{"id":1863,"date":"2024-07-11T10:00:06","date_gmt":"2024-07-11T17:00:06","guid":{"rendered":"https:\/\/dornsife.usc.edu\/magazine\/?p=1863"},"modified":"2024-10-23T13:45:36","modified_gmt":"2024-10-23T20:45:36","slug":"crunching-codes-crafting-cures","status":"publish","type":"post","link":"https:\/\/dornsife.usc.edu\/magazine\/crunching-codes-crafting-cures\/","title":{"rendered":"How artificial intelligence and computational biology are reshaping the quest for better medicines"},"content":{"rendered":"\n\n\n\n\n \n \n\n\n\n\n\n\n\n
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\n\n \n How USC Dornsife is writing the formula for the future of medicine. (Photograph:Max Gerber.)\n\n\n<\/div>\n <\/div>\n \n
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How artificial intelligence and computational biology are reshaping the quest for better medicines<\/h1>\n\n\n<\/div>\n \n \n By<\/span>Katharine Gammon<\/a><\/strong>\n \n July 11, 2024<\/span>\n <\/div>\n<\/div>\n\n\n <\/div><\/div>\n\n \n \n\n\n\n\n\n\n\n
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The Human Genome Project, which mapped the entirety of the genetics of our species, was a watershed moment in science. One of the greatest scientific feats in history, the project was a biological voyage of discovery that significantly advanced our understanding of disease, health and the functionality of our bodies, paving the way to improved medical practice. The landmark global scientific effort was based on foundational research by University Professor Emeritus Michael Waterman<\/a>. Known as the father of computational biology, Waterman joined USC Dornsife in 1982, where he founded one of the world\u2019s first PhD programs in that discipline.<\/p>\n

Building on Waterman\u2019s legacy, USC Dornsife created the Department of Quantitative and Computational Biology<\/a> in 2021, drawing some of the top researchers in the field. We caught up with founding department chair Remo Rohs<\/a> to talk about ongoing research, the role of artificial intelligence (AI) and why he believes the future of biology lies in computation.<\/p>\n

How has computational biology advanced since Michael Waterman founded the field in the early 1980s?<\/strong><\/p>\n

Computational biology uses data analysis, mathematical modeling and computational simulations to understand biological\u00a0systems and relationships. Forty years ago, it was considered a pioneering discipline \u2014 today it is fundamental to the field of biology. Not only are we now able to collect vast quantities of data, but the evolution of biological research demands increasingly sophisticated methods to analyze and interpret this wealth of information.<\/p>\n

The field began with genome sequencing in humans and other species. From those beginnings, it has evolved in a number of directions. We now design new drugs by using structural data to figure out how chemical compounds will work. We use mathematical modeling to predict outcomes in cancer. It\u2019s all a part of the interdisciplinary work the department is doing. I am a physicist by training with a PhD in chemistry. Many of my colleagues are mathematicians, statisticians and computer scientists. What unites us is that we all study biological questions.<\/p>\n

How is the department\u2019s research improving health care outcomes?<\/strong><\/p>\n

Here is just one example from my lab, where we\u2019re using AI to create new, more effective drugs.<\/p>\n

Past drug design was limited to incremental improvements on existing compounds. But now, with the help of AI, we\u2019re identifying proteins or nucleic acids within cells that drugs can affect to treat diseases. And we\u2019re designing previously unknown drugs using machine learning. It\u2019s like finding a new lock and designing the perfect key for it. This means we can create entirely new drugs that are more likely to work and cost less to develop.<\/p>\n

In collaboration with colleagues at the USC Michelson Center for Convergent Bioscience<\/a>, we are already synthesizing some promising new cancer drugs that are based on our work.<\/p>\n

What can we expect from the field of quantitative and computational biology in the next 20 years?\u00a0<\/strong><\/p>\n

Projects across specialties such as molecular biology, evolutionary biology, neurobiology and marine biology already require complex math and computer modeling methods. I believe that all fields of biology will become increasingly reliant on computers, databases, mathematics and statistics. That\u2019s why I call our department \u201cthe biology department of the 21st century.\u201d<\/p>\n

AI is dramatically altering many areas of research, but it is poised to have a particularly huge impact in computational biology, since the field is already so rich with data. There\u2019s no question AI will drive change in a wide range of areas, from revolutionizing basic scientific research to determining how hospitals are run. Because this is ultimately all about data. And it doesn\u2019t matter so much if we\u2019re looking at a protein structure or a patient file. At the end of the day, AI is a supremely efficient way to analyze data, interpret it and draw conclusions. And that holds tremendous promise for innovation in all areas \u2014 from biological discovery to health care.<\/p>\n\n\n\n<\/div>\n\n\n <\/div><\/div>\n\n\n\n\n\n \n \n \n\n\n\n\n\n\n\n

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