Omicron Predicted Near 90% Breakthrough of Immune Individuals
POSTED: Monday, November 29, 2021
CATEGORY: Foundation News
Michigan State University Research Team Uses Mathematical AI to Predict Omicron to have near a 90% Antibody Breakthrough Likelihood and be 7 Times more Infectious than Alpha
East Lansing, November 28, 2021 - The world is anxious for data, not just conjecture, on the latest COVID-19 mutation, Omicron, B.1.1.529. While we need to wait a few weeks for relatively reliable lab data on existing antibody breakthrough likelihood, diligent scientists at Michigan State University have been accurately predicting transmissibility and antibody breakthroughs for the last 23 months.
Here is what they’ve predicted so far, Omicron:
At near 90%, has the highest likelihood of a known antibody breakthrough, more than any other known variants so far, mainly due to K417N, E484A, and Y505H. (Omicron provides serious resistance near 90% of the 132 known COVID-19 antibodies from prior infections and/or vaccines)
Causes about a 15 times efficacy reduction in the Eli Lilly antibody cocktail, while Regeneron monoclonal antibodies (mAbs) are slightly affected.
Is about 7 times more infectious than Alpha, or as much as 12 times more than the original virus found in Wuhan, 2 times more infections than Delta mainly due to N440K, T478K, and N501Y.
AI predictions are based on 15 RBD co-mutations (on the viral spike receptor-binding domain (RBD) G339D, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493K, G496S, Q498R, N501Y, Y505H).
There are no predictions for virulence, but there is no mutation found at the protease inhibitor binding site so the new Pfizer treatment pill, PAXLOVID, looks like it will remain effective.
About: Dr. Guowei Wei, MSU Foundation Professor. Mathematics, Biochemistry & Molecular Biology, Electrical & Computer Engineering, is a leading researcher in AI Drug Discovery says, “My lab has been hard at work leading in the battle to provide accurate predictive data in the fight against COVID for 23 months, we hope this data helps the world to make informed decisions while we wait for experimental lab results”. With his team, they are the highest prize winners in the Drug Design Data Resource (D3R) Grand Challenges, sponsored by the National Institutes of Health (NIH). With postdoc Dr. Jiahui Chen and graduate student Rui Wang, the team uses advanced mathematics and artificial intelligence (AI) to model the complex interactions between the COVID-19 spike protein binding with the human ACE2 receptor or 132 known COVID-19 antibodies to predict transmissibility and known antibody breakthroughs. The team has successfully predicted two major spike protein mutation sites, L452 and N501, for all prevailing variants in May 2020, many months before any variants were identified by WHO. You can investigate the details of this and other work by Dr. Wei here https://users.math.msu.edu/users/weig/.
Dr. Wei is also CTO of MAI Therapeutics. CEO of MAI Therapeutics, Nancy Benovich Gilby states “I have the honor of working with the technology produced by Dr. Wei and his amazing team of scientists. MAI is revolutionizing Drug Discovery by licensing and commercializing the Wei Lab research to have a significant global impact.”
Please direct any media inquiries to Nancy Benovich Gilby: nabgilby@maitherapeutics.com, 650.539.8376.