A noninvasive treatment for “chemo brain”
Stimulating gamma brain waves may protect cancer patients from memory impairment and other cognitive effects of chemotherapy.
Stimulating gamma brain waves may protect cancer patients from memory impairment and other cognitive effects of chemotherapy.
Core-shell structures made of hydrogel could enable more efficient uptake in the body.
Thirteen new graduate student fellows will pursue exciting new paths of knowledge and discovery.
A biotech entrepreneur, Koehler will help faculty and students launch startups and bring new products to market through the MIT Deshpande Center for Technological Innovation.
A pilot-scale system, enabled by an $82 million award from the FDA, aims to accelerate the development and production of mRNA technologies.
“FrameDiff” is a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving gene therapy.
MIT-Novo Nordisk Artificial Intelligence Postdoctoral Fellows Program will support up to 10 postdocs annually over five years.
With full genetic control and visibility into neural activity and behavior, MIT scientists map out chemical’s role in behavior.
A collaborative research team from the MIT-Takeda Program combined physics and machine learning to characterize rough particle surfaces in pharmaceutical pills and powders.
MIT researchers built DiffDock, a model that may one day be able to find new drugs faster than traditional methods and reduce the potential for adverse side effects.
The program leverages MIT’s research expertise and Takeda’s industrial know-how for research in artificial intelligence and medicine.
Companies founded by MechE faculty and alumni solve a variety of health care challenges, from better drug delivery to robotic surgery.
Longtime MIT professor of neuroscience led research behind 200 patents, laying the groundwork for numerous medical products.
Danielle Li takes a close look at scientific practices and organizational decisions — and provides data about improving them.
A geometric deep-learning model is faster and more accurate than state-of-the-art computational models, reducing the chances and costs of drug trial failures.