Upcoming Webinar

Using Quantitative Systems Toxicology (QST): Improving the safety of drugs while reducing animal testing (July 2019)

Using Quantitative Systems Toxicology (QST):  Improving the safety of drugs while reducing animal testing

Presenter: Paul B. Watkins, M.D.

Director, Institute for Drug Safety Sciences, Schools of Pharmacy, Medicine, and Public Health, University of North Carolina – Chapel Hill


It is clear that traditional toxicity studies of new drug candidates performed in animals often fail to identify serious safety liabilities in humans. There have been recent efforts to use human cells (such as the “human on a chip”) and other relevant human tissue-based technologies to address this shortcoming. One such effort is the DILI-sim Initiative. This is a seven year old public-private partnership that has been supported by scientists from 16 of  the top 20 pharmaceutical companies, the Food and Drug Administration, and academia. The Initiative uses differential equations to recapitulate key processes whereby drugs can cause liver injury. The relevant properties of drugs and their metabolites are assessed in the laboratory in human tissue derived models. The data obtained is entered into the model and the likelihood of a toxic response in patients is predicted.  In addition to predicting toxicity in an average patient, simulated patient populations have been created by varying parameters in the model to reflect genetic and non-genetic variation. The Initiative has provided many novel insights into mechanisms underlying drug-induced liver injury and why only some patients may be particularly susceptible to this. The software produced (Dilisym®) has been licensed to FDA reviewers  and is increasingly employed in decision making within Pharma. The modeling results are also frequently referenced in regulatory submissions. The experience with the DILI-sim Initiative strongly supports an important role for QST modeling in assessing safety of new drug candidates while reducing the need for animal studies.