Over the past decade, the landscape of molecular synthesis has gained major impetus by
the introduction of late-stage functionalization (LSF) methodologies. C–H functionalization …

Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …

Prediction of chemical bioactivity and physical properties has been one of the most
important applications of statistical and more recently, machine learning and artificial …

Discovering new reactions, optimizing their performance, and extending the synthetically
accessible chemical space are critical drivers for major technological advances and more …

Organic synthesis is one of the key stumbling blocks in medicinal chemistry. A necessary yet
unsolved step in planning synthesis is solving the forward problem: Given reactants and …

We present a supervised learning approach to predict the products of organic reactions
given their reactants, reagents, and solvent (s). The prediction task is factored into two …

The key objectives of medicinal chemistry are to efficiently design and synthesize bioactive
compounds that have the potential to become safe and efficacious drugs. Most medicinal …

Conspectus Computer-aided synthesis planning (CASP) is focused on the goal of
accelerating the process by which chemists decide how to synthesize small molecule …

Reaction condition recommendation is an essential element for the realization of computer-
assisted synthetic planning. Accurate suggestions of reaction conditions are required for …

Artificial Intelligence (AI) plays a pivotal role in drug discovery. In particular artificial neural
networks such as deep neural networks or recurrent networks drive this area. Numerous …