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Integration of Systems Toxicology into Drug Discovery

Systems Toxicology

Genomic Technology

  1. Mark Fielden

Published Online: 15 SEP 2011

DOI: 10.1002/9780470744307.gat210

General, Applied and Systems Toxicology

General, Applied and Systems Toxicology

How to Cite

Fielden, M. 2011. Integration of Systems Toxicology into Drug Discovery. General, Applied and Systems Toxicology. .

Author Information

  1. Amgen Inc., Comparative Biology and Safety Sciences, South San Francisco, CA, USA

Publication History

  1. Published Online: 15 SEP 2011

Abstract

Success in the pharmaceutical industry is plagued by high rates of late-stage attrition because of unanticipated pre-clinical and clinical toxicity. In order to improve success rates, it is necessary to consider potential on- and off-target-mediated toxicity at an earlier stage in product development to shift attrition upstream in the process. This will help to avoid resource-intensive development activities, such as pre-clinical toxicology and human clinical studies, on compounds that are ultimately destined to fail. Large-scale gene expression profiling technologies, such as toxicogenomics, have the potential to diagnose and predict certain safety liabilities using in vitro and in vivo models. When used appropriately in the early stages of lead optimization and pre-clinical drug testing, it has the potential to improve compound selection at an earlier stage of drug discovery and thus decrease the probability of late-stage attrition. A more thorough understanding of a drug's mechanism of action and toxicity is also expected to improve human risk assessment and help define appropriate screening strategies to avoid toxicophores in subsequent iterations of drug discovery. This chapter will focus on the application of systems toxicology using toxicogenomics in drug discovery for the early safety assessment of small molecule therapeutics.

Keywords:

  • discovery toxicology;
  • drug discovery;
  • in vitro;
  • in vivo;
  • lead optimization;
  • microarray;
  • toxicity prediction;
  • toxicogenomics