Following Nobel Prize-winning chemist David Baker’s recipe for cooking an antidote to cobra venom using artificial intelligence (AI) could be faster and more effective than currently available methods. The ingredients and steps can be found in a new study published by the University of Washington scientist in collaboration with the Technical University of Denmark. They are ready for the next steps in preclinical trials.

Many studies have linked the presence of specific bacteria to various diseases. But a general overgrowth of gut bacteria can be a symptom of different conditions, including colorectal cancer and inflammatory bowel disease.

An international consortium of thousands of scientists is creating the Human Cell Atlas, a three-dimensional map of all the cells in the body. The goal is to understand all the cells that make up human tissues, organs and systems, which will enable multiple medical applications. This collection of cell maps is openly available for navigation at single-cell resolution, identified through omics analyses that reveal the tridimensional distribution of each cell.

David Baker, Demis Hassabis and John Jumper share the 2024 Nobel Prize in Chemistry for their contributions to the science of protein structure. David Baker was awarded half the prize “for computational protein design,” according to the Royal Swedish Academy of Sciences. Hassabis and Jumper shared the other half “for protein structure prediction.”

Artificial intelligence recently roiled the regulatory world, but the U.S. Congress has yet to dive into the task of legislating on the concept. Barrett Tenbarge, general counsel for Sen. Bill Cassidy (R-La.) told an audience here in the nation’s capital that while the Senate is considering several legislative proposals, the desire to avoid legislation that will create as many problems as it solves suggest that legislative development “is a long-term process.”

As the average cost of new drug R&D continues to skyrocket, the perception around using artificial intelligence (AI) as a tool to boost drug discovery is changing. “Developing new AI-based drugs is a difficult task, not only for Korea but also for countries with leading AI technology,” Hyeyun Jung, principal researcher of Korea Health Industry Development Institute’s Center for Health Industry Policy, told the audience at the Bio Korea meeting on May 9. “But there is a change in perception; [namely that] applying AI to new drug development is not an option but a necessity.”

Deep learning algorithms have enabled the discovery of molecular structures of interest in biomedicine to design treatments against aggressive diseases such as idiopathic pulmonary fibrosis (IPF). Scientists at Insilico Medicine Inc. selected a target for IPF using artificial intelligence (AI), then designed an inhibitor to block it, and tested it in vitro, in vivo, and in clinical trials.

The U.S. Patent and Trademark Office (PTO) has released a draft version of patent examiner guidelines to address the increasing use of artificial intelligence (AI) in the inventive process, reflecting the standing U.S. position that AI cannot be an inventor.