FDA/CDER’s Chemical Informatics Program over the past 15 years has collected data on thousands of proprietary and non-proprietary chemicals (drugs, drug impurities, and other substances) through its regulatory research projects and internal Computational Toxicology Consultation Service. The data is used to develop and validate quantitative structure-activity relationship ((Q)SAR) models for a range of toxicological endpoints of regulatory significance. As such, CDER reviewers from any office can submit requests for (Q)SAR evaluation using these models or request chemical informatics-based analyses to support the evaluation of chemicals of unknown toxicity. To track the requests, an internal repository of chemical structures, each with a unique identifier, has been established to enable the organization and use of these data—the CDER<i> Chemical Dictionary</i>. To date over 30,000 chemicals have been registered, and the number grows daily. The source of the data includes both new and generic drug applications, external databases, and the published literature. Since the data is obtained from various sources within and outside of CDER, it is common to encounter the same chemical drawn several different ways and assigned unsystematic names or identifiers. Furthermore, we may also receive multiple consultation requests for the same structure from different parts of the organization. To address these challenges and reduce redundancy, we have developed an internal workflow incorporating the Chemical Dictionary to log all incoming structures and consultations, standardize the representation of chemical structures, and then link the records to facilitate rapid cross-checking as new data comes in. This presentation will discuss the types of chemicals submitted to the Chemical Informatics Program, what information is stored, how the chemicals are standardized, and how this information is used to support regulatory decisions.

FDA/CDER Chemical Informatics Program’s Chemical Dictionary

254th National Meeting (2017)

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