Effective synthetic organic chemistry is based on several principal skills: i) envisioning all feasible synthetic steps and selecting the most suited ii) finding applicable procedures to run the experiments iii) mastering instruments and equipment iv) analysing and drawing the right conclusions from reaction outcomes. The complexity of such tasks explains why it takes several years to educate and enable chemists in this discipline successfully. Even then, non-yielding synthesis steps are part of the reasons why the amount of time to be invested is considerable higher than often expected - particularly in cases of complex molecules.<br/>Reaxys is a software tool that contains well curated FAIR (Findable, Accessible, Interoperable, Reusable) scientific information and teaches chemists how to find and apply the right literature for chemical transformations, identify analytical information and most importantly educates, how to develop retrosynthesis schemes swiftly. The possibilities to evaluate and compare different routes, yields and conditions to molecules are exceptional and allow educators to illustrate retrosynthesis in organic chemistry classes on a day to day basis. Furthermore, computer-aided retrosynthesis tools, which can predict reactions to novel molecules correctly, are part of Reaxys. The ‘deep learning’, neuronal networks produce schemes of sequences of reactions to the desired compounds. This novel AI tool has processed nearly every reaction ever published (&gt; 15 million) and has the potential to transform the way organic chemists work in the future. In an assessment, various synthesis routes generated were tested in a double-blinded trial with 45 organic chemists from two institutes in China and Germany and the routes have proven to be scientifically sound and robust. This unique approach to retrosynthesis will lead to an increase of the success rate in synthetic organic chemistry and should have an enormous benefit in terms of discovering sustainable chemical solutions and minimizing expenditure.

Predicting reaction sequences: Deep neural networks and reaxys data bases

ACS Fall 2020 Virtual Meeting

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.