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COVID, Cancer, and HPC Highlight the Computational Approaches for Cancer Workshop at SC

coronavirus

COVID-19 has transformed life around the globe. In NYC, where I work for the Mount Sinai Health System, we were at the center of the epidemic in the United States in March. At this time, our clinicians and researchers leveraged their domain expertise to focus solely on better understanding and treating this new disease. The spotlight on COVID-19 created new interdisciplinary teams that have already been fruitful: the discovery that the first COVID-19 cases in NYC came from Europe in March1, the first to use AI to detect COVID-related lung disease in CT scans2 and the identification of inflammatory markers to help guide treatment for severe COVID-19 cases3. These advances were made possible through a team science approach that brought together experts in diverse domains, including cancer, computational science and infectious disease. Bridging disciplines is an essential tenet to productive modern science.

We have shared this same interdisciplinary approach for the design of the Computational Approaches for Cancer Workshop, now in its sixth year, at SC20. Experts in the computational, computer, basic and data sciences from the National Cancer Institute (NCI), National Institutes of Health (NIH), U.S. Department of Energy (DOE), Frederick National Laboratory for Cancer Research (FNL), National Science Foundation (NSF), academia and industry have gathered to discuss innovations and best practices on a wide array of topics from drug design, machine learning and data sharing. This workshop has enabled new human connections, facilitated a common language across disciplines, and improved understanding of biomedical opportunities and challenges in the high performance computing community.

With the bridges that have already been built over the last five years, and with the pandemic continuing to rage, this workshop comes at a critical time: never before has the intersection of computational, data and biomedical sciences been more crucial. We look forward to seeing you at the workshop.


1 https://www.mountsinai.org/about/newsroom/2020/mount-sinai-study-finds-first-cases-of-covid-19-in-new-york-city-are-primarily-from-european-and-us-sources-pr

2 https://www.mountsinai.org/about/newsroom/2020/mount-sinai-first-in-us-to-use-artificial-intelligence-to-analyze-coronavirus-covid19-patients-pr

3 https://pubmed.ncbi.nlm.nih.gov/32511562/

Patricia Kovatch is the Senior Associate Dean for Scientific Computing and Data Science at the Icahn School of Medicine at Mount Sinai (ISMMS), founding the division in October 2011. She is also an Associate Professor for the Department of Genetics and Genomic Sciences, the Icahn Institute for Data Science and Genomic Technology and Pharmalogical Sciences. Kovatch is on the Organizing Committee for the CAFCW20.

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