Improving Preclinical to Clinical Translation with Modern Metabolic Approaches


February 20, 2013
11:00 am – 12:30 pm EST

 

Sponsored by
Metabolon
 


Symposium Course Description: 

This webinar will convey how a deep understanding of the underlying biology is needed to drive clinical success. Understanding of the systems underlying biology through a high-throughput metabolic approach can provide essential insight for better target selection and biomarker identification in preclinical development. Further, studies that demonstrate the merits of this approach for translational science and clinical success will be detailed.

Learning Objective Bullet Points: 

  • Define translational challenges and clinical success for disease and demonstrate nutritional benefit
  • Understand the relevance that modern metabolic approaches bring to understanding underlying biology
  • Understand that these new approaches allow for achieving translation of preclinical findings to the clinic
  • Define translational challenges and a new paradigm for disease and nutritional clinical success

Who Should Attend: 

  • Preclinical Development
  • Clinical Development
  • Biomarker/Target Discovery
  • Epidemiology
  • Translational medicine
  • Molecular biology/medicine

Program Agenda: 

  • Moderator intro (3 min) – Welcome
  • Metabolon intro (12 min) – Translational challenges to clinical success
  • Lipomics approach (35-40 min) – Demonstrating how modern metabolomics applications have yielded success in overcoming translational challenges

Speaker Information: 

Steve WatkinsSteve Watkins, Ph.D., Chief Technology Officer
Lipomics Technologies
3410 Industrial Blvd Suite #103
West Sacramento, CA 95691 USA
530-400-8155
swatkins@metabolon.com 

Steve Watkins has studied how lipid metabolism is regulated and how nutrition and regulation affect chronic disease for the last 20 years. He received his Ph.D. from UC Davis in 1998 and developed technology for profiling lipid metabolites broadly and quantitatively during his post-doctoral work with Bruce German. Following a post-doc, Steve founded Lipomics Technologies, an early metabolomics company specializing in lipid metabolism. At Lipomics he served as Chief Executive and Chief Scientific Officer, until the acquisition of Lipomics by Tethys Biosciences, a diagnostics company with a focus on the prediction and prevention of diabetes, in 2008. Steve served as Chief Technology Officer for Tethys and was focused on the creation of new diagnostic tests employing both Lipomic and proteomic technologies. In 2011, Steve joined the Harvard School of Public Health as a Senior Visiting Scientist, working in the Department of Genetics and Complex Diseases with Gokhan Hotamisligil. Recently, he reacquired the Lipomics technology from Tethys, and merged Lipomics with Metabolon, the industry leading metabolomic profiling company. Steve currently serves as the Chief Technology Officer of Metabolon. Steve has authored over 60 papers on lipids and lipid metabolism along with several book chapters, and is a frequent speaker at national nutrition and metabolic disease meetings.

Speaker Information: 

Kirk BeebeKirk Beebe, Ph.D., Director of Application Science
Metabolon, Inc., 617 Davis Dr, Suite #400
Durham, NC 27713 USA
919-572-1711
kbeebe@metabolon.com 

Dr. Beebe received his Ph.D. in biochemistry from Ohio State University where he developed novel chemical biological approaches to understanding substrate selection for mammalian signaling proteins. Following this, he was a postodoctoral scientist and senior research associate at the Scripps Research Institute where he and Professor Paul Schimmel uncovered mechanistic links between genetic code translational fidelity and neurodegenerative diseases. Since then, Dr. Beebe has been an accomplished contributor within technology organizations, including Metabolon Inc. where he has driven several application areas forward for Metabolon’s metabolic profiling technology. Chief among these are the metabolism of proliferative cells and the application of Metabolomics in biomarker discovery.



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