Data in Clinical Research
Data science is good for researchers, good for innovation, and good for public health.
Clinical research generates tremendous amounts of valuable data. However, for decades, this priceless information has been largely unavailable to the wider community of researchers and its full benefit has gone unrealized. By unlocking these vast storehouses of data, we open a new world of possibilities in which the search for new treatments is accelerated and a better understanding of human health and illness is within reach.
The question at the center of the open-science discussion is not whether data should be shared, but how we can develop responsible methods for doing so. Our collaboration with partners in industry, academia, and other spheres will allow data to be shared in ways that can improve public health worldwide.
Michael J. Pencina, PhDVice Dean for Data Science and Information Technology, Duke University School of Medicine
"What if we found new ways to use existing data to improve clinical research and patient care?"
Creating A Common Data Model Across PCORnet
Keith Marsolo, PhD, explains why it is critical to standardize data before using it to answer questions in research, and sheds light on how DCRI is approaching this work via the PCORnet, the National Patient-Centered Clinical Research Network. Learn more about Marsolo's work on the common data model by reading this article. PCORnet is the Patient-Centered Outcomes Research Institute's (PCORI) initiative to improve the nation’s capacity to conduct patient-centered comparative clinical effectiveness research more efficiently by harnessing the power of large amounts of health data and patient partnerships. DCRI is the coordinating center for PCORnet.
Making Sense of Big Data
Researchers today have access to tremendous amounts of data. But how can they make the best use of this information? Michael Pencina, PhD, writes in STAT about the common mistakes people often make when dealing with big data.
Efficiencies for Open Data
Frank Rockhold, PhD, writes in Clinical Trials about why open data is so important to clinical research and outlines suggestions for streamlining data sharing processes.
The Potential of Machine Learning
In a JAMA Viewpoint piece, Eric Peterson, MD, MPH, writes that a focus on adoption of new models is needed in order to fully leverage the potential that machine learning offers.
Biomedical Data Science Across the University
The DCRI's Laine Thomas, PhD, discusses the future of biomedical data science at Duke, as well as the role the DCRI can play, with David Page, PhD, chair of Duke Biostatistics & Bioinformatics.
Frank Rockhold, PhD
Professor of Biostatistics and Bioinformatics
Frank Rockhold, PhD, is a professor of biostatistics and bioinformatics at the DCRI. A leading biostatistician in the pharmaceutical industry, Rockhold has more than 30 years of diverse experience in clinical trial design, data monitoring, decision sciences, statistical research, and epidemiology.
Rockhold was most recently senior vice president of Global Clinical Safety and Pharmacovigilance at GlaxoSmithKline, and prior to that ran Cardiovascular and Metabolic Development and the Biostatistics, Epidemiology and Healthcare Informatics departments. Earlier in his career, he held positions with Merck Research Laboratories and Lilly Research Laboratories.
He served on the board of directors of the Clinical Data Interchange Standards Consortium, most recently as Chairman, is past president of the Society for Clinical Trials, is a fellow of both the American Statistical Association and the Society for Clinical Trials, and is an accredited professional statistician. Rockhold received his PhD in biostatistics from the Medical College of Virginia, his ScM in biostatistics from The Johns Hopkins University, and his BA in statistics from the University of Connecticut.