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Columbia University CTSA Program Hub Innovations: Operating a Clinical Research Unit in the COVID-19 Era and Building a COVID-19 Biobank
Heather Seid, MS, RDN (1); Sheila O’Byrne, PhD (2); Elisabeth DiMaria, MHA (1); Ismael Castaneda, MS, BSN (1); Dianne Frederick (1); Janelle Nunez (1); Ariella Kelin, MSRN (3); Josh Wansley, MSRN (3); Danielle Pendrick, DrPH (4); Jennifer Williamson, MS, MPH (5); David Goldstein, PhD (2); Krzysztof Kiryluk, MD (2); Ronald Wapner, MD (6); Alexander Fedotov, PhD (1); Wendy Chung, MD, PhD (7); Sudha Kashyap, MD (7); Karen Marder, MD, MPH (8); Michael Rosenbaum, MD (7); Muredach Reilly, MBBCh, MSCE (1,2)
(1) Irving Institute for Clinical and Translational Research, New York, NY 10032; (2) Columbia University Irving Medical Center, Department of Medicine, New York, NY 10032; (3) NewYork-Presbyterian Hospital, New York, NY 10032; (4) Columbia University Irving Medical Center, Department of Pathology and Cell Biology, New York, NY 10032; (5) Columbia University Irving Medical Center, Vagelos College of Physicians and Surgeons, Office for Research, New York, NY 10032; (6) Columbia University Irving Medical Center, Department of Obstetrics & Gynecology, New York, NY 10032; (7) Columbia University Irving Medical Center, Department of Pediatrics, New York, NY 10032; (8) Columbia University Irving Medical Center, Department of Neurology, New York, NY 10032
The Irving Institute for Clinical and Translational Research (Irving Institute) is home to Columbia University’s Clinical Translational Science Award (CTSA) Program Hub in New York City (NYC). By April of 2020, NYC had become the United States’ COVID-19 epicenter. In response to the pandemic, the Irving Institute was confronted by several significant issues, including 1) developing a comprehensive biobanking protocol for genetic, molecular, and translational studies of COVID-19, 2) triaging ongoing clinical research to maximize participant safety and project sustainability, and 3) expanding opportunities for COVID-related clinical research to identify novel diagnostic, therapeutic, and preventive interventions. We will highlight innovative responses from the Irving Institute Precision Medicine Resource (PMR) and Clinical Research Resource (CRR).
Early on in the COVID-19 pandemic, the PMR and CRR applied algorithmic approaches to 1) create a comprehensive biobanking protocol and database, 2) triage ongoing clinical research into projects that should be suspended based on risk: benefit ratio analyses; could be continued after relocation into identified lower COVID-risk environments, or the cessation of which would be seriously detrimental to participants, 3) identify areas and streamline opportunities to implement priorities COVID-related research.
By April of 2020, the PMR launched the Columbia University Biobank (CUB) and began enrolling participants and accepting samples. Currently, CUB has successfully collected over 75,000 biological samples from over 11,000 COVID-19 patients by utilizing innovative methods to overcome recruitment barriers amid the crisis, perform large-scale collections of biospecimens with matching phenotype data, address biosafety challenges, generate genomic and transcriptomic data, and comply with privacy protection-related regulatory issues.
Also, by April of 2020, the CRR triaged over 150 active clinical research studies (120 adult, 36 pediatric; 124 using the out-patient and 32 using the in-patient CRR) such that 12 in-patient studies were relocated to the out-patient resource, 19 were continued in lower-risk environments (such as homes and other venues), and 4 were deemed to have a sufficiently favorable risk-benefit ratio to bring into the Irving Institute clinical research space. Separate units were created for COVID-related research based on the COVID-status (contagious, previously infected, etc.) with expedited reviews of COVID-protocols by the CRR.
The Columbia CTSA Program hub’s approaches to biobanking, ongoing clinical research, new COVID-related research, and new COVID-related biobanking successfully adapted to a fluctuating environment including caseloads, demand for hospital beds, and new diagnostic, preventative, and treatment-related protocols. These algorithms could potentially be applied in other emergent situations.