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Translational process

I am delighted to introduce a new section of the Journal of Translational Medicine: Translational Process. The section welcomes contributions aimed to streamline the transition of new knowledge along the translational continuum, and boost our ability to concretely innovate clinical practice.

Too often, clinical translational studies employ methods that are perfectly valid in basic research, but enable only a very slow translation along the continuum heading to clinics. Standard operating procedures are disregarded in the name of “freedom of research”. Requirements and constraints set by regulators, health technology assessment experts and policy makers seldom affect research priorities and study designs. Implementation is seen as a late, downstream and disconnected event entirely up to clinicians or other end-users. Despite increasing involvement of patients in research, frameworks and tools enabling effective interactions of the multiple stakeholders required to bring innovation are scantly available in the academic biomedical field. Interactions between academia and industry are difficult even at pre-competitive levels [1,2,3,4,5,6].

Unsurprisingly, the attrition rate of biomedical research is greater than 90% across different diseases [7]. 85% of the biomarker qualification procedures ever submitted to the EMA for any medical field failed, mostly due to gaps at very early development steps [8]. Clinical guidelines must be defined by expert consensus despite extensive literature, failing to demonstrate clinical validity [2, 9]. Besides delaying benefits to patients, such inconsistent proceeding results in high costs to society, investing in translational research that may be more efficient.

General frameworks for more efficient translation exist [10,11,12], but concrete projects converging needs and constraints from heterogeneous stakeholders are still sparse [13]. Specific definitions of the translational steps from bench to bed-side are available for many fields [14], but are not consistently followed, also due to lack of co-development with relevant stakeholders. Some regulators offer services and initiatives to increase interaction with researchers, but these are scantly known and used, or treat issues at too a high level to achieve concrete impact. The biomedical academic ecosystem may not dispose of the same clarity of objectives and system of incentives characterizing the technology field. This aspect makes Translational Process particularly complementary to the Ecosystems section in this Journal [15].

At the same time, ambitious projects and grant frameworks do aim to bring innovation, rightly leveraging interactions between academia and industry (e.g., the current European Innovative Health Initiative). However, consistent with pragmatic industrial practices and the lack of a specific discipline representing the field, much of the performed work is not published in scientific journals, hurdling retrieval to others needing similar methods. Efforts are thus duplicated, not leveraged upon, or inconsistent with each-other. Similarly, conflicts of interest go unchecked, lacking a framework seeking to capture those beyond direct involvement with pharma companies.

Do we dispose of well-defined translational methods? How can such methods be co-defined with relevant stakeholders, incorporating their needs, requirements and constraints at all development steps? How can new such methods be implemented among academic researchers? How can we dynamically assess the quality of our proceeding, monitor our action, and adjust it as needed, limiting waste and attrition? How can we capture and protect the translational process from the wider range of conflicts of interest scattered on its route?

This section dedicates a space to those who tackle such challenges overcoming the boundaries of individual disciplines. Through a high-standard peer-review process, the Journal of Translational Medicine offers a new opportunity to share and accelerate the development of urgently needed methods, tools and procedures. We warmly look forward to receiving your contributions and streamline the journey along the translational continuum.

References

  1. Garner JP. The significance of meaning: why do over 90% of behavioral neuroscience results fail to translate to humans, and what can we do to fix it? ILAR J. 2014;55(3):438–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Boccardi M, Festari C, Altomare D, Gandolfo F, Orini S, Nobili F, Frisoni GB. Assessing FDG-PET diagnostic accuracy studies to develop recommendations for clinical use in dementia. Eur J Nucl Med Mol Imaging. 2018;45(9):1470–86.

    Article  CAS  PubMed  Google Scholar 

  3. Frisoni GB, Boccardi M, Barkhof F, Blennow K, Cappa S, Chiotis K, Demonet JF, Garibotto V, Giannakopoulos P, Gietl A, et al. Strategic roadmap for an early diagnosis of Alzheimer’s disease based on biomarkers. Lancet Neurol. 2017;16(8):661–76.

    Article  PubMed  Google Scholar 

  4. Whiting P, Rutjes AWS, Reitsma JB, Glas AS, Bossuyt PMM, Kleijnen J. Sources of variation and bias in studies of diagnostic accuracy: a systematic review. Ann Intern Med. 2004;140(3):189–202.

    Article  PubMed  Google Scholar 

  5. Drucker E, Krapfenbauer K. Pitfalls and limitations in translation from biomarker discovery to clinical utility in predictive and personalised medicine. EPMA J. 2013;4(1): 7.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Boccardi M, Handels R, Gold M, Grazia A, Lutz MW, Martin M, Nosheny R, Robillard JM, Weidner W, Alexandersson J, et al. Clinical research in dementia: a perspective on implementing innovation. Alzheimer’s Dement J Alzheimer’s Assoc. 2022. https://doi.org/10.1002/alz.12622.

    Article  Google Scholar 

  7. Thomas D, Chancellor D, Micklus A, LaFever S, Hay M, Chaudhuri S, Bowden R, Lo AW. Clinical development success rates and contributing factors 2011–2020. BIO, Informa Pharma Intelligence, and QLS advisors. 2021. https://www.bio.org/clinical-development-success-rates-and-contributing-factors-2011-2020.

  8. Bakker E, Hendrikse NM, Ehmann F, van der Meer DS, Llinares Garcia J, Vetter T, Starokozhko V, Mol PGM. Biomarker qualification at the European medicines agency: a review of biomarker qualification procedures from 2008 to 2020. Clin Pharmacol Ther. 2022;112(1):69–80.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Smailagic N, Vacante M, Hyde C, Martin S, Ukoumunne O, Sachpekidis C. (1)(8)F-FDG PET for the early diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev. 2015;1:CD010632.

    PubMed  Google Scholar 

  10. Cohrs RJ, Martin T, Ghahramani P, Bidaut L, Higgins PJ, Shahzad A. Translational medicine definition by the European society for translational medicine. New Horiz Transl Med. 2015;2:86–8.

    Google Scholar 

  11. Zimmern RL, Kroese M. The evaluation of genetic tests. J Public Health. 2007;29(3):246–50.

    Article  Google Scholar 

  12. Waldman SA, Terzic A. Clinical and translational science: from bench-bedside to global village. Clin Transl Sci. 2010;3(5):254–7.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Huddy JR, Ni M, Misra S, Mavroveli S, Barlow J, Hanna GB. Development of the point-of-care key evidence tool (POCKET): a checklist for multi-dimensional evidence generation in point-of-care tests. Clin Chem Lab Med. 2019;57(6):845–55.

    Article  CAS  PubMed  Google Scholar 

  14. Lijmer JG, Leeflang M, Bossuyt PMM. Proposals for a phased evaluation of medical tests. Med Decis Mak. 2009;29(5):E13–21.

    Article  Google Scholar 

  15. Mahant V. Translational medicines ecosystem. J Transl Med. 2020;18(1):158.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

Vijay Mahant provided helpful comments on the ethical perspective.

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Correspondence to Marina Boccardi.

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Boccardi, M. Translational process. J Transl Med 21, 677 (2023). https://doi.org/10.1186/s12967-023-04507-7

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  • DOI: https://doi.org/10.1186/s12967-023-04507-7