We all have heard about how beneficial AI can be in health. There are plenty of papers and research about confronting diseases, like cancer. However, in 2020 with COVID-19 be one of the most serious health problems that have caused thousands of deaths worldwide.
Is AI already being used in the drug industry to combat the COVID-19? If yes, can you, please, provide a reference?
A global race is underway to discover a vaccine, drug, or combination of treatments that can disrupt the SARS-CoV-2 virus.
The problem is, there are more than a billion such molecules. A researcher would conceivably want to test each one against the two dozen or so proteins in SARS-CoV-2 to see their effects. Such a project could use every wet lab in the world and still not be completed for centuries.
Computer modelling is a common approach used by academic researchers and pharmaceutical companies as a preliminary, filtering step in drug discovery. However, in this case, even every supercomputer on Earth could not test those billion molecules in a reasonable amount of time.
Folding@home is a distributed computing project run by Stanford University. The aim of the project is to examine how proteins fold and it does this using spare computing power. however, there is a lot of research in progress that are harnessing the potential of Artificial intelligence to develop the potential treatment to combat the COVID-19.
Check this recent article By Tyler Orton in biv focus on how artificial intelligence is used to accelerate the process of Drug Discovery: Drug research turns to artificial intelligence in COVID-19 fight
Here are the list of some companies that are using AI-driven approach for Drug discovery
The Hong Kong-based company Insilico Medicine, a developer of comprehensive drug discovery and biomarker development platform GENTRL, and a pioneer in the application of generative adversarial networks (GANs) to drug discovery.
Insilico Medicine, Publishes a paper in September last year titled, Deep learning enables rapid identification of potent DDR1 kinase inhibitors," in a most reputed journal Nature Biotechnology. The paper describes a timed challenge, where the new artificial intelligence system called Generative Tensorial Reinforcement Learning (GENTRL) designed six novel inhibitors of DDR1, a kinase target implicated in fibrosis and other diseases, in 21 days.
Four compounds were active in biochemical assays, and two were validated in cell-based assays. One lead candidate was tested and demonstrated favorable pharmacokinetics in mice.
