Document Embedding Centroids: New and Versatile Semantic Descriptors for Compounds

Abstract

We describe a novel algorithm for generating representational embeddings of chemical matter based on the biomedical literature/semantic contexts in which they occur. We then demonstrate that these chemical descriptors have utility in nearest neighbor retrieval for early drug discovery tasks such as mechanism of action and target activity predictions.