“I feel so fortunate to be a part of the CTSA and N3C communities that demonstrate the best of humanity and the power of team science with hundreds of scientists, clinicians, and informaticians volunteering their time and expertise to address the COVID-19 pandemic.”

“The Translational Research Institute at UAMS is very excited to be part of the N3C initiative. This data-sharing resource provides the opportunity to better understand the national impact of COVID-19 on the health of vulnerable populations. We are particularly interested in using this platform to compile a novel resource for radiology images of COVID-19 patients. This initiative, led by Fred Prior, will support both research and the education of trainees. Under John Arthur’s leadership, we will also use N3C to better understand the impact of COVID-19 on renal function and identify risk factors that will allow us to personalize future COVID-19 treatments. We envision a number of other research endeavors with colleagues in the College of Public Health using clinical data from all 60 CTSA institutions to develop effective treatment and prevention strategies for the future.”

“Only with the support of our CTSA consortium and N3C partners and collaborators can we achieve our goal of having a centralized national data repository and analytics platform with the power of Big Data to help assess, predict, and identify the most successful approaches that could have direct impact on curbing this yet-to-be cracked pandemic.”

“The coronavirus pandemic has spurred us to build, for the first time, a process for collecting and harmonizing electronic health records from many different institutions, storing it in one secure location, and making it available in a collaborative platform for use by diverse experts. No one’s ever created a dataset like this in the history of the United States.”

“As the co-lead of the Portals and Dashboards subgroup with Dave Eichmann at University of Iowa, my experience engaging with N3C has been very smooth, in spite of the urgency and very short timelines. Self-directed tutorials are now available through Palantir, the NCATS hosted platform for the N3C Enclave. For anyone who has not yet joined a workstream or a subgroup, I definitely encourage you to do so! There is a lot to do and a large capacity for contributing to our institutional data and knowledge for solving important national and global COVID-19 problems.”

“I have been excited about N3C since I first heard of the concept. I was delighted to have UNC support N3C with effort from our Informatics group led by Emily Pfaff. I have helped engage others in the process of getting the wider community of investigators on board. Now I am beavering away trying to leverage N3C to understand the problem of severe outcomes from COVID-19 in patients with diabetes. It has been inspiring to play a small role with a cast of hundreds in this groundbreaking innovation to address the biggest threat the world has faced in my lifetime.”

“I am really excited about N3C, not only because it will provide wide and wise access to data that enables many professional and citizen scientists to find important relationships among COVID19 infection, clinical features, other medical conditions, and social-environmental circumstances—but also because I hope it will serve as a model for the provision of data concerning so many other national health crises as wide-ranging as asthma to sickle cell disease. N3C shows that as a nation we can decide to share data for our common good.  Let’s build on its success to speed health improvement and disease prevention for all Americans.”

"The N3C establishes the precedent for EHR data integration on a secure enclave to support clinical discovery enabled by collaborative, large-scale, computationally-intensive data science. We believe that there’s an enormous amount of talent, not just in academic medical centers, but in computer science departments, data science departments, social studies departments. We may transform the way clinical science is done, leveraging the tools and resources of big data and data science in ways that have not been possible.”