A potential new Alzheimer’s drug represses the harmful inflammatory response of the brain’s immune cells, reducing disease pathology, preserving neurons, and improving cognition in preclinical tests.

This AI system only needs a small amount of data to predict molecular properties, which could speed up drug discovery and material development.

By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.

The machine-learning algorithm identified a compound that kills Acinetobacter baumannii, a bacterium that lurks in many hospital settings.

Despite technological advancements, many challenges remain in getting a drug from lab to pharmacy shelf. Reframing what is a “medicine” could expand treatment options for researchers and patients.

A new study maps the genes and cellular pathways that contribute to exercise-induced weight loss.

A machine-learning method finds patterns of health decline in ALS, informing future clinical trial designs and mechanism discovery. The technique also extends to Alzheimer’s and Parkinson’s.

With the dual threats of antibiotic resistance and emerging pandemics, finding new drugs becomes even more urgent. A trove of medicines may be lying under our nose.