In a groundbreaking collaboration, researchers from Cleveland Clinic and IBM have unveiled a pioneering strategy for identifying new targets for immunotherapy through the application of artificial intelligence (AI). This marks the first peer-reviewed publication resulting from the Discovery Accelerator partnership between the two organizations, aimed at advancing research in healthcare and life sciences.
Published in Briefings in Bioinformatics, the study showcases the capability of AI models that account for changes in molecular shape over time, providing accurate depictions of how immune systems recognize target antigens. By leveraging these models, researchers can pinpoint critical processes to target with immunotherapy treatments, including vaccines and engineered immune cells.
The collaborative team developed both supervised and unsupervised AI techniques to unveil the molecular characteristics of peptide antigens, the small protein fragments that immune cells utilize to identify threats. Bringing together experts from diverse groups led by Cleveland Clinic’s Dr. Timothy Chan and IBM’s Dr. Jeff Weber and Dr. Wendy Cornell, the project represents a significant leap forward in understanding cancer antigen targets.
Dr. Timothy Chan, Chair of Cleveland Clinic’s Center for Immunotherapy and Precision Immuno-Oncology, emphasizes the transformative potential of the partnership with IBM. He notes, “Partnering with IBM allows us to push the boundaries of artificial intelligence and health sciences research to change the way we develop and evaluate targets for cancer therapy. In the past, all our data on cancer antigen targets came from trial and error.”
The historical challenge in identifying antigens and using them to combat cancer cells or virus-infected cells stems from the complex interaction between antigen peptides and immune cells, based on specific features on the cell surface—a process still not fully understood.
The breakthrough AI models developed by the collaborative team address the limitations of traditional computing methods, which struggle with the multitude of variables influencing immune system recognition. Dr. Jeff Weber of IBM expresses the success of the partnership: “These discoveries are an example of what makes this partnership successful—combining IBM’s cutting-edge computational resources with Cleveland Clinic’s medical expertise.”
Moving forward, these insights can be incorporated into other AI models, opening the door to identifying more effective targets for immunotherapy. The collaborative efforts between medical expertise and computational prowess showcase the potential of innovation when driven by collaboration, heralding a new era in cancer therapy research.
