In Silico Toxicity Assessments - (Q)SAR

Risk Assessment of Arsenic - Case study

Predict the potential toxicity of substances, including metabolites and impurities

Exponent has expertise in a variety of methods for in silico toxicity evaluations as well as toxicologists who can evaluate the implications of (Q)SAR outcomes.

When you need to understand the toxicity of substances with no data, how does Exponent provide insights at every stage of your product lifecycle?

In silico toxicology, including (quantitative) structure-activity relationships ((Q)SAR) and read-across, can be useful at every stage of active substance development and as a part of product lifecycle management for substances under review. During the research and development phase, high-throughput screening using various in silico tools enables the relative toxicity of a large series of substances to be rapidly evaluated. The least toxic substances can be prioritized for further development, while substances with potential toxicological concern are identified early in development, informing the correct testing to be performed to evaluate the accuracy of the prediction.

During product lifecycle management, in silico toxicity predictions can be used to assess metabolites and impurities during active substance review. (Q)SAR and read-across are required under some regulatory guidelines. For pharmaceuticals, the ICH M7 guideline (Assessment and control of DNA reactive (mutagenic) impurities in pharmaceuticals to limit potential carcinogenic risk M7(R1)) describes using an in silico approach for the mutagenicity assessment of impurities. For the Plant Protection Products Regulations' residue definition (European Food Safety Authority guidance on the establishment of the residue definition for dietary risk assessment) and impurities (guidance document on the assessment of the equivalence of technical materials of substances regulated under regulation (EC) No. 1107/2009), guidance documents allow the use of in silico toxicity predictions to replace toxicity testing. The main endpoint of interest for these guidelines is genotoxicity, for which very accurate predictions of greater than 85% accuracy can be made using a combination of (Q)SAR and read-across techniques.

Performing in silico predictions at any stage of development can provide fast results that are more cost-effective than traditional toxicity testing methods and do not require the use of animals. Furthermore, in silico predictions allow substances that cannot easily be synthesized and/or isolated (e.g., metabolites and impurities) to be evaluated.

At Exponent, we have expertise in the use and interpretation of a variety of in silico toxicity tools. These include Derek Nexus, Leadscope, OECD QSAR Toolbox, TEST, VEGA, ToxTree, ECOSAR, and EPISUITE. In addition, we have complementary expertise in genotoxicity analysis.

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