Agrochemical In Silico Predictive Toxicology Evaluations

Agrochemical In Silico Predictive Toxicology Evaluations

Agrochemical toxicity assessment is an important step in the development of agrochemicals. In the last few years, in silico toxicity prediction or computational toxicology has been growing rapidly. The application of advanced computational modeling in in silico assessments to predict the potential toxicity of agrochemical actives has attracted a lot of attention. As scientific knowledge and information on active substances grows, the reliability and acceptance of non-animal method is increasing. In addition, in in silico modeling, toxicity predictions can be delivered quickly without additional animal testing. BOC Sciences has introduced a wide range of software available for toxicity prediction of different agrochemical products, capable of providing reliable and accurate results for different toxicological endpoints.

Figure 1. In silico toxicology tools, steps to generate prediction models, and categories of prediction models. (Raies, A. B.; Bajic, V. B. 2016)

Advantages of In Silico Toxicity Prediction

• Cost and labor have been significantly reduced
• Avoidance of experiments with the application of animals
• Enhance the usefulness for bioactive substance development studies

In Silico Toxicity Evaluations for Agrochemicals

• We place special emphasis on advanced software based on quantitative structure-activity relationships studies, expert systems and machine learning methods.
• BOC Sciences has introduced a comprehensive set of QSAR modeling tools for delivering a reliable prediction for any endpoint you need for your agrochemicals. Both expert rule-based systems and statistical-based models are available to enhance the confidence of endpoint predictions.
• We have developed a team of scientists who have deep understanding of the chemistry, toxicology and statistical basis behind QSAR modeling to provide compelling in silico predictions for your agrochemicals.

Figure 2. 2D scatter plots of molecular descriptors and toxicity levels. (Raies, A. B.; Bajic, V. B. 2016)

Features of Our Services

Dedicated Team

• A dedicated team of computational biologists, statisticians, chemists, toxicologists and regulatory experts ensure robust in silico toxicology predictions for your agrochemical products.

Advanced Tools

• BOC Sciences supports a comprehensive set of computational modeling tools that use expert rule-based and statistical-based approaches to deliver the most reliable predictions results.

Integrated Technology

• Aiming to optimize your research spend while maintaining a compelling argument to regulatory agencies, our in silico predictions are integrated into a broader range of testing methods for your active substance.

Figure 3. SAR landscapes. (Raies, A. B.; Bajic, V. B. 2016)

BOC Sciences Advantages

• Highly specialized technical and analytical services for the worldwide registration and regulatory compliance of agrochemicals
• Robust analytical testing programs that span from research and product development through the production process to final product
• Relies on broad industrial experience, ensuring that all of our work meets the high standards expected by our clients
• Our regulatory experts, toxicology consultants, scientists and inspectors will ensure that you receive maximum levels of guidance, testing and inspection you need.

Reference

• Raies, A. B.; Bajic, V. B. In silico toxicology: computational methods for the prediction of chemical toxicity. Wiley Interdisciplinary Reviews Computational Molecular Science. 2016. 6(2): 147-172.