Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Perspective
  • Published:

Transforming the evidence landscape in mental health with platform trials

Nature Mental Health volume 3, pages 276–285 (2025)Cite this article

Subjects

Abstract

Clinical trials are at the core of evidence-based medicine, but many are underpowered and fail to inform clinical practice. In mental health, the number of regulatory drug approvals has consistently lagged behind other areas of medicine, the effects of established therapies may vary, and comparative effectiveness data for available treatments are scarce. Thus, there is an urgent need for more efficient, faster and more collaborative ways of generating evidence. Traditional approaches of ‘one treatment, one trial’ are slow, inefficient, and limit comparability across trials. In contrast, platform trials use a shared infrastructure for many treatments, shared control group(s) and a master protocol that allows treatments to be added over time and ineffective ones to be dropped early. Here we present examples of platform trials in mental health (M-PACT, EU-PEARLDIVER, PUMA and RESiLIENT) and discuss their potential to increase speed, reduce operational costs and participant burden, and improve statistical power and comparability.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Examples of platform trial and master protocol designs in mental health.
Fig. 2: Efficiencies of a mental health platform trial with regard to sample size and statistical power.

Similar content being viewed by others

References

  1. Grimes, D. A. & Schulz, K. F. An overview of clinical research: the lay of the land. Lancet 359, 57–61 (2002).

    Article  PubMed  Google Scholar 

  2. Wouters, O. J., McKee, M. & Luyten, J. Estimated research and development investment needed to bring a new medicine to market, 2009-2018. JAMA 323, 844–853 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  3. DiMasi, J. A., Grabowski, H. G. & Hansen, R. W. Innovation in the pharmaceutical industry: new estimates of R&D costs. J. Health Econ. 47, 20–33 (2016).

    Article  PubMed  Google Scholar 

  4. Chevance, A., Ravaud, P., Cornelius, V., Mayo-Wilson, E. & Furukawa, T. A. Designing clinically useful psychopharmacological trials: challenges and ways forward. Lancet Psychiatry 9, 584–594 (2022).

    Article  PubMed  Google Scholar 

  5. de Vries, Y. A., Schoevers, R. A., Higgins, J. P. T., Munafò, M. R. & Bastiaansen, J. A. Statistical power in clinical trials of interventions for mood, anxiety and psychotic disorders. Psychol. Med. 53, 4499–4506 (2023).

    Article  PubMed  Google Scholar 

  6. Leucht, S., Hierl, S., Kissling, W., Dold, M. & Davis, J. M. Putting the efficacy of psychiatric and general medicine medication into perspective: review of meta-analyses. Br. J. Psychiatry 200, 97–106 (2012).

    Article  PubMed  Google Scholar 

  7. Mullard, A. 2023 FDA approvals. Nat. Rev. Drug Discov. 23, 88–95 (2024).

    Article  PubMed  Google Scholar 

  8. Zhu, T. Challenges of psychiatry drug development and the role of human pharmacology models in early development—a drug developer’s perspective. Front. Psychiatry 11, 562660 (2020).

    Article  PubMed  Google Scholar 

  9. Tranberg, K. et al. Challenges in reaching patients with severe mental illness for trials in general practice—a convergent mixed methods study based on the SOFIA pilot trial. Pilot Feasibility Stud. 9, 182 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Gold, S. M., Landray, M. J., Medhurst, N. & Otte, C. Fast tracking informative clinical trials: lessons for mental health. Lancet Psychiatry 10, 376–378 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Adaptive Platform Trials Coalition. Adaptive platform trials: definition, design, conduct and reporting considerations. Nat. Rev. Drug Discov. 18, 797–807 (2019).

    Article  Google Scholar 

  12. Wang, H. & Yee, D. I-SPY 2: a neoadjuvant adaptive clinical trial designed to improve outcomes in high-risk breast cancer. Curr. Breast Cancer Rep. 11, 303–310 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  13. James, N. D. et al. STAMPEDE: Systemic Therapy for Advancing or Metastatic Prostate Cancer—a multi-arm multi-stage randomised controlled trial. Clin. Oncol. (R. Coll. Radiol.) 20, 577–581 (2008).

    Article  Google Scholar 

  14. Peto, L., Horby, P. & Landray, M. Establishing COVID-19 trials at scale and pace: experience from the RECOVERY trial. Adv. Biol. Regul. 86, 100901 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Angus, D. C. et al. The REMAP-CAP (Randomized Embedded Multifactorial Adaptive Platform for Community-Acquired Pneumonia) Study. Rationale and design. Ann. Am. Thorac. Soc. 17, 879–891 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Griessbach, A. et al. Characteristics, progression and output of randomized platform trials: a systematic review. JAMA Netw. Open 7, e243109 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Blackwell, S. E. et al. Demonstration of a ‘leapfrog’ randomized controlled trial as a method to accelerate the development and optimization of psychological interventions. Psychol. Med. 53, 6113–6123 (2023).

    Article  PubMed  Google Scholar 

  18. Gold, S. M. et al. Control conditions for randomised trials of behavioural interventions in psychiatry: a decision framework. Lancet Psychiatry 4, 725–732 (2017).

    Article  PubMed  Google Scholar 

  19. Gold, S. M. et al. Platform trials and the future of evaluating therapeutic behavioural interventions. Nat. Rev. Psychol. 1, 7–8 (2022).

    Article  Google Scholar 

  20. Blackwell, S. E., Woud, M. L., Margraf, J. & Schönbrodt, F. D. Introducing the leapfrog design: a simple Bayesian adaptive rolling trial design for accelerated treatment development and optimization. Clin. Psychol. Sci. 7, 1222–1243 (2019).

    Article  Google Scholar 

  21. Koenig, F. et al. Current state-of-the-art and gaps in platform trials: 10 things you should know, insights from EU-PEARL. EClinicalMedicine 67, 102384 (2024).

    Article  PubMed  Google Scholar 

  22. Nguyen, Q. L. et al. Regulatory issues of platform trials: learnings from EU-PEARL. Clin. Pharmacol. Ther. 116, 52–63 (2024).

    Article  PubMed  Google Scholar 

  23. Gidh-Jain, M. et al. Developing generic templates to shape the future for conducting integrated research platform trials. Trials. 25, 204 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Bschor, T., Nagel, L., Unger, J., Schwarzer, G. & Baethge, C. Differential outcomes of placebo treatment across 9 psychiatric disorders: a systematic review and meta-analysis. JAMA Psychiatry 81, 757–768 (2024).

    Article  PubMed  Google Scholar 

  25. Huneke, N.T.M. Placebo effects in randomized trials of pharmacological and neurostimulation interventions for mental disorders: an umbrella review. Mol. Psychiatry 29, 3915–3925 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Papakostas, G. I. & Fava, M. Does the probability of receiving placebo influence clinical trial outcome? A meta-regression of double-blind, randomized clinical trials in MDD. Eur. Neuropsychopharmacol. 19, 34–40 (2009).

    Article  PubMed  Google Scholar 

  27. Jones, B. D. M. et al. Magnitude of the placebo response across treatment modalities used for treatment-resistant depression in adults: a systematic review and meta-analysis. JAMA Netw. Open 4, e2125531 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Viele, K. Allocation in platform trials to maintain comparability across time and eligibility. Stat. Med. 42, 2811–2818 (2023).

    Article  PubMed  Google Scholar 

  29. Bofill Roig, M., Glimm, E., Mielke, T. & Posch, M. Optimal allocation strategies in platform trials with continuous endpoints. Stat. Methods Med. Res. 33, 858–874 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Bofill Roig, M. et al. On model-based time trend adjustments in platform trials with non-concurrent controls. BMC Med. Res. Methodol. 22, 228 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Lee, K. M. & Wason, J. Including non-concurrent control patients in the analysis of platform trials: is it worth it? BMC Med. Res. Method. 20, 165 (2020).

    Article  Google Scholar 

  32. Saville, B. R., Berry, D. A., Berry, N. S., Viele, K. & Berry, S. M. The Bayesian time machine: accounting for temporal drift in multi-arm platform trials. Clin. Trials 19, 490–501 (2022).

    Article  PubMed  Google Scholar 

  33. Bofill Roig, M., König, F., Meyer, E. & Posch, M. Commentary: Two approaches to analyze platform trials incorporating non-concurrent controls with a common assumption. Clin. Trials 19, 502–503 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Henssler, J., Alexander, D., Schwarzer, G., Bschor, T. & Baethge, C. Combining antidepressants vs antidepressant monotherapy for treatment of patients with acute depression: a systematic review and meta-analysis. JAMA Psychiatry 79, 300–312 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Nuñez, N. A. et al. Augmentation strategies for treatment resistant major depression: a systematic review and network meta-analysis. J. Affect. Disord. 302, 385–400 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Scott, F. et al. Systematic review and meta-analysis of augmentation and combination treatments for early-stage treatment-resistant depression. J. Psychopharmacol. 37, 268–278 (2023).

    Article  PubMed  Google Scholar 

  37. Köhler-Forsberg, O., Otte, C., Gold, S. M. & Østergaard, S. D. Statins in the treatment of depression: hype or hope? Pharmacol. Ther. 215, 107625 (2020).

    Article  PubMed  Google Scholar 

  38. Toba-Oluboka, T., Vochosková, K. & Hajek, T. Are the antidepressant effects of insulin-sensitizing medications related to improvements in metabolic markers? Transl. Psychiatry 12, 469 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Drevets, W. C., Wittenberg, G. M., Bullmore, E. T. & Manji, H. K. Immune targets for therapeutic development in depression: towards precision medicine. Nat. Rev. Drug Discov. 21, 224–244 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Köhler-Forsberg, O. et al. Efficacy of anti-inflammatory treatment on major depressive disorder or depressive symptoms: meta-analysis of clinical trials. Acta Psychiatr. Scand. 139, 404–419 (2019).

    Article  PubMed  Google Scholar 

  41. Deisenhofer, A. K. et al. Implementing precision methods in personalizing psychological therapies: barriers and possible ways forward. Behav. Res. Ther. 172, 104443 (2024).

    Article  PubMed  Google Scholar 

  42. Blackwell, S. E. Using the ‘leapfrog’ design as a simple form of adaptive platform trial to develop, test and implement treatment personalization methods in routine practice. Adm. Policy Ment. Health 51, 686–701 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Freitag, M.M. et al. Design considerations for a Phase II platform trial in major depressive disorder. Preprint at https://arxiv.org/abs/2310.02080 (2023).

  44. Cunniffe, N. et al. Systematic approach to selecting licensed drugs for repurposing in the treatment of progressive multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 92, 295–302 (2021).

    Article  PubMed  Google Scholar 

  45. Furukawa, T. A. et al. Four 2 × 2 factorial trials of smartphone CBT to reduce subthreshold depression and to prevent new depressive episodes among adults in the community-RESiLIENT trial (Resilience Enhancement with Smartphone in LIving ENvironmenTs): a master protocol. BMJ Open 13, e067850 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Michopoulos, I. et al. Different control conditions can produce different effect estimates in psychotherapy trials for depression. J. Clin. Epidemiol. 132, 59–70 (2021).

    Article  PubMed  Google Scholar 

  47. Furukawa, T. A. et al. Dismantling, optimising and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual participant data. Lancet Psychiatry 8, 500–511 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Cuijpers, P. et al. Psychotherapies for depression: a network meta-analysis covering efficacy, acceptability and long-term outcomes of all main treatment types. World Psychiatry 20, 283–293 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Karyotaki, E. et al. Association of task-shared psychological interventions with depression outcomes in low- and middle-income countries: a systematic review and individual patient data meta-analysis. JAMA Psychiatry 79, 430–443 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Psychiatry, Charité – Universitätsmedizin Berlin, Berlin, Germany

    Stefan M. Gold, Jelena Brasanac, Michaela Maria Freitag & Christian Otte

  2. Medical Department, Section Psychosomatic Medicine, Charité – Universitätsmedizin Berlin, Berlin, Germany

    Stefan M. Gold

  3. German Center for Mental Health (DZPG), Berlin, Germany

    Stefan M. Gold & Christian Otte

  4. Institut für Neuroimmunologie und Multiple Sklerose (INIMS), Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany

    Stefan M. Gold

  5. Lived Experience Expert, Helsinki, Finland

    Fanni-Laura Mäntylä

  6. Mental Health Team – Translation, Wellcome Trust, London, UK

    Kim Donoghue

  7. Center for Medical Data Science, Institute of Medical Statistics, Medical University of Vienna, Wien, Austria

    Franz König & Martin Posch

  8. Department of Mental Health, Hospital Universitari Vall d’Hebron, Barcelona, Spain

    J. Antoni Ramos-Quiroga

  9. Vita-Salute San Raffaele University, Milan, Italy

    Francesco Benedetti

  10. Psychiatry & Clinical Psychobiology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy

    Francesco Benedetti

  11. Psychosis Research Unit, Aarhus University Hospital Psychiatry, Aarhus, Denmark

    Ole Köhler-Forsberg

  12. Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

    Ole Köhler-Forsberg

  13. Department of Psychiatry, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands

    Nina Grootendorst & Witte Hoogendijk

  14. Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, Maurice Wohl Clinical Neuroscience Institute, King’s College London, London, UK

    Carmine M. Pariante

  15. National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, London, UK

    Carmine M. Pariante

  16. Defense Health Agency Operational Medical Systems, Fort Detrick, MD, USA

    Elyse R. Katz

  17. Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, Australia

    Steve Webb

  18. Kyoto University Office of Institutional Advancement and Communications, Kyoto, Japan

    Belinda Lennox

  19. Department of Psychiatry, University of Oxford, Oxford, UK

    Toshi A. Furukawa

Authors
  1. Stefan M. Gold
    View author publications

    Search author on:PubMed Google Scholar

  2. Fanni-Laura Mäntylä
    View author publications

    Search author on:PubMed Google Scholar

  3. Kim Donoghue
    View author publications

    Search author on:PubMed Google Scholar

  4. Jelena Brasanac
    View author publications

    Search author on:PubMed Google Scholar

  5. Michaela Maria Freitag
    View author publications

    Search author on:PubMed Google Scholar

  6. Franz König
    View author publications

    Search author on:PubMed Google Scholar

  7. Martin Posch
    View author publications

    Search author on:PubMed Google Scholar

  8. J. Antoni Ramos-Quiroga
    View author publications

    Search author on:PubMed Google Scholar

  9. Francesco Benedetti
    View author publications

    Search author on:PubMed Google Scholar

  10. Ole Köhler-Forsberg
    View author publications

    Search author on:PubMed Google Scholar

  11. Nina Grootendorst
    View author publications

    Search author on:PubMed Google Scholar

  12. Witte Hoogendijk
    View author publications

    Search author on:PubMed Google Scholar

  13. Carmine M. Pariante
    View author publications

    Search author on:PubMed Google Scholar

  14. Elyse R. Katz
    View author publications

    Search author on:PubMed Google Scholar

  15. Steve Webb
    View author publications

    Search author on:PubMed Google Scholar

  16. Belinda Lennox
    View author publications

    Search author on:PubMed Google Scholar

  17. Toshi A. Furukawa
    View author publications

    Search author on:PubMed Google Scholar

  18. Christian Otte
    View author publications

    Search author on:PubMed Google Scholar

Contributions

S.M.G. and C.O. developed the overall concept. S.M.G. wrote the first draft of the manuscript and Table 1. S.M.G., J.B., M.M.F., F.K., M.P., E.R.K. and T.A.F. prepared the figures. E.R.K., S.M.G., B.L. and T.A.F. wrote Box 1. F.-L.M. and K.D. wrote Box 2. F.-L.M., K.D., J.B., M.M.F., F.K., M.P., J.A.R.-Q., F.B., O.K.-F., N.G., W.H., C.M.P., E.R.K., S.W., B.L., T.A.F. and C.O. edited, reviewed and refined all versions of the manuscript.

Corresponding author

Correspondence to Stefan M. Gold.

Ethics declarations

Competing interests

S.M.G. reports honoraria from Hexal, Angelini and Tegus. O.K.-F. reports honoraria for lectures for Lundbeck Pharma A/S and consultant work for WCG Clinical. J.A.R.-Q. was on the speakers’ bureau and/or acted as consultant for Biogen, Idorsia, Casen-Recordati, Janssen-Cilag, Novartis, Takeda, Bial, Sincrolab, Neuraxpharm, Novartis, BMS, Medice, Rubió, Uriach, Technofarma and Raffo in the last three years. He also received travel awards (air tickets and hotel) for taking part in psychiatric meetings from Idorsia, Janssen-Cilag, Rubió, Takeda, Bial and Medice. The Department of Psychiatry chaired by him has received unrestricted educational and research support from the following companies in the last three years: Exeltis, Idorsia, Janssen-Cilag, Neuraxpharm, Oryzon, Roche, Probitas and Rubió. C.P. reports consultation and speaker’s fees from Boehringer-Ingelheim, Eli Lilly, Compass, Eleusis, GH Research, Lundbeck and Värde Partners. T.A.F. reports personal fees from Boehringer-Ingelheim, Daiichi Sankyo, DT Axis, Kyoto University Original, Shionogi, SONY and UpToDate, a grant from DT Axis and Shionogi, patent 7448125 concerning use of machine learning in internet cognitive–behavioural therapy (iCBT), and a pending patent 2022-082495 about prediction models for depression relapse, and intellectual properties for Kokoro-app (a smartphone CBT app) licensed to Mitsubishi-Tanabe. C.O. reports honoraria for lectures and/or scientific advice from Boehringer-Ingelheim, Janssen, Neuraxpharm, Oberberg Kliniken, Peak Profiling and Limes Klinikgruppe. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Mental Health thanks Urska Arnautovska, Simon Blackwell and Matt Muijen for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gold, S.M., Mäntylä, FL., Donoghue, K. et al. Transforming the evidence landscape in mental health with platform trials. Nat. Mental Health 3, 276–285 (2025). https://doi.org/10.1038/s44220-025-00391-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s44220-025-00391-w

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing