Predictive approaches to increase absorption of compounds during lead optimisation.

Area of Science:

• Drug Discovery
• Medicinal Chemistry
• Pharmacokinetics

Background:

• Oral drug absorption is governed by complex physicochemical and biological processes.
• Understanding these factors is crucial for optimizing drug candidates.

Purpose of the Study:

• To review physicochemical and structural requirements for intestinal absorption.
• To provide methods for improving solubility and permeability during lead optimization.

Main Methods:

• Review of established models for estimating oral absorption (e.g., logD-cMR, Abraham solvation equations).
• Utilizing measured physicochemical properties like solubility and permeability for improved prediction.
• Employing in vitro clearance measurements with liver microsomes to assess first-pass metabolism.

Main Results:

• Solubility and permeability are key physicochemical requirements for absorption, influenced oppositely by lipophilicity and molecular size.
• Various models can predict oral absorption from chemical structures or properties.
• Measured solubility and permeability enhance in vivo absorption estimations.

Conclusions:

• Physicochemical property assessment aids in designing drug compounds with enhanced oral absorption.
• Predictive models and in vitro data are valuable tools in lead optimization.
• Active transporters and first-pass metabolism can impact oral absorption predictions.