Modeling as a framework for knowledge synthesis.

Modeling as a framework for knowledge synthesis.

A comprehensive, interdisciplinary synthesis and interpretation of data should play a central role in Pharma R&D. Knowledge synthesis is essential for the development of effective research and development plans, for the proper design and analysis of studies, and for successful regulatory submissions.

Cross-functional, interdisciplinary knowledge synthesis is, however, lacking in many development programs. Instead, various functional areas are assigned to write separate and distinct sections of investigator brochures, team presentations, and early R&D plans. Each section reflects the group that prepared it. “Synthesis” is merely a compilation of facts and study results.

This lack of cross-functional knowledge synthesis has two important consequences: 1) knowledge gaps are not identified and rectified, and 2) research plans are developed based on intuition rather than explicit synthesis of knowledge. The result can be erroneous assessments of the value of drug assets, causing allocation of resources to unworkable development programs.

The task of knowledge synthesis becomes ever more difficult as our understanding of the pathophysiology of disease and of the pharmacokinetics and pharmacodynamics of candidate compounds expand at an exponential rate. No longer can one scientist, however accomplished, understand the entire project, discern its weakest point, and imagine the proper remedy, as did inventor Elmer Sperry. A framework for synthesis of the enormous amount of knowledge generated during a drug development program is needed. That framework can be provided by pharmacometric modeling and simulation.

Modeling and simulation are valuable for gaining an understanding of the pharmacokinetics and pharmacodynamics of a drug beyond that provided by noncompartmental analyses. Pharmacokinetic models not only provide information about absorption, distribution, metabolism, and excretion of a drug, but also provide insight into the pathophysiologic factors affecting the drug’s dose–concentration relationship. Pharmacodynamic models describe the time course of drug effect and help identify differences in safety and efficacy outcomes across population subgroups that cannot be realized from traditional “change from baseline, last observation carried forward” analyses.

The knowledge synthesis provided by pharmacometric models can further a mechanistic understanding of the determinants of efficacy and safety outcomes and can play a critical role in the design of development programs, both for new molecular entities and for older compounds being studied for new indications.

Are you hooked? Visit the Knocked My Socks Off! blog for more ideas about Elmer Sperry. And, be sure read the next Pharma of the Future? blog entry, Excellence is a team sport.