The use of complex clinical trials: a regulatory review.
Clinical Snapshot
PICO Framework
| P — Population | Complex clinical trials submitted for scientific advice to regulatory agencies |
| I — Intervention | Complex trial designs (adaptive designs, multiple arms, common controls) |
| C — Comparator | Traditional single-arm clinical trial designs and regulatory expectations |
| O — Outcomes | Regulatory acceptance, feedback patterns, methodological concerns, and guidance adherence |
Bottom Line
This systematic review of 30 German regulatory scientific advice procedures reveals that complex clinical trial designs are increasingly proposed and generally acceptable to regulators when appropriately designed. Key regulatory concerns mirror those in traditional trials but require enhanced attention to multiplicity control, pre-planned treatment arms, and appropriate control group definition. The review suggests that lack of multiplicity control may be acceptable in exploratory trials with independent cohorts, and common control groups are frequently proposed. However, the evidence base is limited by its single-agency focus and descriptive nature. For Australian clinical trialists, the findings emphasise the importance of early TGA engagement when planning complex adaptive designs, though specific Australian regulatory preferences may differ from European approaches.
Key Findings
Effect Size: Not quantified - descriptive review
Primary Outcome: Regulatory acceptance patterns for complex clinical trial designs
Nnt Or Sensitivity: 30 scientific advice procedures from 29 complex trials reviewed
Confidence Interval: Not provided
Clinical Application
Moderate - requires early regulatory engagement and careful trial design planning Limited direct applicability - TGA guidance may differ from European approaches, though principles of early regulatory engagement remain relevant for Australian clinical trial sponsors Clinical researchers and pharmaceutical companies designing complex clinical trials
Abstract
BACKGROUND: Complex clinical trials offer flexibility in evaluating multiple treatments or diseases simultaneously. These trials often feature adaptive designs, common controls, and the potential to add new arms. However, the increased complexity raises methodological challenges particularly regarding multiple testing or the adequate choice of control groups. Despite guidance from regulatory bodies like the European Medicines Agency and the U.S. Food and Drug Administration, uncertainties remain about the regulatory acceptance of these trials. METHODS: This systematic review examines scientific advice procedures of products in the remit of the Paul-Ehrlich-Institut for complex clinical trials to highlight key concerns and regulatory feedback. We identified 30 scientific advice procedures corresponding to 29 different complex clinical trials. RESULTS: Our findings reveal an increasing number of complex trial designs proposed by applicants. A lack of multiplicity control due to multiple arms was generally considered acceptable by regulators in exploratory trials and if cohorts can be considered independent. Additionally, the use of common control groups is frequently proposed by applicants. The review underscores the importance of pre-planning for new treatment arms, appropriate multiplicity control, and the definition of control groups in trial designs. CONCLUSION: Overall, our findings suggest that regulatory concerns regarding complex trials largely align with those in traditional trial designs, though their complexity requires careful, case-by-case consideration. Early engagement with regulatory agencies can be crucial to ensure the successful design and implementation of these trials.
References
- 1.Nguyen, Q., Kästel, H., Hees, K., & Hofner, B. (2026). The use of complex clinical trials: a regulatory review. Trials. https://doi.org/10.1056/nejmra1510062
Related Research
JMIR formative research
Automated Machine Learning Frameworks for Radiomics: Comparative Evaluation Study
14 June 2026
Critical care (London, England)
Large language models for optimizing clinical trial recruitment in ICUs: application to ventilator-induced diaphragm dysfunction
13 June 2026
Purinergic signalling
Turning failure into success: how artificial intelligence can help personalize therapies and re-use patient data.
31 May 2026
This content is for educational purposes for healthcare professionals only and does not constitute clinical advice. Clinical decisions should be based on individual patient assessment, current guidelines, and appropriate specialist consultation. Editorial Standards · Privacy Policy · Terms of Service