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QSAR Models at the US FDA/NCTR

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In Silico Methods for Predicting Drug Toxicity

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1425))

Abstract

Quantitative structure–activity relationship (QSAR) has been used in the scientific research community for many decades and applied to drug discovery and development in the industry. QSAR technologies are advancing fast and attracting possible applications in regulatory science. To facilitate the development of reliable QSAR models, the FDA had invested a lot of efforts in constructing chemical databases with a variety of efficacy and safety endpoint data, as well as in the development of computational algorithms. In this chapter, we briefly describe some of the often used databases developed at the FDA such as EDKB (Endocrine Disruptor Knowledge Base), EADB (Estrogenic Activity Database), LTKB (Liver Toxicity Knowledge Base), and CERES (Chemical Evaluation and Risk Estimation System) and the technologies adopted by the agency such as Mold2 program for calculation of a large and diverse set of molecular descriptors and decision forest algorithm for QSAR model development. We also summarize some QSAR models that have been developed for safety evaluation of the FDA-regulated products.

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Declaration

The views presented in this article do not necessarily reflect those of the US Food and Drug Administration.

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Authors and Affiliations

  1. Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, AR, 72079, USA

    Huixiao Hong, Minjun Chen, Hui Wen Ng & Weida Tong

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  1. Huixiao Hong
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  2. Minjun Chen
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  3. Hui Wen Ng
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  4. Weida Tong
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Correspondence to Huixiao Hong .

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Editors and Affiliations

  1. Mario Negri Inst for Pharm Rsrch, IRCCS, Milan, Italy

    Emilio Benfenati

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Hong, H., Chen, M., Ng, H.W., Tong, W. (2016). QSAR Models at the US FDA/NCTR. In: Benfenati, E. (eds) In Silico Methods for Predicting Drug Toxicity. Methods in Molecular Biology, vol 1425. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3609-0_18

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  • DOI: https://doi.org/10.1007/978-1-4939-3609-0_18

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