Phase I trials are critical for the development of anticancer drugs. They aim to identify the maximum tolerable dose (MTD) or recommended phase II dose quickly, while controlling the risk of toxicity [1, 2, 3]. To address this challenge, adaptive Bayesian approaches [4, 5] are appealing. They enable the incorporation of trial-external evidence, which increases inferential precision and leads to better informed decisions. They are also encouraged by Health Authorities. However, they are still rarely implemented in practice , and often not well understood.
This course addresses these issues via a practical Bayesian approach [7, 8] to single- and combination-agent designs that has gained industry-wide interest. The constituents are: parsimonious yet flexible dose-toxicity models; prior distributions that discount trial-external evidence [9, 10]; intuitive metrics for decision making; easy-to-use WinBUGS software; good communication among various stakeholders.
We discuss methodological aspects, use case studies for illustration, and provide basic WinBUGS code. The course provides a self-contained introduction to Bayesian Phase I cancer trials as currently used in practice. The course willbe structured as follows:
1. Introduction: Phase I Oncology trials, clinical and statistical challenges
2. Inference and Decisions
3. Single Agent Phase I Trials: methodology, case studies, implementation (WinBUGS), exercises
4. Historical Data Priors: meta-analytic-predictive (MAP) priors, MAP priors for Phase I studies,implementation (WinBUGS)
5. Phase I Combination Trials: methodology, case studies, implementation (WinBUGS), exercises
6. The Importance of Communication: communication with non-statisticians, review boards and regulatoryagencies, dose escalation meetings, protocol writing
7. Concluding Remarks and Discussion
 Hamberg, Verweij. Phase I drug combination trial design: walking the tightrope. JCO 2009;  Le Tourneau, Lee, Siu. Dose escalation methods in phase I cancer trials. JNCI 2009;  Tighiouart, Rogatko. Dose finding in oncology – parametric methods. In: Dose Finding in Drug Development; Tin (Ed), 2006.  Spiegelhalter, Abrams, Myles. Bayesian Approaches to Clinical Trials and Health-Care Evaluation. Wiley, New York, 2004;  Berry, Carlin, Lee, Müller., Bayesian Adaptive Methods for Clinical Trials. Chapman & Hall, Boca Raton, FL, 2010;  Rogatko, Schoeneck, Jonas et al. Translation of innovative designs into phase I trials. JCO 2007;  Neuenschwander, Branson, Gsponer. Critical aspects of the Bayesian approach to phase I cancer trials. Stat Med 2008;  A Bayesian Industry Approach to Phase I Combination Trials in Oncology. In: Statistical Methods in Drug Combination Studies, Zhao and Yang (Eds). Boca Raton, FL: Chapman & Hall/CRC Press, 2015;  Neuenschwander, Capkun-Niggli, Branson, Spiegelhalter. Summarizing historical information on controls in clinical trials. Clin Trials 2010;  Schmidli, Gsteiger, Roychoudhury, O’Hagan, Spiegelhalter, Neuenschwander. Robust meta-analytic-predictive priors in clinical trials with historical control information. Biometrics 2014