The High Throughput Data Problem: Hypothesis Generation and Phenotype Modeling in Translational Research by Philip R. O. Payne, Ph.D.
Personalized healthcare depends on the ability to link biomarkers and a patient’s phenotype to identify risk factors, diagnose diseases, or plan for the treatment. Recent innovations in the bio-molecular sciences have created unprecedented opportunities for the generation of high-throughput biomarker data. Unfortunately, the ability to use clinical and research information systems to generate large-scale phenotypic data is less well developed. In addition, there is a need to support high-throughput hypothesis generation and testing methods with respect to the multi-dimensional data sets. This presentation will review research and development efforts in the preceding areas at the Center for Translational Research Computing, a research unit spanning OSU’s Department of Biomedical Informatics and Center for Clinical and Translational Science. This work focuses on 1) the use of conceptual knowledge engineering techniques, using knowledge collections such as ontologies, terminologies, and extracts from public databases and literature repositories, to reason about large-scale integrative data sets and generate novel hypotheses linking biomarkers and phenotypes; and 2) the application of human-factors analyses and formal knowledge acquisition techniques to improve our understanding of how to optimally capture high-throughput phenotypic data at the point-of-care.
Dr. Payne is currently an assistant professor in the Department of Biomedical Informatics at The Ohio State University. He also serves as the Director of the Biomedical Informatics Program for OSU’s CTSA-funded Center for Clinical and Translational Science, Co-Director of the Biomedical Informatics Shared Resource within the OSU Comprehensive Cancer Center, and as the Translational Research Informatics Architect for the Ohio State University Medical Center. Dr. Payne received his Ph.D. with distinction in Biomedical Informatics from Columbia University, where his research focused on the design and evaluation of advanced information management platforms for clinical and translational research. Dr. Payne’s research portfolio is broadly situated within the OSU Center for IT Innovation in Healthcare (CITIH), where he serves as the primary scientific leader of a group of over twenty researchers, developers, and trainees who are actively supported by a combination of NCRR, NLM, and NCI awards and contracts. In 2007, Dr. Payne’s national leadership in the domain of clinical research informatics was recognized when he was selected to co-chair the American Medical Informatics Association’s (AMIA) Clinical Research Informatics Steering Task Force, which is currently involved in defining AMIA’s objectives for establishing itself as the preeminent professional home for Clinical Research Informatics researchers and practitioners.