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Disease X Vaccine Powered by AI
Disease X Vaccine Powered by AI
As globalization, urbanization and climate change continue, experts agree that future outbreaks of dangerous novel viruses (Disease X) are inevitable. In 2022, the Coalition for Epidemic Preparedness Innovations (CEPI), published a landmark report, “What Will It Take,” which outlined the paradigm shift needed to speed up vaccine development, and the crucial scientific and technological innovations—including the creation of a vaccine library—that will enable the world to develop new vaccines against future pandemic threats in just 100 days.
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Last summer, CEPI and Houston Methodist announced a partnership—and funding of a consortium led by Houston Methodist—to combine innovative artificial intelligence (AI) technology with established laboratory techniques to further the rapid development of future vaccines against Disease X. The Houston Methodist group was awarded $4.98 million to advance the application of AI to analyze the structures of priority viruses from which the next Disease X is likely to emerge. In 2024, the award increased to $34 million over five years.
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The Team
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Jimmy D. Gollihar, PhD
Led by Jimmy D. Gollihar, PhD, Professor of Pathology and Genomic Medicine and Head of the Antibody Discovery & Accelerated Protein Therapeutics Laboratory, the Houston Methodist team joins experts from Argonne National Laboratory (University of Chicago), J. Craig Venter Institute, La Jolla Institute, The University of Texas Medical Branch and The University of Texas at Austin. Initially, the team will focus efforts on paramyxoviruses and arenaviruses, and viral families, including Nipah virus and Lassa virus, respectively.
“We are delighted to have the Houston Methodist Academic Institute be a part of this program, serving our community and the world. Leading this consortium is an amazing undertaking and a testament to the work that Dr. Jimmy Gollihar, his team in pathology and genomic medicine, and many others in our academic institute are doing to help defeat the next pandemic,” said Dirk Sostman, MD, FACR, Emeritus Professor of Radiology and Distinguished Member of Houston Methodist Academic and Research Institute.
The Mission
A critical enabler of the 100 Days Mission is the establishment of a global “vaccine library”—an accessible store of scientific knowledge, data and prototype rapid-response vaccine candidates against selected viruses from the 25 priority virus families. CEPI’s aim is to store AI-generated, lab-tested and verified antigen designs, developed by the Houston Methodist consortium, in the vaccine library to be quickly used to develop vaccine candidates in the event of an outbreak of a novel pathogenic threat. In this scenario, after sequencing the offending virus, these cataloged antigen designs can be inserted into an appropriate rapid-response vaccine platform to start the production of vaccines for clinical testing.
Spike Display
Gollihar’s group is leading immunogen design, but their work encompasses much more. The team has been developing therapeutic monoclonal antibodies for SARS-CoV-2. As variants of concern emerged, they wanted to determine what those mutations were doing to their monoclonals. So, they developed a mammalian display of viral glycoproteins—called a spike display—to allow researchers to study virus mutations and source code in real time.
“We started using spike display to dissect escape mechanisms and realized it was also an engineering tool. We played around with rational design-based approaches with individual variants and then moved to library approaches where we could use millions of variants in human cells and mammalian cell lines and sort, seek and find out what's binding what. The confluence of AI and directed evolution is outright, but protein engineering is really what allows us to do this rapidly,” said Gollihar.
Battling The Next Pandemic Threat
AI experts from Houston Methodist, The University of Texas at Austin, La Jolla Institute and Argonne National Laboratory will use machine-learning approaches to optimize the design of potential epitopes. The University of Texas Medical Branch will validate their immunogenicity in established preclinical models. When a new pathogen emerges, vaccine developers could quickly respond by selecting AI-identified epitopes that would have already been validated in preclinical tests, enabling vaccine candidates to be moved quickly into clinical testing. This would provide a significant strategic advantage when battling the next pandemic threat, but Gollihar is looking even further into the future.
“The next generation of models for protein engineering will require data sets that don’t yet exist, so we’re really interested in deep mutational scanning,” noted Gollihar. “Because of our engineering platform, we can now take every amino acid and put it into every single position of a protein and ask: what does that mean to expression, antibody binding or host receptor binding? We’ll learn things we could not otherwise learn. This is the next frontier, and we are leading it.”
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