Starting with a single frame in a simulation, a new system uses generative AI to emulate the dynamics of molecules, connecting static molecular structures and developing blurry pictures into videos.
With models like AlphaFold3 limited to academic research, the team built an equivalent alternative, to encourage innovation more broadly.
Novel method to scale phenotypic drug screening drastically reduces the number of input samples, costs, and labor required to execute a screen.
Inspired by traditional medicine, 17-year-old Tomás Orellana is on a mission to identify plants that can help treat students’ health issues.
MIT researchers speed up a novel AI-based estimator for medication manufacturing by 60 times.
Hanna Adeyema and Carolina Haass-Koffler discuss the substance use disorder crisis and the future of innovation in the field.
Large multi-ring-containing molecules known as oligocyclotryptamines have never been produced in the lab until now.
The program focused on AI in health care, drawing on Takeda’s R&D experience in drug development and MIT’s deep expertise in AI.
The SPARROW algorithm automatically identifies the best molecules to test as potential new medicines, given the vast number of factors affecting each choice.
Co-hosted by the McGovern Institute, MIT Open Learning, and others, the symposium stressed emerging technologies in advancing understanding of mental health and neurological conditions.
Twelve finalists participated in initiative and 2023-24 MIT-Royalty Pharma Prize Competition, designed to support female biotech pioneers.
New research addresses a gap in understanding how ketamine’s impact on individual neurons leads to pervasive and profound changes in brain network function.
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.