June 16, 2024

Multi-Institutional Team Leverages AI and Supercomputing to Redesign Antibodies, Enhancing Pandemic Preparedness

A groundbreaking collaboration between researchers from Lawrence Livermore National Laboratory (LLNL) and multiple institutions has resulted in a novel computational approach to redesign antibodies, restoring their effectiveness against viral pandemics, including emerging SARS-CoV-2 variants.

In a recent study published in the journal Nature, the team presented an innovative antibody design platform that integrates experimental data, structural biology, Bioinformatics modeling, molecular simulations, and machine learning algorithms. This platform allowed the researchers to computationally optimize an existing SARS-CoV-2 antibody, ensuring its efficacy against the delta variant while restoring its effectiveness against the omicron subvariants.

The interdisciplinary team’s work, conducted within the GUIDE program, a strategic partnership between LLNL and the Department of Defense, demonstrates the potential to significantly accelerate the drug development process and improve pandemic preparedness. Collaborators from various organizations, including Los Alamos National Laboratory, Vanderbilt University Medical Center, Washington University School of Medicine, Fred Hutchinson Cancer Center, and the JPEO-CBRND, contributed to this project.

The GUIDE program was established to address the pressing need for a swift and adaptive response to biological threats, particularly the continuous mutation of the SARS-CoV-2 virus. The emergence of subvariants that have evaded existing clinical antibody therapeutics highlights the importance of such an approach.

1. Source: Coherent Market Insights, Public sources, Desk research
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