Michael N. Liebman is a leading scientist in the field of biomedical informatics. 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.
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 and the International Park for Translational Biomedicine (Shanghai). He is also an Adjunct Professor of Pharmacology and Physiology at Drexel College of Medicine and Adjunct Professor of Drug Discovery, First Hospital of Wenzhou Medical University.
What will you talk about at InnovationWell Philadelphia?
Precision medicine meets imprecise medicine. The vast majority of my colleagues who talk about ‘Precision Medicine’ don’t understand how real medicine is practiced. There is absolute disconnect. A simple example: my genomics friends see a mutation and think we will be able to use CRISPR to fix it. But we’ve known the gene that causes sickle cell anemia since 1955 and we still can’t fix it. Another example: there have been three very large studies on hypertension associated with a gene. Each study found genes responsible, but with very little consistency because the way they select patients is by blood pressure and there are 20 different ways to measure blood pressure. That’s a variation of 20 or more points. Humans don’t want to deal with complexity and, unfortunately, the world is complicated. Everybody is trying to do good science but it’s like pushing Jello.
Who would you like to see at InnovationWell?
Ideally, it would be a mix. First, pharma: R&D, clinical developers, medical affairs… They never talk to one another, but they have the same needs. Second, people from government agencies. Third, investment bankers because they evaluate the risks for biotech/drugs and can either short a stock or identify what shouldn’t be ignored.
What powerful question would you like to answer?
How much can you believe that a diagnosis merits a certain treatment?That is the weakest part of the process. We often depend on a diagnosis without understanding the disease. From our modelling, we should be able to develop very appropriate diagnostics because of the etiology.