Reduce Study Cost by Modeling and Controlling Study Design Cost Drivers


October 4, 2011
11:30 – 1:30 pm EST

 

 

Symposium Course Description:
Clinical study design drives clinical study cost yet few clinical studies benefit from modeling the costs of specific design features. Modeling these costs makes it possible to control them through the study design while simultaneously preserving the scientific and commercial objectives of a study. This webinar will present a methodology that you can use immediately for objectively and quantitatively modeling and controlling study cost. The methodology begins with a model for a "base case" study and then adds cases to capture the full range of certainty around the base case. The modeling reveals which design features drive the study cost and which have potential for reducing study cost while preserving study objectives. Guided by this modeling, the study designer can revise the design to save money while preserving objectives. Examples from oncology, with a biomarker, and other therapeutic areas will be presented.

Learning Objective:
1. Understand how to formulate a study design as "base case," "best case," and "worst case."
2. See how to assign cost under various scenarios to specific components of the study design.
3. Evaluate study design features and cost to understand how to maintain study objectives while potentially lowering the study cost.

Who Should Attend:  Clinicians, pharmacologists, statisticians, operations specialists, sourcing specialists and finance specialists working in clinical development.

Instructor Information: 
Michael C. Palmer, President, Adaptive Pharmacogenomics, LLC
Michael, in his role leading Adaptive Pharmacogenomics, has been working with the U.S. Food and Drug Administration (FDA) since 2005 on software tools to help assess the cost and complexity of clinical trials. In the initial contracts with the FDA, APG developed spreadsheet tools to assess the complexity and cost of clinical studies for targeted therapies. In 2006, the FDA began discussions with Michael and GlaxoSmithKline about expanding the scope of this work to include interaction studies in a web-based software tool. In 2008, those discussions were successful and the FDA signed a Cooperative Research and Development Agreement (CRADA) with APG and GSK. After two years of intensive work, the CRADA successfully concluded. Michael graduated from the University of Michigan with an MS in biostatistics in 1979 and has worked in clinical research and development in the pharmaceutical industry since then.


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