AI-driven synthetic chemistry platform for drug discovery 

AI-driven synthetic chemistry platform for drug discovery 

Elsevier, a global leader in information and data analytics, has signed a multi-year agreement with Iktos, a company specialising in Artificial Intelligence for new drug discovery. The partnership will strengthen Elsevier’s flagship chemistry solution, Reaxys, by combining the company’s high-quality chemistry data with synthetic planning AI technologies developed by Iktos to accelerate chemistry research for pharmaceutical companies.  

Mirit Eldor, Managing Director, Life Sciences Solutions, Elsevier said: “Our mission is to support research and development (R&D) organisations in fuelling innovation and drug discovery with industry-leading predictive algorithms trained on our high-quality data. We are delighted to partner with Iktos to bring the valued industry insights that Reaxys offers powered by Artificial Intelligence, which will help re-shape the landscape of small molecule discovery.” 

The partnership aims to support R&D organisations to critically decrease the time required to complete Design-Make-Test-Analyse cycles of small molecules, thus reducing the length and cost of early-stage drug discovery. New predictive models will be launched to support use cases including retrosynthesis, synthetic accessibility and other reaction-based analyses. The new tools will be delivered via Reaxys’ user-friendly interface and Application Programming Interface (APIs), accelerating research for synthetic, medicinal, computational and process chemistry teams at pharmaceutical, agro-chemical and contract research organisations.  

Yann Gaston-Mathé, CEO, Iktos said: “Data is the foundation of AI, and we are very excited to partner with Elsevier. We will combine the strength of Reaxys, a chemistry reaction database with unmatched volume, diversity and quality, with Iktos’ leading edge retrosynthesis AI technology. We are committed to making our technology available to R&D organisations around the world to maximise the impact of AI on the productivity of drug discovery.” 

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