Abstract

Solubility and cellular permeability are two of the most important biopharmaceutical properties impacting the successful development of drug substances. Given the importance of these properties, most pharmaceutical companies have invested in medium to high throughput technologies for early evaluation of these characteristics in the drug discovery funnel in order to select, prioritize or eliminate compounds with unfavorable solubility and/or permeability. However, these technologies require physical samples of the substances to be tested. In order to facilitate the early stages of drug discovery, such as defining compound collection composition, designing combinatorial libraries, and in hit expansion or lead optimization, models for predicting aqueous solubility and permeability in the absence of physical sample are increasingly being employed. In this overview, we will discuss solubility and permeability experimental and computational methods separately and then interrelate them in physiologically relevant models for predicting in vivo performance.

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