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:

The role of early-phase trials and real-world evidence in drug development

Nature Cardiovascular Research volume 3, pages 110–117 (2024)Cite this article

Subjects

Abstract

Phase 3 randomized controlled trials (RCTs), while the gold standard for treatment efficacy and safety, are not always feasible, are expensive, can be prolonged and can be limited in generalizability. Other under-recognized sources of evidence can also help advance drug development. Basic science, proof-of-concept studies and early-phase RCTs can provide evidence regarding the potential for clinical benefit. Real-world evidence generated from registries or observational datasets can provide insights into the treatment of rare diseases that often pose a challenge for trial recruitment. Pragmatic trials embedded in healthcare systems can assess the treatment effects in clinical settings among patient populations sometimes excluded from trials. This Perspective discusses potential sources of evidence that may be used to complement explanatory phase 3 RCTs and to speed the development of new cardiovascular medications. Content is derived from the 19th Global Cardiovascular Clinical Trialists meeting (December 2022), involving clinical trialists, patients, clinicians, regulators, funders and industry representatives.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Fig. 1: Sources of RWE include healthcare as well as non-healthcare settings.
Fig. 2: Features of a surrogate endpoint.
Fig. 3: Biomarker utility in clinical trials.

Similar content being viewed by others

Data availability

No new data were generated or analyzed in support of this research.

References

  1. Paraskevas, K. I., de Borst, G. J. & Veith, F. J. Why randomized controlled trials do not always reflect reality. J. Vasc. Surg. 70, 607–614 (2019).

    Article  PubMed  Google Scholar 

  2. Dang, A. Real-world evidence: a primer. Pharmaceut. Med. 37, 25–36 (2023).

    PubMed  PubMed Central  Google Scholar 

  3. Moore, T. J., Heyward, J., Anderson, G. & Alexander, G. C. Variation in the estimated costs of pivotal clinical benefit trials supporting the US approval of new therapeutic agents, 2015–2017: a cross-sectional study. BMJ Open 10, e038863 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Brown, M. L., Gersh, B. J., Holmes, D. R., Bailey, K. R. & Sundt, T. M. 3rd From randomized trials to registry studies: translating data into clinical information. Nat. Clin. Pract. Cardiovasc. Med. 5, 613–620 (2008).

    Article  PubMed  Google Scholar 

  5. Sharma, M., Nazareth, I. & Petersen, I. Observational studies of treatment effectiveness: worthwhile or worthless? Clin. Epidemiol. 11, 35–42 (2019).

    Article  CAS  PubMed  Google Scholar 

  6. Fanaroff, A. C. et al. Randomized trials versus common sense and clinical observation: JACC Review Topic of the Week. J. Am. Coll. Cardiol. 76, 580–589 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Ruberman, W., Weinblatt, E., Goldberg, J. D., Frank, C. W. & Shapiro, S. Ventricular premature beats and mortality after myocardial infarction. N. Engl. J. Med. 297, 750–757 (1977).

    Article  CAS  PubMed  Google Scholar 

  8. Echt, D. S. et al. Mortality and morbidity in patients receiving encainide, flecainide, or placebo. The Cardiac Arrhythmia Suppression Trial. N. Engl. J. Med. 324, 781–788 (1991).

    Article  CAS  PubMed  Google Scholar 

  9. Steinmetz, K. L. & Spack, E. G. The basics of preclinical drug development for neurodegenerative disease indications. BMC Neurol. 9, S2 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Seyhan, A. A. Lost in translation: the valley of death across preclinical and clinical divide—identification of problems and overcoming obstacles. Transl. Med. Comm. 4, 18 (2019).

    Article  Google Scholar 

  11. Paul, S. M. et al. How to improve R&D productivity: the pharmaceutical industry’s grand challenge. Nat. Rev. Drug Discov. 9, 203–214 (2010).

    Article  CAS  PubMed  Google Scholar 

  12. Humbert, M. et al. Pathology and pathobiology of pulmonary hypertension: state of the art and research perspectives. Eur. Respir. J. 53, 1801887 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Yung, L. M. et al. ACTRIIA-Fc rebalances activin/GDF versus BMP signaling in pulmonary hypertension. Sci. Transl. Med. 12, eaaz5660 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Joshi, S. R. et al. Sotatercept analog improves cardiopulmonary remodeling and pulmonary hypertension in experimental left heart failure. Front. Cardiovasc. Med. 10, 1064290 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Humbert, M. et al. Sotatercept for the treatment of pulmonary arterial hypertension. N. Engl. J. Med. 384, 1204–1215 (2021).

    Article  CAS  PubMed  Google Scholar 

  16. Hoeper, M. M. et al. Phase 3 trial of sotatercept for treatment of pulmonary arterial hypertension. N. Engl. J. Med. 388, 1478–1490 (2023).

    Article  CAS  PubMed  Google Scholar 

  17. Mohs, R. C. & Greig, N. H. Drug discovery and development: role of basic biological research. Alzheimers Dement. 3, 651–657 (2017).

    Article  Google Scholar 

  18. Khan, M. S. et al. Leveraging electronic health records to streamline the conduct of cardiovascular clinical trials. Eur. Heart J. 44, 1890–1909 (2023).

    Article  PubMed  Google Scholar 

  19. Dagenais, S., Russo, L., Madsen, A., Webster, J. & Becnel, L. Use of real-world evidence to drive drug development strategy and inform clinical trial design. Clin. Pharmacol. Ther. 111, 77–89 (2022).

    Article  PubMed  Google Scholar 

  20. Zhao, X., Iqbal, S., Valdes, I. L., Dresser, M. & Girish, S. Integrating real-world data to accelerate and guide drug development: a clinical pharmacology perspective. Clin. Transl. Sci. 15, 2293–2302 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Szymanski, P. et al. Real world evidence: perspectives from a European Society of Cardiology Cardiovascular Round Table with contribution from the European Medicines Agency. Eur. Heart J. Qual. Care Clin. Outcomes 9, 109–118 (2023).

    Article  PubMed  Google Scholar 

  22. Leclercq, C. et al. Wearables, telemedicine, and artificial intelligence in arrhythmias and heart failure: proceedings of the European Society of Cardiology Cardiovascular Round Table. Europace 24, 1372–1383 (2022).

    Article  PubMed  Google Scholar 

  23. Honig, P. K. The ‘coming of age’ of real-world evidence in drug development and regulation. Clin. Pharmacol. Ther. 111, 11–14 (2022). This editorial underscores the importance of RWE in medical research to inform clinical trial design, elucidate the natural history of disease, select and monitor endpoints, compare effectiveness, and assess treatment utilization patterns.

    Article  PubMed  Google Scholar 

  24. Flynn, R. et al. Marketing authorization applications made to the European Medicines Agency in 2018–2019: what was the contribution of real-world evidence? Clin. Pharmacol. Ther. 111, 90–97 (2022).

    Article  PubMed  Google Scholar 

  25. Bakker, E. et al. Contribution of real-world evidence in European Medicines Agency’s regulatory decision making. Clin. Pharmacol. Ther. 113, 135–151 (2023).

    Article  PubMed  ADS  Google Scholar 

  26. Purpura, C. A., Garry, E. M., Honig, N., Case, A. & Rassen, J. A. The role of real-world evidence in FDA-approved new drug and biologics license applications. Clin. Pharmacol. Ther. 111, 135–144 (2022). In an application to the US FDA, RWE was influential in 74% (n = 65 out of 88) of decisions, demonstrating that RWE is an essential part of a regulatory approval package.

    Article  PubMed  Google Scholar 

  27. Cave, A., Kurz, X. & Arlett, P. Real-world data for regulatory decision making: challenges and possible solutions for Europe. Clin. Pharmacol. Ther. 106, 36–39 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Mofid, S., Bolislis, W. R. & Kuhler, T. C. Real-world data in the postapproval setting as applied by the EMA and the US FDA. Clin. Ther. 44, 306–322 (2022).

    Article  PubMed  Google Scholar 

  29. Lund, L. H., Oldgren, J. & James, S. Registry-based pragmatic trials in heart failure: current experience and future directions. Curr. Heart Fail. Rep. 14, 59–70 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Doherty, D. A. et al. Registry randomised trials: a methodological perspective. BMJ Open 13, e068057 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Van Spall, H. G. C. et al. Knowledge to action: rationale and design of the Patient-Centered Care Transitions in Heart Failure (PACT-HF) stepped wedge cluster randomized trial. Am. Heart J. 199, 75–82 (2018).

    Article  PubMed  Google Scholar 

  32. Van Spall, H. G. C. et al. Effect of patient-centered transitional care services on clinical outcomes in patients hospitalized for heart failure: the PACT-HF randomized clinical trial. JAMA 321, 753–761 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Frobert, O. et al. Thrombus aspiration during ST-segment elevation myocardial infarction. N. Engl. J. Med. 369, 1587–1597 (2013).

    Article  CAS  PubMed  Google Scholar 

  34. Hess, C. N. et al. Embedding a randomized clinical trial into an ongoing registry infrastructure: unique opportunities for efficiency in design of the Study of Access site For Enhancement of Percutaneous Coronary Intervention for Women (SAFE-PCI for Women). Am. Heart J. 166, 421–428 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Chew, D. S., Whitelaw, S., Vaduganathan, M., Mark, D. B. & Van Spall, H. G. C. Patient-reported outcome measures in cardiovascular disease: an evidence map of the psychometric properties of health status instruments. Ann. Intern. Med. 175, 1431–1439 (2022).

    Article  PubMed  Google Scholar 

  36. Zannad, F. et al. Patient-reported outcome measures and patient engagement in heart failure clinical trials: multi-stakeholder perspectives. Eur. J. Heart. Fail. 25, 478–487 (2023).

    Article  PubMed  Google Scholar 

  37. Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin. Pharmacol. Ther. 69, 89–95 (2001).

    Article  Google Scholar 

  38. Temple, R. Are surrogate markers adequate to assess cardiovascular disease drugs? JAMA 282, 790–795 (1999). This review of surrogate endpoints from a member of the FDA provides a balanced look at the pros and cons of relying on such outcomes in clinical research.

    Article  CAS  PubMed  Google Scholar 

  39. Spertus, J. V. et al. Integrating quality of life and survival outcomes in cardiovascular clinical trials. Circ. Cardiovasc. Qual. Outcomes 12, e005420 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Weir, C. J. & Taylor, R. S. Informed decision-making: Statistical methodology for surrogacy evaluation and its role in licensing and reimbursement assessments. Pharm. Stat. 21, 740–756 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Fleming, T. R. & DeMets, D. L. Surrogate end points in clinical trials: are we being misled? Ann. Intern. Med. 125, 605–613 (1996).

    Article  CAS  PubMed  Google Scholar 

  42. FDA-NIH Biomarker Working Group. BEST (Biomarkers, EndpointS, and other Tools) Resource (US FDA and National Institutes of Health, 2016).

  43. Elliott, P. et al. Development, validation, and implementation of biomarker testing in cardiovascular medicine state-of-the-art: proceedings of the European Society of Cardiology-Cardiovascular Round Table. Cardiovasc. Res. 117, 1248–1256 (2021).

    Article  CAS  PubMed  Google Scholar 

  44. Bakker, E. et al. Biomarker qualification at the European Medicines Agency: a review of biomarker qualification procedures from 2008 to 2020. Clin. Pharmacol. Ther. 112, 69–80 (2022). A review of biomarkers qualified by the EMA between 2008 and 2020 found that only 13 out of 86 applications were approved, and of 9 efficacy biomarkers proposed as surrogate endpoints, none were qualified, demonstrating that this field continues to need more work.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Fleming, T. R. & Powers, J. H. Biomarkers and surrogate endpoints in clinical trials. Stat. Med. 31, 2973–2984 (2012).

    Article  MathSciNet  PubMed  PubMed Central  Google Scholar 

  46. Kim, M. S. et al. A draft map of the human proteome. Nature 509, 575–581 (2014).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  47. Ridker, P. M., Rifai, N., Rose, L., Buring, J. E. & Cook, N. R. Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events. N. Engl. J. Med. 347, 1557–1565 (2002).

    Article  CAS  PubMed  Google Scholar 

  48. Mohebi, R., McCarthy, C. P., Gaggin, H. K., van Kimmenade, R. R. J. & Januzzi, J. L. Inflammatory biomarkers and risk of cardiovascular events in patients undergoing coronary angiography. Am. Heart J. 252, 51–59 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Mohebi, R. et al. Inflammation across universal definition of heart failure stages: the CASABLANCA study. Eur. J. Heart Fail. 25, 152–160 (2022).

  50. Ravera, A. et al. Distinct pathophysiological pathways in women and men with heart failure. Eur. J. Heart Fail. 24, 1532–1544 (2022).

    Article  CAS  PubMed  Google Scholar 

  51. Ridker, P. M. et al. Antiinflammatory therapy with canakinumab for atherosclerotic disease. N. Engl. J. Med. 377, 1119–1131 (2017).

    Article  CAS  PubMed  Google Scholar 

  52. Marwick, T. H., Cho, I., Hartaigh, B. O. & Min, J. K. Finding the gatekeeper to the cardiac catheterization laboratory: coronary CT angiography or stress testing? J. Am. Coll. Cardiol. 65, 2747–2756 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Figtree, G. A. et al. Noninvasive plaque imaging to accelerate coronary artery disease drug development. Circulation 146, 1712–1727 (2022).

    Article  CAS  PubMed  Google Scholar 

  54. Lee, S. E. et al. Effects of statins on coronary atherosclerotic plaques: the PARADIGM study. JACC Cardiovasc. Imaging 11, 1475–1484 (2018).

    Article  PubMed  Google Scholar 

  55. SCOT-HEART Investigators. et al. Coronary CT angiography and 5-year risk of myocardial infarction. N. Engl. J. Med. 379, 924–933 (2018). This trial demonstrated that CTCA added to standard care significantly lowered the rate of CV events at 5 years compared to standard care, suggesting the potential for plaque characteristics on CTCA to be used as surrogate endpoints.

    Article  Google Scholar 

  56. Gulati, M. et al. 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 144, e368–e454 (2021).

    PubMed  Google Scholar 

  57. Knuuti, J. et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur. Heart J. 41, 407–477 (2020).

    Article  PubMed  Google Scholar 

  58. Freeman, A. M. et al. Integrating coronary atherosclerosis burden and progression with coronary artery disease risk factors to guide therapeutic decision making. Am. J. Med. 136, 260–269 (2023).

    Article  CAS  PubMed  Google Scholar 

  59. Chang, H. J. et al. Coronary atherosclerotic precursors of acute coronary syndromes. J. Am. Coll. Cardiol. 71, 2511–2522 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Ferencik, M. et al. Use of high-risk coronary atherosclerotic plaque detection for risk stratification of patients with stable chest pain: a secondary analysis of the PROMISE randomized clinical trial. JAMA Cardiol. 3, 144–152 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Williams, M. C. et al. Coronary artery plaque characteristics associated with adverse outcomes in the SCOT-HEART study. J. Am. Coll. Cardiol. 73, 291–301 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  62. van Rosendael, A. R. et al. Association of high-density calcified 1K plaque with risk of acute coronary syndrome. JAMA Cardiol. 5, 282–290 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  63. van Rosendael, A. R. et al. Progression of whole-heart atherosclerosis by coronary CT and major adverse cardiovascular events. J. Cardiovasc. Comput. Tomogr. 15, 322–330 (2021).

    Article  PubMed  Google Scholar 

  64. Averbuch, T. et al. Applications of artificial intelligence and machine learning in heart failure. Eur. Heart J. Digit. Health 3, 311–322 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  65. Greenberg, B., Adler, E., Campagnari, C. & Yagil, A. A machine learning risk score predicts mortality across the spectrum of left ventricular ejection fraction. Eur. J. Heart Fail. 23, 995–999 (2021).

    Article  PubMed  Google Scholar 

  66. Adler, E. D. et al. Improving risk prediction in heart failure using machine learning. Eur. J. Heart Fail. 22, 139–147 (2020).

    Article  PubMed  Google Scholar 

  67. Jering, K. S. et al. Improving clinical trial efficiency using a machine learning-based risk score to enrich study populations. Eur. J. Heart Fail. 24, 1418–1426 (2022).

    Article  CAS  PubMed  Google Scholar 

  68. Gevaert, A. B. et al. Clinical phenogroups are more effective than left ventricular ejection fraction categories in stratifying heart failure outcomes. ESC Heart Fail. 8, 2741–2754 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This article was generated from discussions at the 19th Global CVCT Forum held online in December 2022. The CVCT Forum is a strategic workshop for high-level dialog between clinical trialists, industry representatives, regulatory authorities and patients. The authors thank P. Lavigne and S. Portelance (unaffiliated, supported by the CVCT Forum) for contributions to writing the manuscript.

Author information

Authors and Affiliations

  1. Department of Medicine, Department of Health Research Methods, Evidence, and Impact; Research Institute of St. Joseph’s, McMaster University, Hamilton, Ontario, Canada

    Harriette G. C. Van Spall

  2. Baim Institute for Clinical Research, Boston, MA, USA

    Harriette G. C. Van Spall

  3. Bristol Myers Squibb, Princeton, NJ, USA

    Arnaud Bastien

  4. Department of Cardiovascular Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA

    Bernard Gersh

  5. Division of Cardiology, UC San Diego Health, San Diego, CA, USA

    Barry Greenberg

  6. Division of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Reza Mohebi

  7. Cleerly, Denver, CO, USA

    James Min

  8. Olink, Uppsala, Sweden

    Karsten Strauss

  9. European Medicines Agency, Amsterdam, the Netherlands

    Steffen Thirstrup

  10. Université de Lorraine, Inserm Clinical Investigation Center at Institut Lorrain du Coeur et des Vaisseaux, University Hospital of Nancy, Nancy, France

    Faiez Zannad

Authors
  1. Harriette G. C. Van Spall
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arnaud Bastien
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bernard Gersh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Barry Greenberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Reza Mohebi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. James Min
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Karsten Strauss
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Steffen Thirstrup
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Faiez Zannad
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Faiez Zannad.

Ethics declarations

Competing interests

H.G.C.V.S. reports grants from the Canadian Institutes of Health Research and the Heart and Stroke Foundation. A.B. reports employment, travel and/or meeting attendance support, and stock or stock options from Bristol Myers Squibb; and membership on the Board of Trustees (unpaid) for Coriell Medical Research Institute. J.M. reports participation on a medical advisory board for Arineta; employment (CEO) with Cleerly; and an equity interest in Cleerly. K.S. reports employment, travel and/or meeting attendance support, and stock or stock options from Olink Proteomics. F.Z. reports consulting fees from 89bio, Applied Therapeutics, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardior Pharmaceuticals, Cellprothera, Cereno Scientific, CEVA, CVRx, Merck, Novartis, NovoNordisk, Owkin, Pfizer and Servier; honoraria for lectures from Bayer, Boehringer Ingelheim, CEVA, CVRx, Merck and Novartis; fees for participation on a data safety monitoring board or advisory board from Acceleron/Merck; and equity interests in G3 Pharmaceuticals, Cereno Pharmaceuticals, Cardiorenal, Eshmoun Clinical Research and CVCT. The other authors declare no competing interests. The views expressed in this article are the personal views of the authors and may not be understood or quoted as being made on behalf of or reflecting the position of the regulatory agency/agencies or organizations with which the authors are employed or affiliated.

Peer review

Peer review information

Nature Cardiovascular Research thanks Ulf Landmesser, and the other, anonymous, reviewer(s) 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

Van Spall, H.G.C., Bastien, A., Gersh, B. et al. The role of early-phase trials and real-world evidence in drug development. Nat Cardiovasc Res 3, 110–117 (2024). https://doi.org/10.1038/s44161-024-00420-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s44161-024-00420-4

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research