USA TODAY International Edition
Bringing biology and AI together
We’re betting that artificial intelligence will help speed real breakthroughs to improve human health
Life and computer sciences have long moved in parallel. In the 1950s, Rosalind Franklin confirmed the structure of DNA while computer scientists were creating artificial intelligence, teaching machines to play checkers. Two decades later, Moore’s Law as we know it took hold, with computing power doubling every two years. Meanwhile, in 1975, Frederick Sanger was figuring out how to sequence a genome.
In the 1990s, the Human Genome Project kicked off while Deep Blue prepared to play and went on to beat reigning chess champion Garry Kasparov. A few years later, we had a full sequence of a human genome — and the ability to make some medical diagnoses with artificial intelligence.
Today, sequencing a human genome costs 0.00003% of what it cost two decades ago — thanks in no small part to Moore’s Law and other computing advances. And AI is everywhere you look, driving cars, recommending movies on Netflix and, yes, discerning cancer from a scan with increasing accuracy.
Despite these parallel histories — and direct convergences, in some cases — we have not yet fully connected data science, AI and machine learning with biology to help solve humanity’s biggest medical questions and challenges. We believe that now is the time — in fact, we’re betting on it.
Last week we announced the Eric and Wendy Schmidt Center at the Broad Institute of MIT and Harvard, a new initiative that we hope will enable scientists around the world to build a new field of knowledge, bridging the two most significant scientific revolutions of our time and advancing the quality and longevity of human life, ethically and equitably.
Many talented scientists are already working at the intersection of these fields. They’ve created algorithms that can design drugs to target particular illnesses, or to spot patterns in cells and tissues to speed up drug screening.
Significant untapped potential
One team at MIT used machine learning to unearth a compound that can kill otherwise wholly drug- resistant bacteria, which poses a massive health challenge around the world.
And AI is already a player in the battle against the coronavirus pandemic: Scientists have used it to identify FDA- approved drugs that could be repurposed to treat COVID- 19 in elderly patients.
The fact that this latter development came more than a year after the disease COVID- 19 was detected demonstrates that there is significant untapped potential in bringing life and data sciences together.
Imagine each example above on a much bigger scale: speedy drug discovery for pressing health needs around the world; quick detection of disease in cells and tissues; truly rapid and potentially hugely lifesaving response to the pandemic.
Then, imagine even more: a complete catalog of the pathways and processes that are encoded in human cells; a deep understanding of how any number of diseases invade and alter human cells; and a way to predict, analyze, diagnose, treat and maybe even cure some of them.
Success may very well be defined in solving a problem we don’t even know exists today.
Ethical lapses and inequities
We also recognize it won’t be enough to bridge life and data sciences alone, powerful as that may be. We also need to consider ethics, behavioral science and the study of racial, gender, class and other disparities as we pursue this work.
Since the founding of genomics and artificial intelligence, both fields have been plagued by ethical lapses and inequities, from Eurocentric genomic datasets that make scientific findings less relevant for the global majority, to the creation of AI that encodes racial biases instead of eliminating them.
Both sciences face dramatic underrepresentation of women and people of color, meaning we’re missing out on the talents and insights of untold numbers of people.
During this devastating year of pandemic, we’ve seen how scientists and policymakers, doctors and diplomats, contact tracers and communicators, ethnologists and economists have all had to work together — with failure to do so leading to tragedy. Our world’s problems simply cannot be solved in silos. Solutions come from deep collaboration, across borders of all kinds, which is exactly what we hope to see more of, and fast.
We have witnessed the power of bringing together exceptional people with diverse backgrounds and areas of expertise through Schmidt Futures, one of our philanthropic initiatives, which inspired us to make this investment in the Broad Institute. And our Schmidt Family Foundation sees how transformational change only happens when problems are addressed from many directions, systematically. When it comes to our health, the stakes are too high, and the promise too great, to do it any other way.
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