IBM & Cleveland Clinic Develop AI to Identify Cancer Targets

Partnering with IBM allows us to push the boundaries of AI to change the way we develop and evaluate targets for cancer therapy, says Dr Chan

IBM has partnered with researchers from global health system Cleveland Clinic to explore strategies of identifying new targets for immunotherapy through artificial intelligence. The publication comes from Discovery Accelerator, a partnership between the two organisations that aims to advance research in healthcare and life sciences.

The developments come in the form of both supervised and unsupervised AI that reveal the molecular characteristics of peptide antigens, small pieces of protein molecules that immune cells use to recognise threats.

“In the past, all our data on cancer antigen targets came from trial and error,” says Timothy Chan, M.D., Ph.D., chair of Cleveland Clinic’s Center for Immunotherapy and Precision Immuno-Oncology and Sheikha Fatima Bint Mubarak Endowed Chair in Immunotherapy and Precision Immuno-Oncology. 

“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.”

Nonprofit multispecialty academic medical centre Cleveland Clinic was founded in 1921 to provide outstanding patient care based upon the principles of cooperation, compassion and innovation. The organisation integrates clinical and hospital care with research and education.

Expert insight on AI in healthcare

Dr. Chan co-authored the report with Dr. Tyler Alban.

Alban is a computational biologist in Cleveland Clinic’s Center for Immunotherapy and Precision Immuno-Oncology where he leads a team of data scientists working on immunogenomics of clinical trials aimed at understanding the mechanisms of immunotherapy resistance.

Additionally, he is a team lead on multiple projects within the Cleveland Clinic IBM Discovery Accelerator partnership, where teams are focused on the use of Quantum machine learning applications in immunotherapy.

Prior to this work, he completed PhD in the Molecular Medicine PhD program at Cleveland Clinic where he worked as a Post-Doctoral Fellow.

Dr. Tyler Alban, co-author of the report.

Dr. Alban shared his thoughts with Healthcare Digital about the impact of AI on healthcare.

What does the discovery mean to the field of immunotherapy? 

Cancer vaccines, CAR-T cells, and checkpoint inhibitors all rely on successful neoantigen recognition by the immune synapse. However, our current understanding of these interactions is based on simplistic sequence-based models. The work here demonstrates that using molecular dynamic simulations of neoantigen recognition can reveal previously unknown features of immunogenic peptides. Exploitation of these features could be used for development of future cancer vaccines and our understanding of immunotherapy resistance.

How can tech and healthcare companies work together to solve pressing healthcare issues?

Cleveland Clinic and IBM set an example of how tech and healthcare can work together with their 10-year partnership and establishment of the Discovery Accelerator. Investments and partnerships like these can greatly speed up the pace of discovery and eliminate barriers of interaction that may exist when academic scientists try to branch out and work with tech companies like IBM.   

What other opportunities in healthcare does this technology present? 

The computational framework developed in this project could be used across other HLA alleles. Due to the available data in the field and computational limitations, this project focused on one HLA allele (HLA-A2), however, there are thousands of alleles each likely with their own unique binding and neoantigen presentation characteristics.


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