2016年11月11日，美国IPQ Analytics创始人、中心客座教授Michael Liebman教授访问中心并做题为“Enhanced Diagnosis and Stratification in Heart Failure: Application of Network-based Analytics to Real World Data” 的报告。
Michael Liebman 介绍：
MICHAEL N. LIEBMAN, PhD, is a leading scientist and thought leader in the field of biomedical informatics with many years of academic and corporate experience. He serves on 14 scientific advisory boards, including the PhRMA Foundation and is on the Board of Directors of the Nathaniel Adamczyk Foundation for Pediatric ARDS. Michael has been the Managing Director of Strategic Medicine, Inc after serving as the Executive Director of the Windber Research Institute since November, 2003. Previously, he was Director, Computational Biology and Biomedical Informatics at the University of Pennsylvania Cancer Center since September, 2000. He served as Global Head of Computational Genomics at Roche Pharmaceuticals and Director, Bioinformatics and Pharmacogenomics at Wyeth Pharmaceuticals, Director of Genomics for Vysis, Inc. He was a co-founder of Prosanos, Inc (2000), which became part of United BioSource Corporation in 2011. He was on the faculty of Mount Sinai School of Medicine in Pharmacology and Physiology/Biophysics. He is an Invited Professor at the Shanghai Center for Bioinformatics Technology. Michael is Chair of the Informatics Program of the PhRMA Foundation and also Chair of its new program in Translational Medicine and Therapeutics and is a member of the PhRMA Scientific Advisory Board. He is on the Advisory Board of the International Society for Translational Medicine and on the Editorial Board for the Journal of Translational Medicine, for Clinical and Translational Medicine and for Molecular Medicine and Therapeutics. His research focuses on computational models of disease progression stressing risk detection, disease process and pathway modeling and analysis of lifestyle interactions and causal biomarker discovery and focuses on moving bedside problems into the research laboratory to improve patient care and their quality of life. He received a PhD in physical chemistry and protein crystallography from Michigan State University in 1977.
The diagnosis of heart failure is comprised of two equivalent patient populations, presenting either reduced ejection fraction or preserved ejection fraction. The threshold separating these categories remains somewhat subjective, typically ranging between 40 and 50%, but more importantly, successful therapeutic intervention only exists for patients with reduced ejection fraction. The critical need to improve management of 50% of all heart failure patients has led to our application of the IPQ Disease Model to examine the guidelines and processes for disease diagnosis and treatment.
In our analysis, we have evaluated the complexity of real world patients and real world clinical practice. Thus clinical history, co-morbidities, family history, etc are all relevant confounders of both the diagnosis and potential for predicting response to treatment as well as physician adherence to guidelines, quality of specific diagnostic procedures, limited incorporation of full clinical observables, etc.
We have developed an approach that goes beyond a “big data” analysis to more closely represent conventional clinical protocols so that the results of this analysis can more readily be integrated into clinical practice.
The unique integration of this approach with non-parametric graph analysis methods has enabled the stratification of patients in clinical studies well beyond that accessible through standard statistical analysis. The development and application of this study will be presented as well as its potential for generalized application to other diseases, including both complex disorders and syndromes.