420 with CNW — Google Unveils AI to Expedite Dru
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Artificial intelligence (AI) now has the potential to significantly speed up the laborious, time-consuming, and currently low-success rate process of finding and approving new pharmaceuticals. Google Cloud introduced two new AI-powered tools — Multiomics and Target and Lead Identification Suites — on May 15, 2023, in an effort to aid pharmaceutical and biotech companies in accelerating the discovery of novel treatments and advancing medicine.
According to a study published in the March 2021 issue of the “British Journal of Pharmacology,” the process of producing a new treatment currently takes between 12 and 15 years from the first idea to the release of the finished product, and can cost more than $1 billion. Moreover, finding a biological target that will make a medication workable can take up to a year.
Conventional methods, such as nuclear magnetic resonance and X-ray crystallography, have a high failure rate and are mostly used to determine the 3D structures of proteins, the biological target required for the initial stage of drug research. These methods could be replaced with AI tools.
Google Cloud announced the launch of the tools during the Bio-IT World Conference held in Boston. The conference, which featured speakers from Harvard Med School, Janssen Pharmaceuticals, and Pfizer Inc., among others, showcased technology and analytical techniques that advance science, address key issues and pave the way for the future of precision medicine.
The Multiomics Suite will support researchers in ingesting, storing, analyzing and sharing enormous amounts of genetic data. This suite supports researchers as they begin to analyze genetic data. DNA can be sequenced far more quickly than it can be decoded and analyzed. However, genomic information in areas such as genetic variants linked to disease is now possible, thanks to technology.
The Target and Lead Identification Suite is made to aid biotech and pharmaceutical businesses in predicting and comprehending protein structure, which also happens to be a crucial component of drug development. Using the Analytics Hub for Google Cloud to securely communicate data, it enables scientists to manage and share protein molecular data.
Then, using AlphaFold2, a machine-learning algorithm created by a subsidiary of Google, researchers analyze data to forecast the structure of a protein. AlphaFold2 is powered by Google’s Vertex AI, a platform that makes it easier for academics to deploy and develop machine learning models. AlphaFold2 can accurately estimate a protein’s 3D structure in a matter of minutes.
The development of new treatments often involves Investigational New Drug Applications (INDs) submitted to the Food and Drug Administration. In biotech, this process can intersect with the cannabis sector, and Google’s new technology may completely change the way certain businesses operate in that space.
It would be interesting to hear what cannabis-based drug developers such as IGC Pharma Inc. (NYSE American: IGC) think of this new drug-development technology released by Google.
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