Computational Toxicology Services LLC specializes in supplying computer based quantitative structure-activity (QSAR) predictive toxicology screening of pharmaceuticals and the qualification of impurities in drug products. Computational toxicology is also used for the screening of indirect food additives. Computational Toxicology Services offers a cost effective solution for clients with toxicology screening needs that do not justify the investment in QSAR software licenses, database modules and trained staff necessary for computational toxicology screening of test substances.
Computational toxicology can efficiently identify, prioritize and eliminate compounds with unacceptable safety profiles early in the product development process. A wide range of toxicology endpoints including mutagenicity, genotoxicity and carcinogenicity are available for the following software that are used extensively by industry and regulatory agencies:
The Qualification of Impurities in Pharmaceuticals A major application of in silico (Q)SAR mutagenicity testing is for the qualification of impurities in pharmaceutical products. The requirements for the qualification of pharmaceutical impurities have been revised under the 2014 ICH M7 guideline*. This guidance recommends that bacterial mutagenicity should be assessed for the qualification of impurities using two (Q)SAR prediction methodologies, an expert rule-based and a statistical-based method. Derek-Nexus, Leadscope Expert and Toxtree are rule-based SAR software. Leadscope Model Applier and Sarah-Nexus are examples of statistical-based QSAR software that can be used to meet the ICH M7 qualification requirements.
*U. S. Food and Drug Administration: Center for Drug Evaluation and Research. International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH). M7 (2014): Assessment and Control of DNA Reactive (Mutagenic) Impurities in Pharmaceuticals to Limit Potential Carcinogenic Risk). http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Multidisciplinary/M7/M7 Step_4.pdf.
Sutter, A., Amberg, A., Boyer, S., Brigo, A., Contrera, J.F., Custer, L.L., Dobo, K.L., Gervais, V., Gloienke, S., van Gompel, J., Greene, N., Muster, W., Nicolette, J., Reddy, M., Thybaud, V., Vock, E., White, A.T., and Muller, L. Use of in silico systems and expert knowledge for structure-based assessment of potentially mutagenic impurities. Regul. Toxicol. Pharmacol. 67 (2013) 39-52.
Computational Toxicology Services LLC is based in Maryland suburbs of Washington D.C. and was established by Joseph F. Contrera, Ph.D. in 2008. Dr. Contrera was formerly director of the Informatics and Computational Safety Analysis Staff at FDA Center for Drug Evaluation and Research.
QSAR Testing Limitations Some classes of chemicals cannot be tested due to limitations of the software or training dataset. Inorganic chemicals (salts and metals), high molecular weight substances (>1200 Daltons), peptides, polysaccharides, proteins, organometallic chemicals and complex mixtures cannot be modeled. Compounds that are insufficiently represented in the software training datasets of statistical based software such as Leadscope, Sarah-Nexus or SciQSAR are classified as out of domain compounds and cannot be predicted.
Computational toxicology based estimates of toxicity are intended to be used as supplemental decision support information in combination with traditional toxicology testing as part of a weight of evidence approach to hazard and risk assessment.
