Around Needham, Anne Carpenter may be recognized with a wave by her neighbors. Professionally, though, the Ph.D. biologist and computational scientist has been receiving much wider recognition — honors and accolades by the handful. Last year, she was selected as one of 50 outstanding scientists by Cell Press, the scientific journal publisher. Last week, she was on the dais as the consumer publication STAT held its celebration of its STATUS List, made up of “50 influential people shaping the future of health and life sciences across biotech, medicine, health care, policy, and health tech.”
At the Broad Institute of MIT and Harvard, Carpenter is an institute scientist and senior director of the Imaging Platform. Her work and that of the team she leads is unique in two ways: in rapidly improving drug development and lowering costs through increasingly sophisticated analysis of cell imaging, it’s at the intersection of biology, computational science and AI. And by providing free, open-source analysis software and public datasets, Carpenter and her colleagues are bucking the industry trend of hoarding intellectual property for profit. According to her Institute profile, thousands of biologists use the software and their “Cell Painting assay has been adopted throughout the pharma industry to accelerate drug discovery.”
“My work involves computer vision,” Carpenter said. “Using computers to take the place of our eyeballs, looking at microscopy images. There’s been a major advancement in technology over the past decade or two, which has really made it possible for computers to discover more of what is in images.
“We try to figure out what goes wrong when patients have a particular disease, and then devise methods to test chemicals to see which ones might be good candidate drugs for those diseases.”
Carpenter’s lab is on the data side of that effort. “My lab is entirely computational, but we work really closely with biologists all across the Boston area as well as around the world on different projects. And I love that because I get the opportunity to learn a little bit about all kinds of different diseases and contribute to helping move towards solutions for those diseases.”
| Carpenter on being a scientist When Anne Carpenter won the American Society for Cell Biology’s Women in Cell Biology Mid-career Award in 2020, she wrote an essay about her career path. One section highlighted the collaborative approach that has been the hallmark of her career. “I could not imagine devoting my life to working out the intricate mechanisms of some biological structure or process. But I am delighted that many people are passionate about doing so, and I collaborate with such people every day. It is very clear to me that science functions best as a whole organism, with each part carrying out very different roles in very different ways, rather than arguing about the right way to do science: whether to focus on basic research questions versus applied, generating data versus analyzing the data we already have, big science versus small. . . . Sometimes we take for granted the very organic structure of science, with the moving and mixing of researchers every few years during training, the ease of collaborating across institutional boundaries; all this allows each person to identify his or her style and passions and find people with whom to work that complement them.” |
The researchers in her group, she said, spend their days looking at data and discerning ways to make it yield even more useful information. In addition to overseeing that work, as the leader of the group Carpenter spends her time meeting with scientific collaborators in academia, government and the pharmaceutical industry, raising funds to support her team’s work, and reaching out to new audiences to raise the awareness and use of the tools her team has created.
This has become a stressful time in Carpenter’s world, as U.S. government policies have affected funding, talent recruitment and the ability to work across international lines.
Still, she says, they’re making progress. “I’m going to steal a line from another scientist, saying that I’m a long-term optimist and a short-term pessimist. I do think these methodologies will really change the pace of drug discovery. We desperately need to get new medicines out more quickly and more cheaply.
“But in the short term,” said Carpenter, “there’s a lot that it [“computer vision” and analysis] can’t do quite yet. So a lot of promise on the horizon.”
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