Tuesday, June 10, 2025 6/10/2025

AI-based platform for predicting emerging vaccine-escape variants and designing mutation-proof antibodies

Award Number: R01AI164266
ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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AI-based platform for predicting emerging vaccine-escape variants and designing mutation-proof antibodies - Project Summary Due to massive vaccination, coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been partially under control. However, emerging contagious variants such as Delta are still fueling new waves of infections around the world. Vaccine-escape (or vaccine-breakthrough) variants pose renewed threats to our battle against COVID-19. Understanding viral mutagenesis and evolution is of preeminent importance. By integrating genomic analysis, artificial intelligence (AI), computational biophysics, advanced mathematics, and experimental data, the PIs have built a comprehensive program with the experimental level of accuracy and population-level of reliability for predicting SARS-CoV-2 variant infectivity and antibody disruption. It remains challenging to forecast future emerging vaccine-escape variants, to develop the next-generation of vaccines, and to design mutation- proof antibody therapeutics. These challenges are tackled in the proposed project. New mathematical tools and AI algorithms will be developed to further improve the current state-of- the-art in predicting mutation-induced viral infectivity changes, vaccine breakthroughs, and antibody disruptions. Vital mutations in future emerging variants will be forecasted based on molecular mechanisms, natural selection, and evolutionary effects. New mutation-proof antibody drugs will be designed and tested based on those antibodies that had gone through earlier clinical trials. The predictive models will be implemented into a user-friendly platform with online servers for researchers to design mutation-proof new vaccines and antibody therapies. The proposed methods will be applied to forecast emerging variants in the flu and improve the efficacy of seasonal flu vaccines.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = $547,413 )
2025	2025	MICHIGAN STATE UNIVERSITY	426 AUDITORIUM RD RM 2	EAST LANSING	MI	48824	INGHAM	USA	Allergy and Infectious Diseases Research	000	4	5/21/2025	NON-COMPETING CONTINUATION	$547,413
														Subtotal = $547,413

Issue Date FY: 2024 ( Subtotal = $544,602 )
2024	2024	MICHIGAN STATE UNIVERSITY	426 AUDITORIUM RD RM 2	EAST LANSING	MI	48824	INGHAM	USA	Allergy and Infectious Diseases Research	000	3	4/26/2024	NON-COMPETING CONTINUATION	$544,602
														Subtotal = $544,602

Issue Date FY: 2023 ( Subtotal = $541,935 )
2023	2023	MICHIGAN STATE UNIVERSITY	426 AUDITORIUM RD RM 2	EAST LANSING	MI	48824	INGHAM	USA	Allergy and Infectious Diseases Research	000	2	5/5/2023	NON-COMPETING CONTINUATION	$541,935
														Subtotal = $541,935

Issue Date FY: 2022 ( Subtotal = $540,234 )
2022	2022	MICHIGAN STATE UNIVERSITY	426 AUDITORIUM RD RM 2	EAST LANSING	MI	48824	INGHAM	USA	Allergy and Infectious Diseases Research	000	1	5/6/2022	NEW	$540,234
														Subtotal = $540,234

Grand Total All Awards = $2,174,184

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AI-based platform for predicting emerging vaccine-escape variants and designing mutation-proof antibodies

Award Number: R01AI164266

ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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