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AI is already discovering new cures
As part of a wide-ranging conversation on the GZERO World podcast, oncologist and Pulitzer prize-winning author Siddhartha Mukherjee walks Ian Bremmer through one of the most groundbreaking uses of AI in medicine today: generative drug discovery. It’s not just about speeding up research—it’s about creating entirely new molecules that no human has ever seen.
Using AI, researchers can now analyze the shape of a dysfunctional protein—like one found in a cancer or autoimmune cell—and generate chemical compounds that could bind to and modify its behavior. “This is true generative chemistry,” Mukherjee says. “Every time we do this in collaboration with a machine, the machine learns it, and it learns it forever.”
The process is like solving a puzzle with a million possible pieces. With each failure, the AI learns more, narrowing down candidates until it finds a match. It’s already produced new antibiotics with never-before-seen structures—and Mukherjee believes this is just the beginning of a medical revolution.
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How AI will revolutionize medicine with Siddhartha Mukherjee
Listen: Nearly 1 in 2 men and 1 in 3 women in the US will be diagnosed with cancer, and 1,700 people die from it every day. Disparities persist—Black women are 40% more likely to die of breast cancer than white women—and treatment costs remain crushing for many.
On the latest episode of the GZERO World podcast, Ian Bremmer talks with world-renowned cancer researcher and Pulitzer Prize-winning author Siddhartha Mukherjee about the future of medicine—and why artificial intelligence might finally tip the scales in the decades-long war on cancer.
Cancer remains the second leading cause of death in the US, killing nearly 1,700 people every day. But Mukherjee says AI is already reshaping the field, from radiology and diagnostics to identifying new carcinogens and designing entirely new cancer drugs. “Every time we do this in collaboration with a machine,” he explains, “the machine learns it, and it learns it forever.”
In a wide-ranging conversation, Mukherjee breaks down three major areas where AI is advancing medicine: patient care, data mining, and generative drug development. He also weighs in on early cancer detection, how inflammation may hold the key to understanding new carcinogens, and why this moment may be the most hopeful in half a century of cancer research.
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What AI could mean for healthcare
Researchers at the University of South Florida are using AI and virtual reality to study Alzheimer's disease and autism, mapping the brains of mice as they develop. A team from IBM and the Cleveland Clinic published a strategy for using AI to find new targets for immunotherapy. And a new startup is incorporating AI into CRISPR, the revolutionary gene-editing technique, to identify novel gene alterations not already found in nature to expand the possibilities of new treatments.
Meanwhile, a slew of new AI-powered cancer screenings have now been approved by the US Federal Drug Administration and are available for concerned patients, according to CNBC. That follows a trend: about 600 of the 900 AI and machine learning devices and programs approved by the FDA in the past five years have been radiology applications.
And patients could even find that their most ornery doctors are suddenly friendlier. Many report that ChatGPT and other tools have improved their virtual bedside manner over medical chat-based programs.
“It’s hard to overstate the potential that AI breakthroughs could have for nearly every aspect of healthcare, from our understanding of disease and designing new drugs to aspects of healthcare delivery like improving access through more efficient allocation of limited resources,” said Laura Yasaitis, a healthcare consultant for Eurasia Group.
Of course, she has concerns, such as overreliance on AI-generated output, privacy, and exacerbating inequities such as in approving or denying insurance claims.
And, at least for now, Yasaitis thinks that the most promising use of AI is, yes, the boring stuff.
“For every hour of direct patient care, doctors spend around two hours on paperwork during the day, and another one to two hours at night,” she said. “AI applications that can generate much of that content, and then only require review by clinicians, could dramatically reduce that burden.”
While these technologies offer hope for improving healthcare options and extending lives, insurers have yet to catch up. Medicare and private insurers tends not to cover AI-based tests. So when AI makes medical breakthroughs, there might be a delay for those who cannot afford to pay out of pocket.
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