Computer Graphics World

July-Aug-Sept 2021

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32 cgw j u ly • a u g u s t • s e p t e m b e r 2 0 2 1 T oday, we can produce more biomedical data in about three months than we did in the past, with petabytes from just a single hospital. There is a deluge from various sources, such as patients' medical records, medical instruments, lab work, and more. Likewise, in the research and development space, similar amounts of data are gener- ated from clinical trials, e-notebooks, and other drug development groups. No human can synthesize that level of data, and this is where artificial intelligence is crucial. It is soware that writes soware that no human can. Machine learning and deep learning can harness this exploding quantity of health data and are capable of identifying patterns in immense amounts of data, helping us glean insights faster and more holistically. This is especially important in areas where clinical staff and resources are low compared to the number of patients. Deep learning can help identify genomic variants and detect anomalies in a radiol- ogy image. It can help us to generate new chemical structures during drug develop- ment, make sense of pathology reports and medical records, guide us through medical procedures via AI-assisted robotics and surgical devices, flag urgent cases or patient falls, and be the extra tools we need to bring care to patients faster. AI is an invaluable tool across all aspects of biology in the discovery of therapeutics in humans, to discovering new plant mole- cules in solar synthesis, to agro-industrial uses. And AI helps us amass insight faster, as speed of discovery became especially important this past year during the deadly public health crisis of COVID-19. SCREENING MORE COMPOUNDS The pharmaceutical industry invests billions of dollars to bring drugs to market, only to watch 90 percent of them fail before they even reach clinical trials. The rise in digital data in health care actually presents an opportunity to improve the understanding and holistic view of a patient through AI. Mo- mentum around this shied with COVID-19, with start-ups in this space raising well over $5 billion in 2020. Top research institutions, like the Uni- versity of California at San Francisco, are using Nvidia GPUs to power their work in cryo-electron microscopy, a technique used to study the structure of molecules, such as the spike proteins on the COVID-19 virus, and accelerate vaccine and drug discovery. Pharmaceutical companies, such as GlaxoSmithKline and major health-care sys- tems like the U.K.'s National Health Service, will utilize the computer power of Cam- bridge-1, the U.K.'s faster supercomputer, to identify and create novel therapeutics, with the goal of improving diagnosis and delivery of critical medicines and vaccines. Last fall, a team of 27 researchers, led by Rommie Amaro at the University of Cali- fornia at San Diego, combined high-perfor- mance computing (HPC) and AI to provide the clearest view of the coronavirus to date, winning the Gordon Bell Prize for fighting COVID-19 — the equivalent of the Nobel Prize in the supercomputing community. The image was taken by Amaro's lab using what is called a computational micro- scope, a digital tool that links the power of HPC simulations with AI to see the details beyond what is capable with conventional instruments. For more than a decade, every ma- jor pharmaceutical company has used Schrödinger's modeling soware, which AI Rx ARTIFICIAL INTELLIGENCE IS ADVANCING HEALTH CARE AND LEADING A DIGITAL BIOLOGY REVOLUTION BY VANESSA BRAUNSTEIN Using HPC and AI, researchers achieved the clearest view of the coronavirus thus far.

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