Practical guidance for running late-phase platform protocols for clinical trials: lessons from experienced UK clinical trials units

Journal article

BACKGROUND: Late-phase platform protocols (including basket, umbrella, multi-arm multi-stage (MAMS), and master protocols) are generally agreed to be more efficient than traditional two-arm clinical trial designs but are not extensively used. We have gathered the experience of running a number of successful platform protocols together to present some operational recommendations. METHODS: Representatives of six UK clinical trials units with experience in running late-phase platform protocols attended a 1-day meeting structured to discuss various practical aspects of running these trials. We report and give guidance on operational aspects which are either harder to implement compared to a traditional late-phase trial or are specific to platform protocols. RESULTS: We present a list of practical recommendations for trialists intending to design and conduct late-phase platform protocols. Our recommendations cover the entire life cycle of a platform trial: from protocol development, obtaining funding, and trial set-up, to a wide range of operational and regulatory aspects such as staffing, oversight, data handling, and data management, to the reporting of results, with a particular focus on communication with trial participants and stakeholders as well as public and patient involvement. DISCUSSION: Platform protocols enable many questions to be answered efficiently to the benefit of patients. Our practical lessons from running platform trials will support trial teams in learning how to run these trials more effectively and efficiently

Authors: Love, SB; Cafferty, F; Snowdon, C; Carty, K; Savage, J

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: BioMed Central
• Journal: Trials
• Volume: 23
• Issue: 1
• Pages: 757-757
• Article number: 757
• Publication date: 2022-09-06
• DOI: 10.1186/s13063-022-06680-4
• EISSN: 1745-6215
• ISSN: 1745-6215
• Language: English
• Keywords: Clinical trial; Staffing; Set (abstract data type); Computer science; Medicine; Process management; Alternative medicine; Engineering; Nursing; Protocol (science)