SAGE Open Medicine Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). https://doi.org/10.1177/2050312117736228 SAGE Open Medicine Volume 5: 1–16 © The Author(s) 2017 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/2050312117736228 journals.sagepub.com/home/smo The life cycles of six multi-center adaptive clinical trials focused on neurological emergencies developed for the Advancing Regulatory Science initiative of the National Institutes of Health and US Food and Drug Administration: Case studies from the Adaptive Designs Accelerating Promising Treatments Into Trials Project Timothy C Guetterman 1 , Michael D Fetters 1 , Samkeliso Mawocha 2 , Laurie J Legocki 1 , William G Barsan 2 , Roger J Lewis 3 , Donald A Berry 4 and William J Meurer 2,5 Abstract Objectives: Clinical trials are complicated, expensive, time-consuming, and frequently do not lead to discoveries that improve the health of patients with disease. Adaptive clinical trials have emerged as a methodology to provide more flexibility in design elements to better answer scientific questions regarding whether new treatments are efficacious. Limited observational data exist that describe the complex process of designing adaptive clinical trials. To address these issues, the Adaptive Designs Accelerating Promising Treatments Into Trials project developed six, tailored, flexible, adaptive, phase- III clinical trials for neurological emergencies, and investigators prospectively monitored and observed the processes. The objective of this work is to describe the adaptive design development process, the final design, and the current status of the adaptive trial designs that were developed. Methods: To observe and reflect upon the trial development process, we employed a rich, mixed methods evaluation that combined quantitative data from visual analog scale to assess attitudes about adaptive trials, along with in-depth qualitative data about the development process gathered from observations. Results: The Adaptive Designs Accelerating Promising Treatments Into Trials team developed six adaptive clinical trial designs. Across the six designs, 53 attitude surveys were completed at baseline and after the trial planning process completed. Compared to baseline, the participants believed significantly more strongly that the adaptive designs would be accepted by National Institutes of Health review panels and non-researcher clinicians. In addition, after the trial planning process, the participants more strongly believed that the adaptive design would meet the scientific and medical goals of the studies. Conclusion: Introducing the adaptive design at early conceptualization proved critical to successful adoption and implementation of that trial. Involving key stakeholders from several scientific domains early in the process appears to be associated with improved attitudes towards adaptive designs over the life cycle of clinical trial development. Keywords Adaptive clinical trials, mixed methods research, Bayesian statistics, emergency medicine, neurology, clinical trials Date received: 17 March 2017; accepted: 18 September 2017 1 Department of Family Medicine, University of Michigan, Ann Arbor, MI, USA 2 Department of Emergency Medicine, University of Michigan, Ann Arbor, MI, USA 3 Department of Emergency Medicine, Harbor-UCLA Medical Center, Los Angeles, CA, USA 736228SMO 0 0 10.1177/2050312117736228SAGE Open MedicineGuetterman et al. research-article 2017 Original Article 4 Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 5 Department of Neurology, University of Michigan, Ann Arbor, MI, USA Corresponding author: Timothy C Guetterman, Department of Family Medicine, University of Michigan, 1018 Fuller ST, Ann Arbor, MI, 48104, USA. Email: tguetter@umich.edu