Risk Management in Early Discovery Medicinal Chemistry

Gurpreet Singh, Jayme L. Dahlin, Michael A. Walters

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

Drug discovery is inherently very risky. The management of these risks can enable the effective use of limited human and monetary resources. A careful attention to risk management in early discovery is especially important given that what happens in the early phases of a project may dictate the course of a research program for months or years. Risk management in early discovery starts with high-level managerial concerns: careful project selection, sufficient staffing and funding, and access to the appropriate instrumentation and tools. Herein we describe the operational elements of risk management that range from the very broad to the extremely specific. These elements have as their base an embedded culture of risk management that extends down to the experiment level, and project ownership in which all researchers anticipate risk, but are not paralyzed by it. In our model, on this base of culture stand the four pillars of early discovery risk management: right libraries, right assays, right series, and right structure–activity relationships. Appropriate attention to these considerations can decrease the risks inherent in early discovery medicinal chemistry, thereby potentially increasing the return on the investment of necessarily finite resources.

Original languageEnglish (US)
Title of host publicationMethods in Enzymology
EditorsCharles A. Lesburg
PublisherAcademic Press Inc.
Pages1-25
Number of pages25
ISBN (Print)9780128153833
DOIs
StatePublished - Jan 1 2018

Publication series

NameMethods in Enzymology
Volume610
ISSN (Print)0076-6879
ISSN (Electronic)1557-7988

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Inc.

Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

Keywords

  • Drug development
  • Drug discovery
  • High-throughput screening
  • Risk management
  • Risk mitigation
  • Structure–activity relationship

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