Reaxys resources

Factsheets

• Reaxys for pharma

• Reaxys target and bioactivity

• Iktos Reaxys Predictive Retrosynthesis

• Pending.AI Reaxys Predictive Retrosynthesis

• Reaxys for academic institutions

Guides and tutorials

• Reaxys Reference Guide (2025 edition)

• Predictive Retrosynthesis Guide – Pending.AI

• Predictive Retrosynthesis Guide – Iktos

• See video tutorials

Webinars

Big data in chemistry webinars

• A universal approach to reaction informatics Professor Lee Cronin, Center for Digital Chemistry, University of Glasgow

• Understanding the history of chemical space through big data Professor Guillermo Restrepo, Leipzig University

• Reaction condition prediction using Reaxys: from raw data to best-in-class model Asst Professor Timur Madzhidov, Organic and Medicinal Chemistry, Kazan Federal University

• Charting the chemical reaction space for DNA-encoded library design Professor Andreas Brunschweiger, Chemistry and Chemical Biology, TU Dortmund

Reaxys Predictive Retrosynthesis webinars

• Reaxys Predictive Retrosynthesis — speed matters Manish Uniyal, Drs. Mandar Bodas and Abhinav Kumar, Elsevier

• AI-enabled predictive retrosynthesis tool to advance drug discovery Drs. Abhinav Kumar and Nilesh Rane, Elsevier

• Next generation synthesis planning using AI for chemists Drs. Mandar Bodas, Abhinav Kumar and Juergen Swienty-Busch, Elsevier

Reaxys patents and patent expansion webinars

• Reaxys patent expansion: uncovering chemical compounds hidden in patents Vinod Honmute, Head of KM, IP law and BI at Aarti Industries, Dr. Nilesh Rane, Elsevier

• Reaxys patent expansion 2021: an improved competitive intelligence Jen Teske and Robert Niebergall, Elsevier