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Elsevier collaborates with Pending.AI for AI-driven chemistry retrosynthesis tool -

Elsevier, a global research publishing and information analytics provider, is collaborating with Pending.AI (PAI), a start-up focused on developing artificial intelligence (AI) solutions for drug discovery, to develop the predictive retrosynthesis tool based on deep learning to support innovation in synthetic and medicinal chemistry. The tool was initially developed via Elsevier's R&D Collaboration Network and is now being integrated into Elsevier's flagship chemistry solution, Reaxys, combining Reaxys' content with cutting-edge AI and machine learning technologies developed by PAI.

The Reaxys-PAI Predictive Retrosynthesis solution uses a model that incorporates deep neural networks trained on Reaxys data. The results are found using a Monte Carlo tree search approach to quickly discover promising candidate routes. Hundreds of thousands of reaction rules (>400,000) are algorithmically extracted from the Reaxys source data (>15 million single-step organic reactions), enabling it to be non-reliant on hand-encoded rules that are typically used in other solutions.

The tool has been tested rigorously by the world's leading pharmaceutical and chemical companies and has been demonstrated to provide scientifically robust, diverse and innovative synthetic route suggestions. It is a valuable tool that is easy and intuitive to use and supports the needs of the business and researchers by being a very good assistant and idea generator. The predictive retrosynthesis solution has been trained on both positive and negative reaction data and solves synthesis design questions for novel molecules with direct links to experimental reactions available in the most trusted chemistry solution Reaxys. The predictive model training and creation is fast, allowing it to ‘self-learn’ from the rapidly ever-growing chemistry knowledge. Reaxys-PAI Predictive Retrosynthesis can be further augmented by training on proprietary chemistry reaction data, including a customer's own reaction dataset and building block library.

This is a step in Elsevier Life Science's Chemistry solution strategy of building next-generation AI & machine learning enabled decision support tools that will help to bring drugs to market for patients most in need, help to find synthesis routes for novel chemical compounds that may be more environmentally friendly and help design scale-up processes which may be greener.

The Reaxys-PAI Predictive Retrosynthesis tool is now available as an add-on module for Reaxys customers.

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