Novel high/low solubility classification methods for new molecular entities.

Area of Science:

• Pharmaceutical Sciences
• Drug Discovery and Development

Background:

• Accurate solubility classification is crucial for new molecular entities (NMEs) in drug development.
• Traditional methods often rely on dose number criteria, which can be limiting.

Purpose of the Study:

• To establish a rapid and accurate solubility classification approach for NMEs.
• To define decision rules based on measured solubility (MSol) and log solubility (MLogSM).

Main Methods:

• Classified 635 compounds into high (BDDCS/BCS 1/3) and low (BDDCS/BCS 2/4) solubility groups.
• Utilized Receiver Operating Characteristic (ROC) curve analysis to determine statistically significant thresholds for MSol (>0.30 mg/mL) and MLogSM (>-3.05).
• Validated the classification method on an independent set of 108 orally administered drugs.

Main Results:

• NMEs with MLogSM > -3.05 or MSol > 0.30 mg/mL demonstrated an >= 85% probability of high solubility.
• NMEs with MLogSM <= -3.05 or MSol <= 0.30 mg/mL demonstrated an >= 85% probability of low solubility.
• The method achieved 85% classification accuracy when compared to BDDCS and correctly classified 81% (high) and 95% (low) of independent drug samples.

Conclusions:

• The developed solubility classification using MSol or MLogSM is a novel, rapid, and accurate approach.
• This method is independent of traditional dose number criteria, offering a valuable tool for NME development.
• The established thresholds provide reliable criteria for predicting drug solubility early in the discovery pipeline.