Computational models to predict aqueous drug solubility, permeability and intestinal absorption

Area of Science:

• Pharmacology and Drug Development
• Computational Chemistry
• Biopharmaceutics

Background:

• Poor intestinal absorption is a significant obstacle in developing orally administered drugs.
• This absorption issue often stems from low aqueous solubility and/or poor cell permeability.
• Drug stability and metabolism further complicate absorption, necessitating predictive modeling.

Purpose of the Study:

• To review databases and techniques for developing in silico absorption models.
• To highlight the critical role of aqueous drug solubility in drug development.
• To provide insights into computational approaches for predicting drug absorption.

Main Methods:

• Literature review of published papers on in silico absorption models.
• Analysis of databases and computational techniques used in model development.
• Focus on methods predicting aqueous drug solubility and intestinal permeability.

Main Results:

• In silico models are increasingly utilized to predict drug absorption properties.
• Aqueous solubility is a primary concern addressed by these predictive models.
• Various databases and computational techniques contribute to model accuracy.

Conclusions:

• Predictive in silico models are essential tools for optimizing drug candidates.
• Addressing poor aqueous solubility is key to improving oral drug absorption.
• Continued development of computational methods will accelerate drug discovery.