The private-public Accelerating Therapeutic Opportunities in Medicine (ATOM) consortium is showing “significant” progress in demonstrating that HPC and M) tools can speed up the drug discovery process, said Jim Brase, ATOM co-lead and LLNL’s deputy associate director for data science. The consortium currently boasts more than a dozen member organizations, including national laboratories, private industry, and universities. ATOM sponsored Brase’s May 18 webinar, during which he discussed ATOM’s approach to multiparameter molecular design—an ML-backed generative loop that predicts properties of proposed drug molecules; screens them virtually for safety, pharmacokinetics, manufacturability, and efficacy; optimizes the designs; and uses computational models and experimental feedback from the synthesized compounds to improve the models. In addition to providing an overview of ATOM and its accomplishments to date, Brase also presented the technology used in the drug design loop, including the ATOM Modeling PipeLine (AMPL) framework, which he said has proven useful for integrating multiple data sets and training large populations of models. Read more at LLNL News.