrated dynamical models

Area of Science:

• Pharmacokinetics and Drug Development
• Computational Modeling in Pharmacology

Background:

• Poor oral absorption is a primary cause for drug candidate termination.
• Oral drug absorption is a multifaceted process involving drug, formulation, and physiological factors.
• In silico and computational models are crucial for informed decision-making in drug absorption studies.

Purpose of the Study:

• To review diverse computational methods for predicting oral drug absorption.
• To highlight the application of these models across key absorption processes.
• To discuss integrated absorption prediction systems and software.

Main Methods:

• Review of in silico, computational, and mathematical modeling techniques.
• Focus on models addressing solubility, permeability, dissolution, release rates, and gastrointestinal transit.
• Inclusion of modern integrated absorption prediction systems and software.

Main Results:

• A spectrum of computational tools exists, from simple empirical methods to complex dynamic systems.
• These models support the evaluation of critical oral absorption parameters.
• Integrated systems offer comprehensive approaches to absorption prediction.

Conclusions:

• Computational modeling is indispensable for overcoming oral absorption challenges in drug development.
• A variety of in silico tools can be applied to predict and optimize drug absorption.
• Advanced computational systems enhance the prediction of drug behavior in the gastrointestinal tract.