Measuring a grey area in medication deployment reveals delays from invention to clinical use of rheumatoid arthritis medications
Editorial

Measuring a grey area in medication deployment reveals delays from invention to clinical use of rheumatoid arthritis medications

Mark Tatangelo

University Health Network, Toronto, ON, Canada

Correspondence to: Mark Tatangelo. 4EN-200 Elizabeth St., Toronto, ON 416 3404800, Canada. Email: Mark.tatangelo@mail.utoronto.ca.

Comment on: Lupatini EO, Zimmermann IR, Barreto JOM, et al. How long does it take to translate research findings into routine healthcare practice?—the case of biological drugs for rheumatoid arthritis in Brazil. Ann Transl Med 2022;10:738.


Submitted Jun 23, 2022. Accepted for publication Jul 20, 2022.

doi: 10.21037/atm-22-3234


Medical interventions, especially for new medications, often require large portions of time from discovery to use in patient care (1-3). Delays can include time for adequate testing for safety and efficacy, time for regulatory review, manufacturing certification, country-specific regulations, and other administrative reasons (4-6). Often steps are complex, opaque, and difficult to measure. Some difficulties researchers encounter are the noted secrecy among drug companies around product listing agreements, patient-level data from clinical trials, and a general lack of interest among funders for research measuring the administrative aspects of medication discovery and delivery (7,8).

For the factors listed above, among others, the work of Lupatini et al. is impactful because the authors have resorted to the difficult task of operationalizing administrative time between medication approval steps using publicly available data (6). The effort to systematically quantify time from first clinical trial to use in patients is laudable and difficult irrespective of clinical implications, highlighted by the paucity of research on this topic, especially in rheumatoid arthritis (RA). The author’s methods in this paper highlight effective ways of gathering and interpreting data from the administrative aspects of clinical trials and country-specific administrative data.

However, readers would be remiss to ignore the broad clinical implications of these findings for patients with RA: potentially beneficial medications are tested and approved, yet unavailable to clinician level use at the patient care level. These types of barriers to care are prototypical issues in health care delivery (9,10). Often, medical systems have a product but delay or suboptimal deploy medications at the clinician level. These barriers may seem insignificant, but when added together, many small obstacles create an additive problem in health care systems. To adopt an approach of total quality improvement, studies that measure administrative delay to the deployment of medications have value in identifying and reducing non-medically indicated delays to drug deployment.

The final thematic element of this study that readers can take away is specific to the rheumatology community and the treatment care paradigm for RA patients. Rheumatologists seek to control disease activity by prescribing one or more conventional synthetic disease-modifying anti-rheumatic drugs (csDMARD) alone or in combination with a biological disease-modifying anti-rheumatic drug (bDMARD) (11,12). As medications fail to achieve a clinical response (primary failure) or fail to continue to maintain an adequate clinical response after 90 or more days (secondary failure), rheumatologists can switch to different combinations of csDMARDs. They can prescribe different bDMARDs with only one active bDMARD prescription at a time. Once a bDMARD fails, the rheumatologist will generally not switch a patient back to that medication. Empirical estimates of time to failure of bDMARDs are wide-ranging and dependent on many factors; however, a reasonable estimate of time to failure assuming no primary failure could be 6 months–3 years per bDMARD (13-16). Therefore, given the similar lifespan of RA patients to non-diseased patients (17), new bDMARDs are constantly needed for rheumatologists to switch to effective therapies once old therapies have failed. This treatment paradigm highlights the potential impact of the author’s work because the faster deployment of bDMARDs allows rheumatologists to have more options for patients to switch to and maintain effective treatments. We also know that with more treatment options available, rheumatologists can change medications from sub-optimally performing when there are options to switch. Otherwise, a rheumatologist may continue to have patients continue on medication without alternative options. This situation described occurred early on in the deployment of bDMARDs where only 1–3 bDMARDs were available (18), constraining the clinician’s ability to switch medications because of a lack of viable alternative therapies. Therefore, given proven safety and efficacy profiles, we can see the marginal benefit to patients of additionally available bDMARDs as quickly as possible.

Overall, this paper measures an often-overlooked time in the medication approval process and has potential implications for treating rheumatoid arthritis and other chronic diseases.


Acknowledgments

Funding: None.


Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Annals of Translational Medicine. The article did not undergo external peer review.

Conflicts of Interest: The author has completed the ICMJE uniform disclosure form (available at https://atm.amegroups.com/article/view/10.21037/atm-22-3234/coif). The author has no conflicts of interest to declare.

Ethical Statement: The author is accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


References

  1. McNamee LM, Walsh MJ, Ledley FD. Timelines of translational science: From technology initiation to FDA approval. PLoS One 2017;12:e0177371. [Crossref] [PubMed]
  2. Tamimi NA, Ellis P. Drug development: from concept to marketing! Nephron Clin Pract 2009;113:c125-31. [Crossref] [PubMed]
  3. Robuck PR, Wurzelmann JI. Understanding the drug development process. Inflamm Bowel Dis 2005;11:S13-6. [Crossref] [PubMed]
  4. Medlinskiene K, Tomlinson J, Marques I, et al. Barriers and facilitators to the uptake of new medicines into clinical practice: a systematic review. BMC Health Serv Res 2021;21:1198. [Crossref] [PubMed]
  5. Lublóy Á. Factors affecting the uptake of new medicines: a systematic literature review. BMC Health Serv Res 2014;14:469. [Crossref] [PubMed]
  6. Lupatini EO, Zimmermann IR, Barreto JOM, et al. How long does it take to translate research findings into routine healthcare practice?—the case of biological drugs for rheumatoid arthritis in Brazil. Ann Transl Med 2022;10:738. [Crossref]
  7. Morgan SG, Friesen MK, Thomson PA, et al. Use of product listing agreements by Canadian provincial drug benefit plans. Healthc Policy 2013;8:45-55. [Crossref] [PubMed]
  8. Bourassa Forcier M, Noël F. Product listing agreements (PLAs): a new tool for reaching Quebec's pharmaceutical policy objectives? Healthc Policy 2013;9:65-75. [PubMed]
  9. Institute of Medicine (US) Committee on Quality of Health Care in America; Kohn LT, Corrigan JM, Donaldson MS. To Err is Human: Building a Safer Health System. Washington (DC): National Academies Press (US), 2000.
  10. Institute of Medicine (US) Committee on Quality of Health Care in America. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington (DC): National Academies Press (US), 2001.
  11. Fraenkel L, Bathon JM, England BR, et al. 2021 American College of Rheumatology Guideline for the Treatment of Rheumatoid Arthritis. Arthritis Care Res (Hoboken) 2021;73:924-39. [Crossref] [PubMed]
  12. Smolen JS, Landewé RBM, Bijlsma JWJ, et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2019 update. Ann Rheum Dis 2020;79:685-99. [Crossref] [PubMed]
  13. Pappas DA, Litman HJ, Lesperance T, et al. Persistence on biologic DMARD monotherapy after achieving rheumatoid arthritis disease control on combination therapy: retrospective analysis of corrona registry data. Rheumatol Int 2021;41:381-90. [Crossref] [PubMed]
  14. Blum MA, Koo D, Doshi JA. Measurement and rates of persistence with and adherence to biologics for rheumatoid arthritis: a systematic review. Clin Ther 2011;33:901-13. [Crossref] [PubMed]
  15. Murray K, Turk M, Alammari Y, et al. Long-term remission and biologic persistence rates: 12-year real-world data. Arthritis Res Ther 2021;23:25. [Crossref] [PubMed]
  16. Fisher A, Bassett K, Wright JM, et al. Comparative persistence of the TNF antagonists in rheumatoid arthritis--a population-based cohort study. PLoS One 2014;9:e105193. [Crossref] [PubMed]
  17. Widdifield J, Bernatsky S, Paterson JM, et al. Trends in Excess Mortality Among Patients With Rheumatoid Arthritis in Ontario, Canada. Arthritis Care Res (Hoboken) 2015;67:1047-53. [Crossref] [PubMed]
  18. Tatangelo M, Tomlinson G, Paterson JM, et al. Association of Patient, Prescriber, and Region With the Initiation of First Prescription of Biologic Disease-Modifying Antirheumatic Drug Among Older Patients With Rheumatoid Arthritis and Identical Health Insurance Coverage. JAMA Netw Open 2019;2:e1917053. [Crossref] [PubMed]
Cite this article as: Tatangelo M. Measuring a grey area in medication deployment reveals delays from invention to clinical use of rheumatoid arthritis medications. Ann Transl Med 2022;10(14):757. doi: 10.21037/atm-22-3234

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