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Author: Alex Ouyang

MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases

More than 300 people across academia and industry spilled into an auditorium to attend a BoltzGen seminar on Thursday, Oct. 30, hosted by the Abdul Latif Jameel Clinic for Machine Learning in Health (MIT Jameel Clinic). Headlining the event was MIT PhD student and BoltzGen’s first author Hannes Stärk, who had announced BoltzGen just a few days prior. Learn more

2025’s Fiercest Women in Life Sciences

The life sciences mission of Najat Khan, Ph.D., was forged in hospital hallways.
Her parents, a trauma surgeon and a gynecologist-turned-radiologist, “didn't believe in babysitters,” she joked in an interview. The extensive time she therefore spent in hospitals throughout her childhood showed Khan the life-changing impact of innovative medicines and set her on the path to the C-suites of Johnson & Johnson and Recursion Pharmaceuticals. Learn more

Marketwatch25: She survived breast cancer. Now her AI tool could help you skip annual mammograms.

As an MIT computer-science professor, Regina Barzilay was used to living on the bleeding edge of innovation, teaching computers to understand words in the nascent field of natural language processing. But when she was diagnosed with breast cancer in 2014, she was thrust into a different and, as she describes it, “really backwards” technological world. Learn more

AI steps in to detect the world’s deadliest infectious disease

As a professor and computer scientist at MIT, Regina Barzilay has spent years building AI models to detect breast cancer and lung cancer. Then, when a hospital in Sri Lanka told her it couldn't afford to buy off-the-shelf AI models for TB screenings, she agreed to build one for them.

As she got to work this past year, she says, she immediately understood why TB is at the vanguard of the global health challenges with AI solutions.

"You can see TB. TB is visual. You have an x-ray. You have a label which says whether they have it or not — and you just train the model," Barzilay says, adding that it only took her a few months and less than $50,000 to make her model. "It's straightforward, very cheap, very fast to develop." Learn more

AI maps how a new antibiotic targets gut bacteria

“This discovery speaks to a central challenge in antibiotic development,” says Jon Stokes, senior author of a new paper on the work, assistant professor of biochemistry and biomedical sciences at McMaster, and research affiliate at MIT’s Abdul Latif Jameel Clinic for Machine Learning in Health. “The problem isn’t finding molecules that kill bacteria in a dish — we’ve been able to do that for a long time. A major hurdle is figuring out what those molecules actually do inside bacteria. Without that detailed understanding, you can’t develop these early-stage antibiotics into safe and effective therapies for patients.” Learn more
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