Trials (Jan 2020)

Streamlining and cycle time reduction of the startup phase of clinical trials

  • Amani Abu-Shaheen,
  • Ahmad Al Badr,
  • Isamme Al Fayyad,
  • Adel Al Qutub,
  • Eissa Ali Faqeih,
  • Mohamad Al-Tannir

DOI
https://doi.org/10.1186/s13063-020-4079-8
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 6

Abstract

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Abstract Objective The startup phase of a clinical trial (CT) plays a vital role in the execution of new drug development. Hence, the aim of this study is to identify the factors responsible for delaying the CT startup phase. Further, it focuses on streamlining and reducing the cycle time of the startup phase of newly sponsored CTs. Methods Thirteen sponsored CTs conducted between 2016 and 2017 at the Clinical Research Department of King Fahad Medical City, Riyadh, Saudi Arabia, were considered for this study. Eight trials were analyzed to identify the data specific to startup metrics using the FOCUS–PDCA cycle (Find an improvement area–Organize a team–Clarify current practices–Understand the source of variation/problem–Select a Strategy–Plan–Do–Check–Act). Six measures incorporated in the metrics were (1) date of initial contact with site to the signing of confidentiality agreement, (2) date of receiving questionnaire from sponsor to date of its completion, (4) time taken to review protocol and approve investigational drug service form, and (5) time taken to study protocol and approve pharmacy and pathology and clinical laboratory medicine form and date of receipt of institutional review board (IRB) submission package to final IRB approval. Fishbone analysis was used to understand the potential causes of process variation. Mean (SD) time was calculated for each metric before and after implementation of the intervention protocol to analyze and compare percentage reduction in the mean cycle time of CTs. Data were represented as mean (SD), and the P value was calculated for each metric. The significance level was set at P < 0.05. Results Of the various potential factors of delay identified through fishbone analysis, the two major ones were lack of a well-defined timeline for approval and review of the study protocol and inconsistent IRB meetings. After introduction of the new intervention protocol, the entire CT life cycle was reduced by 45.6% (mean [SD], 24.8 [8.2] weeks vs. 13.5 [11.6] weeks before and after the intervention, respectively). Conclusion Various factors are responsible for the delay of the startup phase of CTs, and understanding the impact of each element allows for optimization and faster execution of the startup phase of CTs.

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