iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://doi.org/10.1038/s41582-020-00446-9
Facing the urgency of therapies for progressive MS — a Progressive MS Alliance proposal | Nature Reviews Neurology
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:

Facing the urgency of therapies for progressive MS — a Progressive MS Alliance proposal

Nature Reviews Neurology volume 17, pages 185–192 (2021)Cite this article

Subjects

Abstract

Therapies for infiltrative inflammation in multiple sclerosis (MS) have advanced greatly, but neurodegeneration and compartmentalized inflammation remain virtually untargeted as in other diseases of the nervous system. Consequently, many therapies are available for the relapsing–remitting form of MS, but the progressive forms remain essentially untreated. The objective of the International Progressive MS Alliance is to expedite the development of effective therapies for progressive MS through new initiatives that foster innovative thinking and concrete advancements. Based on these principles, the Alliance is developing a new funding programme that will focus on experimental medicine trials. Here, we discuss the reasons behind the focus on experimental medicine trials, the strengths and weaknesses of these approaches and of the programme, and why we hope to advance therapies while improving the understanding of progression in MS. We are soliciting public and academic feedback, which will help shape the programme and future strategies of the Alliance.

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

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Fig. 1: Balancing innovation with comparability.
Fig. 2: Markers of biological and paraclinical efficacy.
Fig. 3: Proposed set of core measures to obtain information on clinical, paraclinical and immunological effects.

Similar content being viewed by others

References

  1. Fox, R. J. et al. Setting a research agenda for progressive multiple sclerosis. The International Collaborative on Progressive MS. Mult. Scler. 18, 1534–1540 (2012).

    PubMed  PubMed Central  Google Scholar 

  2. Deshmukh, V. A. et al. A regenerative approach to the treatment of multiple sclerosis. Nature 502, 327–332 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Mei, F. et al. Micropillar arrays as high-throughput screening platform for therapeutics in multiple sclerosis. Nat. Med. 20, 954–960 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Najm, F. J. et al. Drug-based modulation of endogenous stem cells promotes functional remyelination in vivo. Nature 522, 216–220 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Eleuteri, C. et al. A staged screening of registered drugs highlights remyelinating drug candidates for clinical trials. Sci. Rep. 7, 45780 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Rankin, K. A. et al. Selective estrogen receptor modulators enhance CNS remyelination independent of estrogen receptors. J. Neurosci. 39, 2184–2194 (2019).

    PubMed  PubMed Central  Google Scholar 

  7. Baker, D., Lidster, K., Sottomayor, A. & Amor, S. Two years later: journals are not yet enforcing the ARRIVE guidelines on reporting standards for pre-clinical animal studies. PLoS Biol. 12, e1001756 (2014).

    PubMed  PubMed Central  Google Scholar 

  8. Kilkenny, C., Browne, W. J., Cuthill, I. C., Emerson, M. & Altmann, D. G. Improving bioscience research reporting: the ARRIVE guidelines for reporting animal research. PLoS Biol. 8, e1000412 (2010).

    PubMed  PubMed Central  Google Scholar 

  9. Baker, D. & Amor, S. Publication guidelines for refereeing and reporting on animal use in experimental autoimmune encephalomyelitis. J. Neuroimmunol. 242, 78–83 (2012).

    CAS  PubMed  Google Scholar 

  10. Baker, D. & Amor, S. Checklist for reporting and reviewing studies of experimental animal models of multiple sclerosis and related disorders. Mult. Scler. Relat. Disord. 1, 111–115 (2012).

    PubMed  Google Scholar 

  11. Bergman, J. et al. Intrathecal treatment of rituximab in progressive MS. Neurology 91, 1893–1901 (2018).

    Google Scholar 

  12. Kosa, P. et al. Idebenone does not inhibit disability progression in primary progressive MS. Mult. Scler. Relat. Disord. https://doi.org/10.1016/j.msard.2020.102434 (2020).

    Article  PubMed  Google Scholar 

  13. Gnanapavan, S. et al. Biomarker report from the phase II lamotrigine trial in secondary progressive MS – neurofilament as a surrogate of disease progression. PLoS ONE 8, e70019 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Green, A. J. et al. Clemastine and fumarate as a remyelinating therapy for multiple sclerosis (ReBUILD): a randomized, controlled, double-blind, crossover trial. Lancet 390, 2481–2489 (2017).

    CAS  PubMed  Google Scholar 

  15. Komori, M. et al. Insufficient disease inhibition by intrathecal rituximab in progressive multiple sclerosis. Ann. Clin. Transl. Neurol. 3, 166–179 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Brubaker, D. K. & Lauffenburger, D. A. Translating preclinical models to humans. Science 367, 742–743 (2020).

    CAS  PubMed  Google Scholar 

  17. Brubaker, D. K. et al. An interspecies translation model implicates integrin signaling in infliximab-resistant inflammatory bowel disease. Sci. Signal. 13, eaay3258 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Kennedy, M. E. et al. The BACE1 inhibitor verubecestat (MK-8931) reduces CNS β-amyloid in animal models and in Alzheimer’s disease patients. Sci. Transl Med. 8, 363ra150 (2016).

    PubMed  Google Scholar 

  19. Egan, M. F. et al. Randomized trial of verubecestat for prodromal Alzheimer’s disease. N. Engl. J. Med. 380, 1408–1420 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Henley, D. et al. Preliminary results of a trial of atabecestat in pre-clinical Alzheimer’s disease. N. Engl. J. Med. 380, 1483–1485 (2019).

    PubMed  Google Scholar 

  21. Li, S., Liu, L. & Selkoe, D. Verubecestat for prodromal Alzheimer’s disease. N. Engl. J. Med. 381, 388–389 (2019).

    PubMed  PubMed Central  Google Scholar 

  22. Dubuisson, N., Puentes, F., Giovannoni, G. & Gnanapavan, S. Science is 1% inspiration and 99% biomarkers. Mult. Scler. J. 23, 1442–1452 (2017).

    CAS  Google Scholar 

  23. Franklin, R. J. M. & Ffrench-Constant, C. Regenerating CNS myelin: from mechanisms to experimental medicines. Nat. Rev. Neurosci. 18, 753–769 (2017).

    CAS  PubMed  Google Scholar 

  24. Hauser, S. L. Progress in multiple sclerosis research: an example of bedside to bench. JAMA 324, 841–842 (2020).

    PubMed  Google Scholar 

  25. FitzGerald, G. et al. The future of humans as model organisms. Science 361, 552–553 (2018).

    CAS  PubMed  Google Scholar 

  26. Klotz, L. et al. Teriflunomide treatment for multiple sclerosis modulates T cell mitochondrial respiration with affinity-dependent effects. Sci. Transl Med. 11, eaao5563 (2019).

    CAS  PubMed  Google Scholar 

  27. Insel, T. R. The NIMH experimental medicine initiative. World Psychiatry 15, 151–153 (2015).

    Google Scholar 

  28. Plenge, R. M. Disciplined approach to drug discovery and early development. Sci. Transl Med. 8, 349ps15 (2016).

    PubMed  Google Scholar 

  29. Fang, H. et al. A genetics-led approach defines the drug target landscape of 30 immune-related traits. Nat. Genet. 51, 1082–1091 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Woodcock, J. & LaVange, L. M. Master protocols to study multiple therapies, multiple diseases, or both. N. Engl. J. Med. 377, 62–74 (2017).

    CAS  PubMed  Google Scholar 

  31. Pardini, M., Cutter, G. & Sormani, M. P. Multiple sclerosis: clinical trial design 2019. Curr. Opin. Neurol. 32, 358–364 (2019).

    PubMed  Google Scholar 

  32. Dickson, D. et al. The master observational trial: a new class of master protocol to advance precision medicine. Cell 180, 9–14 (2020).

    CAS  PubMed  Google Scholar 

  33. Granovetter, M. The strength of weak ties. Am. J. Sociol. 78, 1360–1380 (1973).

    Google Scholar 

  34. Bodin, O. Collaborative environmental governance: Achieving collective action in social-ecological systems. Science 357, eaan1114 (2017).

    PubMed  Google Scholar 

  35. Cipriani, A. & Barbui, C. What is a factorial trial. Epidemiol. Psychiatr. Sci. 22, 213–215 (2013).

    CAS  PubMed  Google Scholar 

  36. Food and Drug Administration. FDA Guidance for Industry: codevelopment of two or more new investigational drugs for use in combination. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/codevelopment-two-or-more-new-investigational-drugs-use-combination (2013).

  37. Romano, S. et al. Drug holiday of interferon beta 1b in multiple sclerosis: a pilot, randomized, single-blind study of non-inferiority. Front. Neurol. 10, 695 (2019).

    PubMed  PubMed Central  Google Scholar 

  38. Conway, D. & Cohen, J. A. Combination therapy in multiple sclerosis. Lancet Neurol. 9, 299–308 (2010).

    PubMed  Google Scholar 

  39. Cohen, J. A. et al. Avonex combination trial in relapsing–remitting MS: rationale, design and baseline data. Mult. Scler. 14, 370–382 (2008).

    CAS  PubMed  Google Scholar 

  40. Cohen, J. A. et al. Results of the Avonex Combination Trial (ACT) in relapsing-remitting MS. Neurology 72, 535–541 (2009).

    CAS  PubMed  Google Scholar 

  41. Lublin, F. D. et al. Randomized study combining interferon and glatiramer acetate in multiple sclerosis. Ann. Neurol. 73, 327–340 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Mandolesi, G. et al. miR-142-3p is a key regulator of IL-1beta-dependent synaptopathy in neuroinflammation. J. Neurosci. 37, 546–561 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Lago, S. G. et al. Drug discovery for psychiatric disorders using high-content single-cell screening of signaling network responses ex vivo. Sci. Adv. 5, eaau9093 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Hartmann, F. J. et al. Comprehensive immune monitoring of clinical trials to advance human immunotherapy. Cell Rep. 28, 819–831 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Inoue, H., Nagata, N., Kurokawa, H. & Yamanaka, S. iPS cells: a game changer for future medicine. EMBO J. 33, 409–417 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Ashton, N. J. et al. An update on blood-based biomarkers for non-Alzheimer neurodegenerative disorders. Nat. Rev. Neurol. 16, 265–284 (2020).

    PubMed  Google Scholar 

  47. Dubal, D. B. & Pleasure, S. J. Neural-derived extracellular vesicles in clinical trials: message in a bottle. JAMA Neurol. 76, 402–404 (2019).

    PubMed  Google Scholar 

  48. Nelson, M. R. et al. The support of human genetic evidence for approved drug indications. Nat. Genet. 47, 856–860 (2015).

    CAS  PubMed  Google Scholar 

  49. Floris, M., Olla, S., Schlessinger, D. & Cucca, F. Genetic-driven druggable target identification and validation. Trends Genet. 34, 558–570 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Khramtsova, E. A., Davis, L. K. & Stranger, B. E. The role of sex in the genomics of human complex traits. Nat. Rev. Genet. 20, 173–190 (2019).

    CAS  PubMed  Google Scholar 

  51. Alroughani, R. et al. Is time to reach EDSS 6.0 faster in patients with late-inset vs young-onset multiple sclerosis? PLoS ONE 11, e0165846 (2016).

    PubMed  PubMed Central  Google Scholar 

  52. Cinar, B. P. & Yorgun, Y. G. What we learned from the history of multiple sclerosis measurement: expanded disability status scale. Noro Psikiyatr. Ars. 55 (Suppl. 1), S69–S75 (2018).

    PubMed  PubMed Central  Google Scholar 

  53. Smith, K. A. et al. Comorbid disease burden among MS patients 1968-2012: a Swedish register-based cohort study. Mult. Scler. J. https://doi.org/10.1177/1352458520910497 (2020).

    Article  Google Scholar 

  54. Berry, D. A. The Brave New World of clinical cancer research: adaptive biomarker-driven trials integrating clinical practice with clinical research. Mol. Oncol. 9, 951–959 (2015).

    PubMed  PubMed Central  Google Scholar 

  55. McFarland, H. F. et al. Using gadolinium-enhanced magnetic resonance imaging lesions to monitor disease activity in multiple sclerosis. Ann. Neurol. 32, 758–766 (1992).

    CAS  PubMed  Google Scholar 

  56. Frank, J. A. et al. Serial contrast-enhanced magnetic resonance imaging in patients with early relapsing-remitting multiple sclerosis: implications for treatment trials. Ann. Neurol. 36, S86–S90 (1994).

    PubMed  Google Scholar 

  57. Nauta, J. J., Thompson, A. J., Barkhof, F. & Miller, D. H. Magnetic resonance imaging in monitoring the treatment of multiple sclerosis patients: statistical power of parallel-groups and crossover designs. J. Neurol. Sci. 122, 6–14 (1994).

    CAS  PubMed  Google Scholar 

  58. Pallmann, P. et al. Adaptive designs in clinical trials: why use them, and how to run and report them. BMC Med. https://doi.org/10.1186/s12916-018-1017-7 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

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

    Google Scholar 

  60. Chataway, J. et al. Efficacy of three neuroprotective drugs in secondary progressive multiple sclerosis (MS-SMART): a phase 2b, multiarm, double-blind, randomised placebo-controlled trial. Lancet Neurol. 19, 214–225 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Renfro, L. A. & Sargent, D. J. Statistical controversies in clinical research: basket trials, umbrella trials, and other master protocols: a review and examples. Ann. Oncol. 28, 34–43 (2017).

    CAS  PubMed  Google Scholar 

  62. Zarin, D. A., Goodman, S. N. & Kimmelman, J. Harms from uninformative clinical trials. JAMA https://doi.org/10.1001/jama.2019.9892 (2019).

    Article  PubMed  Google Scholar 

  63. Rieckmann, P. et al. Unmet needs, burden of treatment, and patient engagement in multiple sclerosis: A combined perspective from the MS in the 21st Century Steering Group. Mult. Scler. Rel. Disord. 19, 153–160 (2018).

    Google Scholar 

  64. Levitan, B. et al. Assessing the financial value of patient engagement: a quantitative approach from CTTI’s patient groups and clinical trials project. Ther. Innov. Regul. Sci. 52, 220–229 (2018).

    PubMed  Google Scholar 

  65. Salvetti, M. et al. Steps towards collective sustainability in biomedical research. Trends Mol. Med. 24, 429–432 (2018).

    PubMed  Google Scholar 

  66. Solaro, C. et al. Box and block test, hand grip strength and nine-hole peg test: correlations between three upper limb objective measures in multiple sclerosis. Eur. J. Neurol. 27, 2523–2530 (2020).

    CAS  PubMed  Google Scholar 

  67. Newsome, S. D. et al. Longitudinal assessment of hand function in individuals with multiple sclerosis. Mult. Scler. Relat. Disord. 32, 107–113 (2019).

    PubMed  PubMed Central  Google Scholar 

  68. Kapoor, R. et al. Serum neurofilament light as a biomarker in progressive multiple sclerosis. Neurology 95, 436–444 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Williams, T., Zetterberg, H. & Chataway, J. Neurofilaments in multiple sclerosis. A systematic review. J. Neurol. https://doi.org/10.1007/s00415-020-09917-x (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Amiri, H. et al. Urgent challenger in quantification and interpretation of brain grey matter atrophy in individual MS patients using MRI. Neuroimage Clin. 19, 466–475 (2020).

    Google Scholar 

  71. Leocani, L., Guerrieri, S. & Comi, G. Visual evoked potentials as a biomarker in multiple sclerosis and associated optic neuritis. J. Neuroophtalmol. 38, 350–357 (2018).

    Google Scholar 

  72. Cruz-Herranz, A. et al. The APOSTEL recommendations for reporting quantitative optical coherence tomography studies. Neurology 86, 2303–2309 (2016).

    PubMed  PubMed Central  Google Scholar 

  73. International Progressive Multiple Sclerosis Alliance. Collaborative Network Awards. https://www.progressivemsalliance.org/research/collaborative-network-awards/ (2020).

  74. Simon, N. & Simon, R. Adaptive enrichment designs for clinical trials. Biostatistics 14, 613–625 (2013).

    PubMed  PubMed Central  Google Scholar 

  75. Koch, M. W. et al. The promise of futility trials in neurological diseases. Nat. Rev. Neurol. 11, 300–305 (2015).

    PubMed  Google Scholar 

  76. Sibbaid, B. & Roberts, C. Understanding controlled trials. Crossover trials. BMJ 316, 1719 (1998).

    Google Scholar 

Download references

Acknowledgements

The authors thank Dr Robert J. Fox for critically reading the manuscript.

Author information

Author notes

  1. Representative of Industry Forum members of the International Progressive MS Alliance: Fernando Dangond

Authors and Affiliations

  1. EMD Serono, Billerica, MA, USA

    Fernando Dangond

  2. Department of Computer Science, O’Reilly Institute, Trinity College, Dublin, Ireland

    Alexis Donnelly

  3. Institute of Clinical Neuroimmunology, Biomedical Center and Hospital of the Ludwig Maximilians Universität München, Munich, Germany

    Reinhard Hohlfeld

  4. Munich Cluster for Systems Neurology (Synergy), Munich, Germany

    Reinhard Hohlfeld

  5. Neurology Department, Sorbonne University, Pitié-Salpêtrière Hospital, Paris, France

    Catherine Lubetzki

  6. Multiple Sclerosis Society UK, London, UK

    Susan Kohlhaas

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

    Letizia Leocani

  8. Neurorehabilitation Department and Experimental Neurophysiology Unit, INSPE, Scientific Institute Hospital San Raffaele, Milan, Italy

    Letizia Leocani

  9. Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK

    Olga Ciccarelli & Jeremy Chataway

  10. National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK

    Olga Ciccarelli & Jeremy Chataway

  11. Sorbonne University, Brain and Spine Institute, ICM, Pitié-Salpêtrière Hospital, Paris, France

    Bruno Stankoff

  12. Department of Health Sciences (DISSAL), University of Genova, Genova, Italy

    Maria Pia Sormani

  13. IRCCS Ospedale Policlinico San Martino, Genova, Italy

    Maria Pia Sormani

  14. Italian Multiple Sclerosis Society, Genoa, Italy

    Federico Bozzoli

  15. Dipartimento di Scienze Biomediche, Università di Sassari, Sassari, Italy

    Francesco Cucca

  16. MS Research Australia, North Sydney, New South Wales, Australia

    Lisa Melton

  17. National Multiple Sclerosis Society, New York, NY, USA

    Timothy Coetzee

  18. Department of Neurosciences, Mental Health and Sensory Organs, Centre for Experimental Neurological Therapies (CENTERS), Faculty of Medicine and Psychology, Sapienza University, Rome, Italy

    Marco Salvetti

  19. IRCCS Istituto Neurologico Mediterraneo (INM) Neuromed, Pozzilli, Italy

    Marco Salvetti

Authors
  1. Fernando Dangond
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alexis Donnelly
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Reinhard Hohlfeld
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Catherine Lubetzki
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Susan Kohlhaas
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Letizia Leocani
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Olga Ciccarelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Bruno Stankoff
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Maria Pia Sormani
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jeremy Chataway
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Federico Bozzoli
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Francesco Cucca
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Lisa Melton
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Timothy Coetzee
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Marco Salvetti
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

F.D., S.K., L.M. and M.S. researched data for the article. F.D., A.D., R.H., C.L., S.K., L.L., O.C., B.S., M.P.S., J.C., T.C. and M.S. contributed to writing of the manuscript. All authors made substantial contributions to discussion of the content and reviewed and edited the manuscript before submission.

Corresponding author

Correspondence to Marco Salvetti.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information

Nature Reviews Neurology thanks B. Wienstock-Guttman, H. Weiner and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note

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

Related links

International Progressive MS Alliance: https://www.progressivemsalliance.org/

Immune Tolerance Network: https://www.immunetolerance.org

Sage Bionetworks: http://sagebionetworks.org/

The MULTI-ACT project: https://www.multiact.eu/

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dangond, F., Donnelly, A., Hohlfeld, R. et al. Facing the urgency of therapies for progressive MS — a Progressive MS Alliance proposal. Nat Rev Neurol 17, 185–192 (2021). https://doi.org/10.1038/s41582-020-00446-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41582-020-00446-9

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