Willigers Bartholomeus J A, Wiesiolek Agata E, Potter Bruce, Pszczółkowska Alina, Kristensson Cecilia, Presz Veronica, Saraiva Gabriela Luporini, Psallidas Ioannis
Late-stage Development, Respiratory & Immunology, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.
Clinical Operations, BioPharmaceuticals R&D, AstraZeneca, Warsaw, Poland.
BMC Med Res Methodol. 2025 Aug 29;25(1):205. doi: 10.1186/s12874-025-02652-9.
BACKGROUND: Over the last decade, the pharmaceutical industry has witnessed longer, more complex, and expensive clinical trials. This complexity contributes to delays in clinical trial implementation, execution, monitoring, recruitment, data cleaning, and interpretation. Our aim was to develop a protocol complexity tool (PCT) to simplify clinical trial execution without compromising science or quality. METHODS: Using a collaborative design process, a taskforce comprising 20 cross-functional experts in clinical trial design and execution developed a PCT, between June 2021 and December 2022 and comprising 26 questions across 5 domains (operational execution, regulatory oversight, patient burden, site burden and study design). Individual domain scores and total complexity score (TCS) were calculated, and agreed by consensus, for 16 pre-identified phase II-IV difficult clinical trials across 3 therapeutic areas. Change in score was assessed post-PCT pass through. The relationship between TCS and key trial indicators (i.e. time-to-site activation and participant enrolment) was assessed for 26 studies by correlation analysis. RESULTS: Post-PCT pass through, the TCS was reduced in 12 trials (75%), remained the same in 3 trials (18.8%) and increased in 1 trial (6.2%). Complexity was most notably decreased in the operational execution and site burden domains, decreasing in 50% and 43.8% of assessed trials, respectively. Time-to-site activation and participant enrolment positively correlated with TCS, reaching statistical significance at 75% site activation (rho = 0.61; p = 0.005; n = 19) and 25% participant recruitment (rho = 0.59; p = 0.012; n = 17). CONCLUSIONS: We have developed a Protocol Complexity Tool to objectively measure the complexity of a study protocol consistently and transparently. The PCT is capable of driving simplification, enhancing collaboration, and creating additional confidence in trial designs. In the future, we envision the tool will support earlier discussions to develop protocols that are simpler to execute and more cost-effective.
背景：在过去十年中，制药行业经历了更长、更复杂且成本更高的临床试验。这种复杂性导致临床试验在实施、执行、监测、招募、数据清理和解读方面出现延迟。我们的目标是开发一种方案复杂性工具（PCT），以简化临床试验执行，同时不影响科学性或质量。 方法：通过协作设计流程，一个由20名临床试验设计和执行方面的跨职能专家组成的特别工作组在2021年6月至2022年12月期间开发了一种PCT，该PCT涵盖5个领域（操作执行、监管监督、患者负担、研究点负担和研究设计）的26个问题。针对3个治疗领域的16项预先确定的II-IV期困难临床试验，计算并经共识商定了各个领域的得分以及总复杂性得分（TCS）。在PCT通过后评估得分变化。通过相关性分析评估了26项研究中TCS与关键试验指标（即研究点启动时间和参与者入组情况）之间的关系。 结果：在PCT通过后，12项试验（75%）的TCS降低，3项试验（18.8%）保持不变，1项试验（6.2%）增加。操作执行和研究点负担领域的复杂性下降最为显著，分别在50%和43.8%的评估试验中有所降低。研究点启动时间和参与者入组情况与TCS呈正相关，在75%的研究点启动时（rho = 0.61；p = 0.005；n = 19）以及25%的参与者招募时（rho = 0.59；p = 0.012；n = 17）达到统计学显著性。 结论：我们开发了一种方案复杂性工具，以一致且透明的方式客观衡量研究方案的复杂性。PCT能够推动简化、加强协作，并在试验设计中建立更多信心。未来，我们设想该工具将支持更早进行讨论，以制定更易于执行且更具成本效益的方案。
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