Establishment of quantitative retention-activity model by optimized microemulsion liquid chromatography

Area of Science:

• Analytical Chemistry
• Pharmacokinetics
• Drug Discovery

Background:

• Effective permeability is crucial for assessing drug bioavailability.
• Current methods for measuring permeability are often expensive and time-consuming.
• There is a need for efficient, high-throughput methods in drug development.

Purpose of the Study:

• To develop a novel, cost-effective microemulsion liquid chromatography (MELC) method for determining drug effective permeability.
• To establish quantitative retention-activity relationships (QRA R) for optimizing MELC.
• To validate MELC as an alternative to the parallel artificial membrane permeability assay (PAMPA).

Main Methods:

• Optimization of MELC using parallel artificial membrane permeability assays (PAMPA) to establish QRA R.
• Development of predictive models using support vector machine (SVM) and back-propagation neural networks (BPNN).
• Validation of the MELC method by comparing experimental and predicted permeability values.

Main Results:

• An optimal MELC system was identified using a specific mobile phase composition.
• QRA R models demonstrated improved prediction accuracy for drug permeability.
• A strong correlation was observed between experimental and predicted values, validating the model's performance.

Conclusions:

• Microemulsion liquid chromatography provides a high-throughput and potentially more economical approach for permeability assessment.
• MELC can effectively simulate biological processes and serve as an alternative to PAMPA.
• This method aids in the optimization and prediction of drug candidate bioavailability.