A note regarding the special issue on innovative design and analysis of complex clinical trials and opportunities for future research

Abstract

The special issue on innovative design and analysis of complex clinical trials (Volume 30, Issue 6) is a compilation of invited papers from speakers at the April 2019 Duke-Industry Statistics Symposium on “Innovative Design and Analysis of Complex Clinical Trials for Drug and Device Developments.” This issue covers a wide variety of topics and is a recommended read for statisticians who are practitioners in the field of drug development. Some common themes in this issue include dose finding trials utilizing both efficacy and toxicity (adaptive) platform trials, and practical considerations for designing Bayesian sequential or adaptive trials. For statisticians working on immunotherapies or cell therapies, four papers on dose finding trials address some challenging issues germane to these areas. In one paper, the trial design accounts for late-onset toxicities in Maximum Tolerated Dose (MTD) determination (Andrillon et al. 2020). In recognition of the limited understanding of doseresponse relationship, several papers proposed dose finding trials that consider both efficacy and safety outcomes for dose selection (Lin and Ji 2020; Yin and Yuan 2020; Li et al. 2020). Furthermore, emerging topics on platform trials are talked about in two papers. The paper by Bai et al. (2020) explores multiplicity issues for sharing a control arm while in Ivanova et al. (2020) discusses key elements of utilizing cross-over design under a master protocol. Last but not the least, adaptive designs were discussed in various settings, including paediatric studies (Psioda and Xue 2020), enrichment trials (Joshi et al. 2020; Wang et al. 2020) and sequential designs (Ivanova and Qaqish 2020; Wei et al. 2020), to name a few. The number of statistical issues that emerge in clinical trial designs and operations are innumerable. Yet, the wide variety of topics covered by this issue is not expected to span across all innovative designs of interest and its aspects. One prominent topic not illustrated in this special issue is on incorporating real-world evidence (RWE) in the design and analysis of clinical trials. Trialists are interested to expand the RWE utilization throughout the clinical development program including in support of new drug approval. The explicit mention of the use of RWE in drug development in the 21 Century Cures Act (Public Law 114–255, 2016) has increased interest in this area. However, it is to be noted that Sec. 3022 of the 21 Century Cures Act (Public Law 114–255, 2016) only mentions the use of RWE in support of approval for new indication for already approved drugs and to help support or satisfy post-approval study requirements. Scientific publications, regulatory discussions (e.g. Food and Drug Administration (FDA) 2017, FDA 2019a and FDA 2019b) and cross-functional discussions are becoming increasingly abundant in this fast-developing area. It is imperative to reflect on the basic principles that affect the successes or failures of utilizing RWE and statisticians’ role in facilitating sound study design within this changing regulatory environment. Prominent among the list of issues is the ability to make causal estimates of effect and how data and associated biases make that challenging. Of note, the Journal of Biopharmaceutical Statistics (JBS) is still accepting manuscript submissions for