The Center for Alternatives to Animal Testing is an academic center affiliated with the Division of Toxicological Sciences in the Department of Environmental Health Sciences of the Johns Hopkins University Bloomberg School of Public Health.

 

Johns Hopkins School of Public Health

Abstract for TestSmart--Pharmaceuticals: An Efficient and Humane Approach to Predictors of Potential Toxic Effects of Drugs

Computational Toxicology And Knowledge Bases at FDA/CDER

Joseph F. Contrera
Center for Drug Evaluation and Research (CDER), US Food and Drug Administration

Ready access to scientific information is critical to support safety related regulatory decisions especially in situations where available experimental information are inadequate or unavailable, and to identify information gaps and prioritize research. CDER files are a unique repository of the results of clinical and non-clinical toxicology studies. With the major advances in computer and information technology this unique scientific resource can be more effectively used to improve the scientific basis of regulatory decisions and product development. A current challenge is developing better means to identify useful relationships and insights from large sets of data.

An electronic toxicology knowledge base and computational toxicology initiative is underway in the FDA Center for Drug Evaluation and Research (CDER), Office of Pharmaceutical Sciences. The objectives of this effort are to provide scientific decision support information for regulatory scientists to facilitate the review process, improve consistency and uniformity and to provide the Agency with a scientific resource for regulatory and applied research. An essential component of this scientific knowledge base is a comprehensive electronic relational database of FDA regulated substances that is linked to chemical structure. The use of a digital representation of chemical structure (ISIS molfile) as the primary substance identification field makes possible the identification of clusters of substances having similar chemical structure/substructural features and similar pharmacological or toxicological activities. With this capability, informatic and computational toxicology strategies can then be applied to identify and prioritize compounds by their chemical structure related toxicological profiles. Under a cooperative research and development agreement (CRADA), we modified and enhanced the capability of MULTICASE, a computational toxicology software, to predict the carcinogenic potential of molecules based on chemical structure. Computational toxicology has potential regulatory and drug development applications that can ultimately benefit the public health and refine and reduce the use of animals in the assessment of product safety.