Artificial intelligence (AI)-based models developed by a team of international researchers were able to identify ovarian cancer in ultrasound images more accurately than humans. Results from a study published in Nature Medicine showed that the AI models achieved an accuracy rate of 86.3%, compared to 82.6% for the experts and 77.7% for the non-expert examiners.

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.

The development of new machine learning tools like Alphafold and Rfdiffusion has allowed scientists to predict the structure of proteins and design them for drug discovery purposes, among other uses. Now, scientists at the Arc Institute have created Evo, an AI model that generates DNA sequences and estimates their interaction with other molecules at single-nucleotide resolution, scalable to an entire genome.

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. A study counting gut microbiome proposes that microbial load, rather than the disease, could explain the presence of certain pathogens.

Backed by AI technology, Aigen Sciences Inc. raised ₩12 billion (US$8.8 million) in a series A financing round to further advance its cancer and rare disease drug pipelines. Aigen said Oct. 16 that the series A round was joined by existing investors Partners Investment, Quad Investment Management and Medytox Venture Investment, as well new investors Premier Partners, K2 Investment Partners and Scale Up Partners.

Rakovina Therapeutics Inc. has obtained a short-list of recommended drug candidates from an initial artificial intelligence (AI) screening effort using the Deep Docking AI platform under a collaboration with the University of British Columbia.

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.”

Tonix Pharmaceuticals Holding Corp. has entered into an artificial Intelligence and machine learning research collaboration with X-Chem Inc. to accelerate development of Tonix’s oral broad-spectrum antivirals for medical countermeasures.

It’s hard to know where to start in describing the biopharma applications of the 2024 Nobel Prize in Physics. It was awarded to John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks.”