Toxicological and clinical computational analysis and the US FDA/CDER

Area of Science:

• Computational Toxicology
• Toxicological Data Analysis
• Predictive Modeling

Background:

• Introduction to computational toxicology for non-experts.
• Overview of the U.S. Food and Drug Administration (FDA), Center for Drug Evaluation and Research's (CDER) work.
• Importance of toxicological and clinical data compilation.

Purpose of the Study:

• To familiarize readers with computational toxicology terminology and principles.
• To report on the FDA's advancements in creating predictive toxicology models.
• To speculate on the future of computational toxicology at the FDA.

Main Methods:

• Compilation of toxicological and clinical databases.
• Development of predictive toxicology models based on compiled data.
• Commercialization of FDA-developed models through software collaborators.

Main Results:

• Successful development of multiple predictive toxicology models.
• Availability of these models commercially.
• Demonstrated progress by the FDA in leveraging data for predictive toxicology.

Conclusions:

• Computational toxicology offers valuable tools for drug evaluation.
• The FDA has made significant strides in this field.
• Future potential for computational toxicology, particularly within the FDA, is substantial.