Automated high throughput pK and distribution coefficient measurements of pharmaceutical compounds for the SAMPL8 blind prediction challenge.

The goal of the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) challenge is to improve the accuracy of current computational models to estimate free energy of binding, deprotonation, distribution and other associated physical properties that are useful for the design of new pharmaceutical products. New experimental datasets of physicochemical properties provide opportunities for prospective evaluation of computational prediction methods. Here, aqueous pK and a range of bi-phasic logD values for a variety of pharmaceutical compounds were determined through a streamlined automated process to be utilized in the SAMPL8 physical property challenge.

Understanding the Role of Sodium Lauryl Sulfate on the Biorelevant Solubility of a Combination of Poorly Water-Soluble Drugs Using High Throughput Experimentation and Mechanistic Absorption Modeling.

This study investigates the influence of surfactant sodium lauryl sulfate (SLS) on the solubility of poorly-water soluble drug substances, model Compound X and Compound Y, used in a fixed dose combination oral solid dosage form. To determine the impact of SLS concentration on the solubility of compounds X and Y, we experimentally determined the critical micelle concentration (CMC) of SLS in water, simulated gastric fluid (SGF), and fed state simulated intestinal fluid (FeSSIF) in the presence of Compound X and Compound Y using UV/Visible spectrophotometry at 25°C. The aggregation of SLS was characterized by calculating the standard Gibbs free energy of micellization in all the media investigated.