On the use of real-world datasets for reaction yield prediction.

The lack of publicly available, large, and unbiased datasets is a key bottleneck for the application of machine learning (ML) methods in synthetic chemistry. Data from electronic laboratory notebooks (ELNs) could provide less biased, large datasets, but no such datasets have been made publicly available. The first real-world dataset from the ELNs of a large pharmaceutical company is disclosed and its relationship to high-throughput experimentation (HTE) datasets is described.

Strategic elements in computer-assisted retrosynthesis: A case study of the pupukeanane natural products.

Computer-assisted synthesis planning represents a growing area of research, especially for complex molecule synthesis. Here, we present a case study involving the pupukeanane natural products, which are complex, marine-derived, natural products with unique tricyclic scaffolds. Proposed routes to members of each skeletal class informed by pathways generated using the program Synthia are compared to previous syntheses of these molecules.