Million Dollar Grants Awarded For Computational Tools To Identify Those At Risk Of Pancreatic Cancer

Pixabay License | Source:  Gordon Johnson , no changes made.
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The Pancreatic Cancer Collective, the strategic partnership of Lustgarten Foundation and Stand Up To Cancer (SU2C), has announced two, million-dollar grants for computational approaches to identify high-risk pancreatic cancer patient populations, based on their health records. The announcement was made at the Annual Meeting of the American Association for Cancer Research.

The identification of genomic and immune factors in high-risk populations for pancreatic cancer will be led by Raul Rabadan, PhD, of Columbia University and Núria Malats, MD, PhD, MPH, of the Spanish National Cancer Research Centre (CNIO). Identifying individuals at high risk of pancreatic cancer through machine learning analysis of clinical records and images will be led by Chris Sander, PhD, of Dana-Farber Cancer Institute and Regina Barzilay, PhD, of the Massachusetts Institute of Technology.

The two teams will each pursue a different approach to identifying individuals in the general population who are at high risk for pancreatic cancer. One will use molecular and genetic data taken from a variety of datasets to identify new and accessible ways to identify high-risk individuals. The other focuses on identification of high-risk individuals by applying machine learning analysis to real-world data comprising radiological images, electronic medical records, and information collected by physicians. Each team will receive up to $1 million over two years.

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The datasets to be used by the two research teams include the UK Biobank, European Study on Digestive Illnesses and Genetics (PanGen-EU), The Cancer Genome Atlas, the International Cancer Genome Consortium, and rich clinical records from large, diverse patient populations within three health systems: Henry Ford Health System, Partners HealthCare, and the Danish National Patient Registry.

“If these efforts to comprehensively integrate clinical, genetic, and microenvironmental factors are successful, this team [Raul Rabadan’s] will revolutionize the screening and identification of individuals highly susceptible to pancreatic cancer,” – Phillip A. Sharp, PhD, the Nobel laureate who is chair of the SU2C Scientific Advisory Committee (SAC) and scientific co-leader of the Collective

“From diagnosing pancreatic cancer to determining which treatment approach may be best for each patient, we believe the field of AI holds great promise for patients and their families.” – David A. Tuveson, MD, PhD, Lustgarten’s chief scientist, director of the Cancer Center at Cold Spring Harbor Laboratory and co-scientific leader of the Collective