Use of Prior Information (Clinical, Pre-clinical and Models) to Improve Efficiency and the Efficacy Estimates Roseann M. White, MA Director of Clinical Trial Statistics Duke Clinical Research Institute

Disclosure Statement of Financial Interest Within the past 12 months, I or my spouse/partner have had a financial interest/arrangement or affiliation with the organization(s) listed below. Affiliation/Financial Relationship Company Employee Consulting Fees/Honoraria Other Financial Benefit Duke Clinical Research Institute Claret Abbott, Abbvie

Acknowledgements Dawn Bardot, Ph.D., VP, MDIC Dan Schwartz, M.S., PM, MDIC Tarek Haddad, Ph. D., Director, MDT Mitchell Krucoff, M.D., F.A.C.C., DCRI/VA

Those who fail to learn from history are doomed to repeat it Winston Churchill modifying a quote from George Santayana

Agenda Quick review of exchangeability clinical examples Conclusion

former executive, president, and chair of Hewlett-Packard Co. The goal is to turn data into information, and information into insight. Carly Fiorina former executive, president, and chair of Hewlett-Packard Co.

Strategy Planning Stage: Regulatory, Science, Statistics agree on This type of planning can happen at any time during the development process – its never too early or too late Strategy Planning Stage: Regulatory, Science, Statistics agree on your labeling about the product about safety, efficacy and effectiveness Before you begin a non-clinical or clinical study, Regulatory, Science, Statistics agree on How the data collected in this study will fit into a coherent body of evidence about the product safety, efficacy and effectiveness Aggregating data from several similar studies will help to turn the data into information and insight about the product but it needs to be considered before the study is run.

Statistical Methods for Aggregating Data Underlying assumption for all data aggregation methods: exchangeability One is sampling from the same underlying population (patients, animals, materials, etc.)

Bayesian Methods Bayesian methods of data aggregation are processes where continuum of data sets with the outcome being studied are combined to improve estimates

Aggregating Using Bayesian Methods Historical Historical Historical Current Current Current

Non-clinical Study Examples

Non-clinical Stability Studies From Stan Altan, Senior Director and Fellow, Janssen R&D, presentation at Rutgers, 2009 on the use of Bayesian methods for stability studies Are the regulatory guidelines reflective of current technology and statistical practice? This is the right time to question the pooling paradigm Are we stuck in a Hypothesis Testing /Equivalence Testing rut? Bayesian approach Provides mechanism to include prior information to the statistical analysis of current data and to update model parameter estimates as new data are collected A more natural way to approach to CMC decision making in terms of a posterior predictive distribution

Clinical Study Examples

Approval of Stents MULTI-LINK TETRA(tm) Coronary Stent System approval was based on the use of bayesian priors from DUET and Multilink Approved using 100 pts in-hospital outcomes 6 months from start of enrollment to submission Boston Scientific ION stent Paclitaxel-Eluting Platinum Chromium Coronary Stent System 1/3 of patients were contributed from the TAXUS IV RCT

Conclusion Rather than just submitting individual studies on a particular topic, aggregating the results to improve the accuracy and precision of the results will provide FDA with that coherency Data aggregation methods can be applied to both non-clinical and clinical studies However it requires close collaboration among, science statistics and regulatory during the entire product development life cyle