This type of analysis involves pooling proprietary data across relevant clinical trials to provide the team with the best estimate of drug effects based on the cumulative information collected during development.  Such analyses are typically undertaken at the end of development (e.g., Integrated Summary of Safety / Integrated Summary of Efficacy).  However, performing pooled analyses early in the course of development can provide considerable insight leading to early data driving decisions.  Utilizing pharmacologically based models allows for a rational method for analyzing data across trials that evaluated different doses, regimens, and/or patient populations.

The Great Lakes Drug Development team considers 3 levels of data analysis and interpretation to support decision-making utilizing traditional statistics and model based analysis.  Together, the 3 levels provide a foundation for informed, data-driven, quantitative decision making.  This adaptive drug development approach accelerates the accumulation of knowledge vs. traditional approaches

Making the Most of Available Data:
Text Box: The 1st level is the TRIAL. Text Box: The 2nd level is the drug development PROGRAM. Text Box: The 3rd level is the COMPETITIVE ENVIRONMENT.

In this case relevant data from literature reviews are pooled with proprietary clinical trial data to understand better the effects of the new compound relative to the competitive environment.  This quantitative insight can be useful when considering go / no go decisions and Phase 3-4 strategies.

Analyses at this level utilize data collected from the trial of interest and are limited to addressing questions specific to that trial.  This type of analysis is routinely undertaken across the pharmaceutical industry.