Prior, at Rosetta Inpharmatics, he pioneered novel algorithms and genomic applications including the 70-gene breast cancer prognosis classifier as basis for the FDA-approved MammaPrint test. He was also responsible for developing new platforms and data integration strategies for biomarker identification, mechanism of action elucidation, predictive & translational safety modeling. Prior to Inflammatix, he led Computational Biology/Bioinformatics teams at Amgen and Merck as Scientific Director to advance multiple programs for drug R & D pipeline in areas of target discovery & liability assessment, lead optimization, safety issue resolution & enablement of IND fillings. Yudong is VP of Computational Biology at Inflammatix, focusing on research for novel multi-gene molecular diagnostic signatures. Liesenfeld has authored more than 160 articles in peer-reviewed journals and more than 30 book chapters. He also completed a postdoctoral fellowship in the Division of Infectious Diseases and Geographic Medicine at Stanford University.
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med) degree from the Free University of Berlin, Germany and completed his residency in medical microbiology and infection epidemiology at the Charite Medical School, Berlin. Liesenfeld previously served as associate professor of Medical Microbiology and Infection Immunology at the Charite Medical School in Berlin, Germany, where his research focused on the immune response to infections. His team designed and executed numerous clinical trials to support regulatory approvals and commercialization of the company’s broad product portfolio, including the LightCycler® SeptiFast test for use in sepsis diagnosis.ĭr. As chief medical officer at Roche Molecular Diagnostics, he built a state-of-the-art medical department and led the company’s clinical science, medical affairs, clinical operations and biometrics functions. He has over 25 years of industry and academic experience in the diagnostics field, with a focus on molecular diagnostics and infectious diseases. Liesenfeld is an expert in the field of microbiology, infectious diseases and the host response.
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Khatri has authored or co-authored more than 140 papers and holds 30-plus patents. Using these methods, he has identified highly specific and sensitive biomarkers for: (1) infectious diseases (sepsis, respiratory infections, tuberculosis), (2) acute solid-organ transplant rejection, and (3) cancer (pancreatic cancer, small cell and non-small cell lung cancer, mesothelioma). His most recent work focused on developing computational methods for integrated, multi-cohort analysis of publicly available data to increase sample size, as well as better account for the heterogeneity observed in real world patient populations. Khatri developed the first ontology tool for analysis of microarray data, named Onto-Express, and has expanded into a suite of web-based open access tools, Onto-Tools.
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He is well-known for his work on ontological and pathway analysis of high-throughput molecular, genomics, and proteomics data. Khatri possesses more than 15 years of experience in bioinformatics, computational biology, and translational medicine.