Standard Article

Implementing Systems Toxicology in Drug Development for Regulatory Decision Making

Systems Toxicology

Regulatory Applications

  1. Joseph F. Sina,
  2. Frank D. Sistare

Published Online: 15 SEP 2011

DOI: 10.1002/9780470744307.gat248

General, Applied and Systems Toxicology

General, Applied and Systems Toxicology

How to Cite

Sina, J. F. and Sistare, F. D. 2011. Implementing Systems Toxicology in Drug Development for Regulatory Decision Making. General, Applied and Systems Toxicology. .

Author Information

  1. Safety Assessment, Merck Research Laboratories, West Point, PA, USA

Publication History

  1. Published Online: 15 SEP 2011


The concept of integrating molecular and biochemical data from new technologies with more traditional endpoints to develop a more complete understanding of risks and benefits in drug development has gained wide acceptance as a reasonable way to advance human health. However, actual implementation of this systems approach is not straightforward. While technology keeps advancing, our ability to accurately interpret the complexity of human biology has not kept pace. Indeed, sometimes the case seems to be one of the deeper we investigate, the more we realize what we do not understand. Additionally, in developing ethical pharmaceuticals, a major issue is establishing the necessary level of confidence to extrapolate from a series of endpoint measurements to accurately predict beneficial and/or potentially adverse responses in the diverse population of patients. The evidentiary standard for acceptance of new models and biomarkers in clinical practice is necessarily high, although the concept of “fit-for-purpose” may help expedite the application of new knowledge in specific clinical situations. This chapter will present a view of both the progress and hurdles to applying systems toxicology to drug development in a regulated environment.


  • systems toxicology;
  • drug development;
  • biomarkers;
  • clinical translation;
  • pre-clinical;
  • pathways;
  • review;
  • genomics;
  • metabolomics;
  • proteomics