News

What Decisions Benefit from Model-Based Meta-Analysis (MBMA)?

Posted by Jeffrey Hane on May 31, 2017 3:47:13 PM

The primary rationale for model-based meta-analysis (MBMA) is to improve decision-making by better leveraging prior information from multiple sources. Decision-makers generally attempt to consider such prior information, but it is usually done in a relatively qualitative manner, and each individual decision-maker is usually aware of only a subset of the prior information. MBMA seeks to make the process more quantitative and comprehensive. The process and results of MBMA may be made visible (aka transparent) to the decision-makers. The end result is that the decision-makers are better informed, and they can contribute their knowledge to the modeling process leading to better, more trusted models and model-based inferences.

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Topics: Methodology, Tools, and Computation

Can methods based on existing models really aid decision making in non-small-cell lung cancer (NSCLC) trials?

Posted by Jonathan French on May 31, 2017 3:46:34 PM

I recently returned from the 2013 PAGE meeting in Glasgow. As usual, the scientific presentations were some of the best in the field of pharmacometrics. At this year’s meeting I was offered an opportunity to present some of our recent thoughts about model-based drug development in oncology.

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Topics: Methodology, Tools, and Computation, Oncology

Practice of Bayesian Analysis

Posted by Charles Margossian on May 19, 2017 2:31:50 PM

 

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Topics: Methodology, Tools, and Computation, Neurodegenerative Diseases