Frontiers in Medicinal Chemistry

Volume: 1

Indexed in: Scopus, EMBASE, Chemical Abstracts, EBSCO, Ulrich's Periodicals Directory.

Frontiers in Medicinal Chemistry is a book series devoted to the review of areas of important topical interest to medicinal chemists and others in allied disciplines. Frontiers in Medicinal Chemistry ...
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Compound Optimization in Early and Late Phase Drug Discovery: Acceptable Pharmacokinetic Properties Utilizing Combined Physicochemical, In Vitro and In Vivo Screens

Pp. 607-618 (12)

Gary W. Caldwell


New chemical entities (NCEs) are abandoned in development primarily because of insufficient efficacy, safety issues, and for economic reasons. Since efficacy and safety deficiencies are related in part to pharmacokinetics (PK), uncovering PK defects as early in drug discovery as possible would be highly valuable in reducing NCE failures in preclinical and clinical development. In this review, a strategy is put forth to integrate drug metabolism/pharmacokinetics and toxicology functions into drug discovery. Compound optimization in early and late phase drug discovery is covered emphasizing physicochemical properties, in vitro absorption, metabolism, and in vivo animal PK methodologies. The present study also illustrates the idea of sorting oral bioavailability data into high/intermediate/low categories based on combining high/low rank-ordered information from physicochemical properties and in vitro absorption, metabolism, and serum binding assays. It is shown that by combining the results from solubility, stability, absorption and metabolism assays the high/intermediate/low human oral bioavailability for a series of b- blockers can be approximately predicted. This method has a high sample throughput and should be useful in rank-ordering the predicted oral bioavailability of large collections of compounds at the lead optimization step of drug discovery. These results are useful for selecting compounds for future in vitro-in vivo correlation modeling or in vivo animal testing. This type of approach will improve the decision making process of compound selection in drug discovery.


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