Innovative designs of clinical trials have the advantage of flexibility over traditional designs while maintaining the integrity of the trials. The novel designs could expedite drug development or have ethical benefits for the trial participants, but the uptakes of the innovative designs in practice are not as broad as the traditional designs. This invited paper session invites five experts in the topic area of innovative designs and statistical inference to present new findings of their cutting-edge research and to discuss the implication of those new results from a practical perspective. This session will provide a platform to exchange ideas between pharmaceutical industry experts and academic professionals, which may foster new ideas of research and help boost uptakes of novel designs of clinical trials in practice.

Innovative designs of clinical trials have the advantage of flexibility over traditional designs while maintaining the integrity of the trials. The novel designs could expedite drug development or have ethical benefits for the trial participants. These novel designs use the cumulated information collected during the trials to sequentially make changes to the Alpha spending function or randomization probabilities or other aspects of the designs to improve the efficiency of the designs or to benefit trial participants. However, the uptakes of innovative designs in practice are not as broad as the traditional designs. One of the hesitations in adopting those designs is the concern about the validity of statistical conclusions for the design and the possible loss of efficiency due to the modification of the trials. The modification of a trial proposes challenges to the estimation of treatment effects and in the control of the possible inflation of type I error rate. It is important to have valid statistical inferential methods established for the designs to ensure the inferential properties and efficiency of the designs probably by integrating the inferential properties of treatment effect estimate with design features. The aim of this invited session is to create an opportunity for the front runners in innovative designs of clinical trials to exchange ideas and disseminate research findings.

This session invites five experts in the topic area to talk about and discuss their cutting-edge research findings on innovative designs and statistical inference for clinical trials. Two of the invited experts will serve as discussants, Dr. Xikui Wang, a long-term full professor at the University of Manitoba, and Dr. Alex Sverdlov, a senior director statistical scientist from Novartis Pharmaceuticals Corporation in the U.S. The two discussants are senior professionals with extensive experience in the design and conduct of clinical trials.  The three speakers have expertise in novel designs of clinical trials and statistical inference with diversified academic backgrounds, Dr. Xuekui Zhang, a Tier 2 Canada Research Chair at the University of Victoria, Dr. Leilei Zeng, a full professor at the University of Waterloo, and Dr. Li Xing, an assistant professor at University of Saskatchewan. This invited session adopts the format of three speakers and two discussants, which will offer the opportunity for a timely critical appraisal of the newly presented research results from a practical perspective. 

This session will provide a platform to discuss the implication of the new theoretical findings, exchange ideas between academic professionals and industry experts, and explore possible issues in the application of the novel designs in practice. The interaction between academic and industry experts may foster new ideas for research on study designs from a practical perspective. It may help shape the research direction of innovative designs for clinical trials and boost the uptakes of those novel designs in practice in the future.

Organiser: Yanqing Yi 

Chair: Yanqing Yi 

Speaker: Dr Xuekui Zhang 

Speaker: Yanqing Yi  

Speaker: Xikui Wang

Discussant:  Alex Sverdlov