The solutions mark Google’s latest advancements in the AI arms race and hope to address a long-standing issue facing biotech and pharmaceutical companies.
researchers traditionally use to determine protein structures also have a high rate of failure, according to Maniar.
Cerevel, which focuses on developing treatments for neuroscience diseases, typically has to screen a large library of 3 million different molecules to find one that will produce a positive effect against a disease, according to Chief Scientific Officer John Renger. He called that process "complicated and involved and expensive."
"What it means is we can get there faster, get there cheaper and we can get to drugs to patients much more quickly without as many failures," he told CNBC. As a startup, Colossal did not have the internal infrastructure necessary to organize or decipher massive quantities of genomic data. One human genome sequence alone requires more than 200 gigabytes of storage, and researchers believe that they will need 40 exabytes to store the world’s genomic data by 2025, according to theThe institute estimates that five exabytes could store every word ever spoken by humans, so building the technology to support genomic data analysis is not a small task.
Researchers’ ability to sequence DNA has historically outpaced their ability to decipher and analyze it. But as technology has improved in recent years, genomic data has unlocked new insights into areas like the genetic variations associated with disease.
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