American Scientist

Kendall Square, a life science hub and major tech center near the Massachusetts Institute of Technology, hosts many start-ups and venture capital firms. In his new book, Where Futures Converge: Kendall Square and the Making of a Global Innovation Hub, Robert Buderi tells stories about the hub’s history, interviews the entrepreneurs who work there, and considers its future as a place where artificial intelligence, health care, and biology converge.

When I met with E. O. Wilson to kick off this book, one big theme we talked about was evolution. A thriving ecosystem, just like a thriving person, isn’t static; it keeps evolving and growing, spawning novel species, adapting to changing conditions. One of the key ways that happens in innovation ecosystems is the convergence of different technologies or scientific [disciplines] to inspire ideas and innovations, and sometimes new fields.

A number of people are already working on the next technological iteration of Kendall Square. It seems clear that the dominant current threads, in computing, machine learning, and especially in biotechnology, are not going away in the foreseeable future. In biotech alone, emerging tools like CRISPR gene editing, as well as “older” innovations like genomics, RNA interference, and gene therapy, are just beginning to make their marks. To all appearances, their future is very bright. . . .

When talking to people about new fields of growth that might power not just Kendall Square, but the entire region, two major lines of thought come through. Both involve convergence. Atop many people’s list is the convergence of artificial intelligence (AI), health care, and biology.

This convergence has been underway for a number of years. Every biotech and pharma company utilizes a mash-up of computing power and data science along with its biology. The Broad Institute, with its powerful genomics platform, employs a lot of machine learning and AI. GNS Healthcare, a Kendall Square start-up that recently moved a half-mile away to Somerville, uses its “causal AI technology” to figure out which patients respond to a given drug and why—as well as to discover new drug targets for specific patient populations. A host of start-ups these days champion their use of AI, with wide variance in how they employ it. In short, there are many flavors of AI and myriad ways to bring it to bear on health care. These run from analyzing medical images with unprecedented accuracy to diagnosing disease to finding drug compounds. “The convergence of molecular patient data, computing, and bleeding-edge AI mathematics will do more to transform our understanding of complex diseases such as cancer, neurodegeneration, and immune system diseases and our ability to discover and develop drugs and better match them to patients in the real world than any other innovation,” says GNS Healthcare cofounder and CEO Colin Hill. “This is the key that unlocks a new age of predictive biology that will change the way we discover, develop, and use new and existing medicines.”

One manifestation of this trend can be seen in Takeda Pharmaceutical Company’s Data Sciences Institute. The institute is based near Central Square, but its 250 statisticians, programmers, real-world data experts, digital tools specialists, and others are spread all over—including Kendall Square and other sites around the world.

The ultimate goal is to analyze and crunch data to design better drug trials and help improve patient outcomes, explains Anne Heatherington, the senior vice president who heads the institute. Her group does this in a number of ways that don’t involve AI, such as employing digital tools to gather patient data remotely, as well as traditional mathematical methods. But one longer-term effort seeks to use vast computing power, natural language processing, and AI techniques to mine patient records and medical data to better diagnose patients. For some rare diseases, it can take seven years or more to make the right diagnosis, which makes outcomes more problematic, says Heatherington. “If there are algorithms built into the hospital systems, patients could potentially get flagged for particular diseases much, much earlier,” she says.

An interdisciplinary mindset is critical to addressing many future challenges.

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In early 2020, the company announced a collaboration with the MIT Jameel Clinic for Machine Learning in Health—known as the J-Clinic—that would help with this effort and others. The three- to five-year initiative (dollar terms were not announced) is designed to explore issues at the intersection of AI and health that Takeda believes could impact its business. It started with 10 projects—among them efforts in diagnosing gastrointestinal diseases, drug manufacturing, and biomarkers—each involving a joint team of Takeda and MIT people. “The plan is each of these 10 projects will have a two-year life span, and then we will kick off another round of projects after that,” says Heatherington.

Coming at this convergence from the big tech perspective is IBM, which established its IBM Watson Health headquarters in Kendall Square in 2016. Around the same time, it beefed up IBM Research’s local strength in AI—putting both groups in the same building along Binney Street. Big Blue then underscored its growing Kendall Square AI activities with several major financial commitments. In 2016, it announced a five-year, $50 million collaboration with the Broad Institute to support an initiative to sequence cancer samples and then analyze related genomic data with Watson. It expanded that in 2019, announcing a separate three-year joint project aimed at helping physicians wield genomics, AI, and clinical data to better predict the likelihood of patients developing serious cardiovascular diseases. Meanwhile, in 2017, it also announced a 10-year, $250 million commitment to fund a new laboratory at MIT—the MIT–IBM Watson AI Lab.

Through this lab, IBM backs about 50 projects per year, addressing a variety of issues that include algorithms, hardware, applications for specific areas like health care, and the ethics of AI. . . .

These are just two examples of what large corporations are doing around the convergence of computing, AI, and health care. They are hardly alone. MIT, not surprisingly, is at the heart of many collaborations—and has AI-related initiatives with a number of other companies and organizations. . . . One of the latest, announced in March 2021, involves the creation of the Eric and Wendy Schmidt Center at the Broad Institute of MIT and Harvard. The upstart center, backed by a $150 million endowment from the former Google CEO and his wife, will bring AI and computer science more broadly to bear against a variety of diseases and medical conditions. It also will follow the Broad tradition of collaborating with a number of other top institutions and companies worldwide.

Well before the Schmidt Center’s formation, MIT took things to another level in 2018 when it announced a $1 billion commitment toward addressing the opportunities and potential hurdles posed by the increasing power of AI and computing. The commitment included the establishment of a new college, the MIT Schwarzman College of Computing. The college marks the most significant structural change at MIT in more than 70 years. . . . One of the main goals involves integrating AI into every discipline at MIT.

. . . An interdisciplinary mindset is critical to addressing many future challenges, [says the college’s inaugural dean, Daniel Huttenlocher], and the college will provide more paths for students “that aren’t just the silos of the disciplines.”

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The integration of AI and machine learning with a variety of fields opens the door for a wave of innovations and start-ups. In the eyes of Jim Collins, a serial entrepreneur and the Termeer Professor of Medical Engineering and Science at MIT, AI writ large is “going to be one of the two dominant themes of this century.” The other, he believes: synthetic biology.

Collins is uniquely positioned to come to this conclusion. He is one of the seminal figures in the field, winner of a MacArthur “genius” award largely for his work on this frontier. One of the companies he cofounded, Synlogic, is based along Binney Street in Kendall Square, and is seeking to develop a novel class of bioengineered, “living” drugs that target tumors and various diseases or conditions, among them gastrointestinal and immune disorders. But that is just one face of synthetic biology—and as it becomes increasingly melded with the power of AI, even more possibilities will arise, Collins predicts. “The integration of AI with synthetic biology will allow us to use advanced computational tools to understand and embrace the complexity of biological systems, enabling us to harness the power and diversity of biology for the benefit of our planet. We will be able to endow living cells with novel functions, enabling us to tackle some of the world’s great challenges in health, food, energy, climate change, and sustainability.”

Excerpted from Where Futures Converge: Kendall Square and the Making of a Global Innovation Hub, by Robert Buderi. Reprinted with permission from The MIT Press. Copyright 2022.