Discovering and validating potential immune biomarkers is a highly complex and time-consuming process. These biomarkers can be identified in several ways, including studies of recovery from natural infection, animal immunogenicity studies, and human clinical studies. Scientific literature related to the development of vaccines against a given pathogen can cover decades of research and be highly diverse.
AI offers a powerful opportunity for accelerating this process. By rapidly analyzing data, generating hypotheses, and supporting regulatory justifications, AI tools may be able to identify potential CoPs that could help speed the development of new vaccines.
“Automated search and synthesis of research is not new, but as with so many fields, the advent of large language models has profoundly changed what is possible—and the speed at which it can be done,” said Dr. Bilal Mateen, Chief AI Officer at PATH.
“These tools have exciting potential to not only breathe a second life back into previously considered but prematurely abandoned hypotheses, but also, given their ‘generative’ nature, to maybe even propose something radically new.”