In recent years there has been tremendous corporate and consumer interest in moving towards the commercialization of more sustainable products. Understanding the toxicity of products and their raw materials is a crucial for chemical hazard and risk assessment. Unfortunately, there is not enough trustworthy and comprehensive toxicity data that can help in avoiding toxic chemicals, understanding the risks involved in exposure to complex mixture of chemicals within laboratories, to consumers, and through toxic waste generated. Scientists in academia and industry that are responsible for product development processes usually not trained or well-equipped to make objective assessments of chemicals.<br/><br/>There is, therefore, an urgent need for solutions that offer trusted, comprehensive, easily obtained and understood environmental, safety and health hazard information. This presentation will highlight a self-learning software platform that provides comprehensive chemical and toxicological information of over 90 million chemicals and a real-time hazard evaluation for new drug-targets or proprietary chemicals. It will describe how careful and constant data-curation and utilization of sophisticated read-across and deep-learning-neural-networks technologies can be used to achieve high accuracy of prediction not achieved in the past. Use of this platform will enable R&D scientists to make better decisions during product design and development.

Comprehensive toxicity information of every chemical for better R&D decisions

2019 Fall National Meeting

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