Recommendations for chemists: a case study.

Large pharmaceutical companies have a wealth of reaction and chemical structure data, but face a new problem: analyzing that corpus to yield project insights and future directions. One straight-forward approach would be to have a recommendation system to match drug structures with similar research endeavors across geographically- or organizationally-separated groups. We developed and deployed Chem Recommender, a system that suggests similar, related work to experiments that chemists have recently started. The goal of the system is to accelerate the drug discovery process by ensuring that chemists are aware of each other's work. To date, we have sent more than 8500 recommendations to over 800 medicinal chemists in our organization. The results have been positive, with several chemists reporting that the recommendations have aided their molecular syntheses.