Solubility prediction, solvate and cocrystal screening as tools for rational crystal engineering

Area of Science:

• Computational chemistry
• Drug development
• Physical chemistry

Background:

• Increasing insolubility of novel drug candidates poses a significant challenge in modern drug development.
• Computational tools offer potential solutions for screening solvents and identifying cocrystal formers to enhance bioavailability.

Purpose of the Study:

• To provide an overview of recent developments in the COSMO-RS (conductor-like screening model for real solvents) approach relevant to drug development.
• To present new applications of COSMO-RS for predicting drug solubility and screening for solvates and cocrystals.

Main Methods:

• The study utilized the COSMO-RS (conductor-like screening model for real solvents) approach for all property predictions.
• COSMO-RS employs screening charge density from first-principles calculations and statistical thermodynamics to determine chemical potential in solution.

Main Results:

• Fast and accurate assessment of drug solubility is achievable with COSMO-RS.
• Identification of suitable solvents, solvates, and cocrystal formers is now possible, complementing drug development efforts.
• Efficiency is improved by utilizing a database of pre-computed molecular fragments, bypassing expensive quantum-chemical calculations.

Conclusions:

• COSMO-RS theory is applicable to various physicochemical properties crucial for rational crystal engineering.
• Accurate quantitative solubility predictions in diverse solvents and mixtures are feasible when combined with experimental data.
• COSMO-RS effectively predicts cocrystal formation, demonstrating high accuracy in coformer screening, with recent variants offering speed and ease of use by avoiding quantum chemical calculations.