Invited Speakers
Erwin Böttinger, M.D.
Director, Charles R. Bronfman Institute for Personalized Medicine
Professor, Medicine, Nephrology
Professor, Pharmacology and Systems Therapeutics
Informatics Solutions for Biomarker Research and Personalized Medicine in Clinical Care
Abstract The BioMe Biobank Platform is an EHR-linked clinical care cohort of 30,000 consented patients cared for by Mount Sinai doctors. BioMe is accredited by the College of American Pathologists (CAP) and applies informatics solutions to integrate a patient’s clinical care information and research data for genomic discovery and biomarker development. The CLIPMERGE Platform (Clinical Implementation of Personalized Medicine through Electronic medical Records and Genomics) is a tool for effective integration of genomic medicine in busy clinical care practices. CLIPMERGE overcomes multiple challenges for clinical integration of personalized medicine, including provider education gaps and negative impact on clinical workflow. Innovative pilots for real-time, point-of-care personalized medicine solutions through genome-informed clinical decision support enabled in electronic health records will be presented. The “Virtual Clinical Cohort” approach for biomarker development combines de-identified routine clinical care samples from Mount Sinai’s clinical laboratory linked via ‘honest broker’ mechanism with de-identified clinical information extracted from the EHR. The ‘virtual clinical cohort’ approach allows for rapid and cost-effective generation of large real-world sample collections with longitudinal clinical data. Proof of concept is demonstrated with the Chronic Kidney Disease Biomarkers Consortium funded by the National Institute for Diabetes and Digestive and Kidney Diseases (grant 5U01DK085688-05).
Biography Dr. Böttinger is a native of Germany where he obtained his M.D. degree from the University of Erlangen-Nuremberg in 1986. He trained in internal medicine and nephrology in the United States, including a Clinical and Research Fellowship in Nephrology at the Massachusetts General Hospital and Harvard Medical School. After additional research training at the National Cancer Institute, Bethesda, Dr. Bottinger joined the faculty at the Albert Einstein College of Medicine where he served as Director of the Albert Einstein Biotechnology Center. In 2004, he was recruited to the Mount Sinai School of Medicine in New York City where he currently holds an endowed chair as Irene and Dr. Arthur Fishberg Professor in Medicine. Dr. Bottinger served as Vice Chairman for Biomedical Research in the Department of Medicine, before he was appointed in 2007 as inaugural Director of The Charles Bronfman Institute for Personalized Medicine at Mount Sinai, an interdisciplinary institute to advance personalized health and healthcare. Dr. Böttinger is the Principal Investigator of Mount Sinai’s BioMe hospital-based Biobank and several NIH-funded national research consortia, including the Chronic Kidney Disease Biomarker Consortium (CKD BioCon), the electronic MEdical Records and GEnomics (eMERGE) network and the Implementing GeNomic medIcine in practice (IGNITE) network.
Zhiyong Lu, PhD
Earl Stadtman Investigator
Head, Text Mining Group
National Center of Biotechnology Information (NCBI)
National Library of Medicine (NLM)
National Institutes of Health (NIH)
Data and Text Mining for Knowledge Discovery in Biomedicine
Abstract The explosion of biomedical big data and information in the past decade or so has created new opportunities for discoveries to improve the treatment and prevention of human diseases. But the large body of knowledge—mostly exists as free text in journal articles for humans to read—presents a grand new challenge: bio-scientists around the world are increasingly finding themselves overwhelmed by the sheer volume of research literature and are struggling to keep up to date and to make sense of this wealth of textual information. Our research aims to break down this barrier and to empower scientists towards accelerated knowledge discovery. We will discuss our data- and text-mining research and its applications for improved access to the biomedical literature through PubMed. Moreover, we will discuss our novel competition-winning methods for biological named entity recognition and relation extraction in various biomedical texts such as clinical notes.
Biography Dr. Lu is an Earl Stadtman investigator at the National Institutes of Health, where he joined immediately after earning a PhD in Bioinformatics at the University of Colorado School of Medicine. His research group is developing computational methods for analyzing and making sense of natural language data in biomedical literature and clinical text. Several of his recent research has been successfully integrated into and widely used in PubMed and other NCBI web resources. Dr. Lu is an Associate Editor for BMC Bioinformatics and serves on the editorial board for the Journal Database. He is also involved in the organization of several international scientific meetings such as the BioCreative challenge series, PSB sessions on drug repurposing and crowdsourcing, and IEEE conference on health informatics.