The design-make-test cycle is critical to medicinal chemistry. The hypothesis driven science of drug design is fueled by ideation of a chemical structure followed by its synthesis and evaluation. Despite rapid improvements in the field, few drugs reach phase I and many more backed by considerable investment fail to strike the delicate balance of pharmacokinetic and pharmacodynamic properties needed for commercial approval. This problem of throughput can be lessened by making and testing molecules faster as well as selecting better molecules to make. Success can also be improved by augmenting our ability to make certain classes of molecules. Much as how high-throughput experimentation (HTE) has enabled efficient synthesis and biological evaluation, modern computing and enumeration can optimize chemical space sampling and improve structural hypotheses. We present a framework that leverages computational enumeration and 1,536 well ultrahigh-throughput experimentation (uHTE) to rapidly identify and invent transformations that have high utility in creating drug-like matter. In this paradigm, enumerative combinatorics is used to computationally study hypothetical transformations between building blocks in commercial databases, revealing key reactions that improve access to drug-like space. Simultaneously, the development of the chemical experimentation software phactor™ enables uHTE synthesis-to-biology workflows to be designed and rapidly executed. Several examples of using phactor™ to invent and test the scope of new reaction methodologies that were identified by an enumerative combinatorics search of chemical space are presented.

MEDI predoctoral fellowship award: Ideation and evaluation of key synthetic transformations using enumeration and ultrahigh throughput experimentation

Fall 2022 abstracts, posters, and presentations will launch in mid-September.

ACS Fall 2022

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