- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06385197
Improving the Effect of Multiple Sclerosis Drugs by Chronobiology
Improving the Effect of Dimethyl Fumarate and Diroximel Fumarate (DRF) for Patients With Multiple Sclerosis by Chronobiology
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Dimethyl fumarate (DMF) is an oral option for patients with relapsing forms of MS. The effectiveness of DMF on the clinical and radiological activity of multiple sclerosis were demonstrated in a real-world setting, both in naive patients and in those switching from other multiple sclerosis therapies. Sustained safety and efficacy of DMF was observed in patients continuing on treatment for up to 11 years, supporting DMF as a long-term treatment option for patients with MS. It continues to be an efficacious treatment for multiple sclerosis with a favorable safety profile demonstrated over 10 years of clinical use Patients who have partial response or non-responders in most cases require different medications associated with a less favorable safety profile. Recently fda approved Diroximel fumarate (DRF) is a noval drug which is bioequivalent to DMF regarding efficacy and safety profiles, differing only by chemical precursor structure which is hypothesized to elicit less irritation in the GI tract than DMF. Both drug active metabolites are similar in bioactivity and efficacy treating MS Many aspects of cellular physiology display circadian (approximately 12-h) rhythms. Dysfunction of the circadian clock molecular circuitry is associated with human health derangements, including neurodegeneration, increased risk of cancer, cardiovascular diseases and the metabolic syndrome. Recent evidences support a link between the circadian clock circuitry and biological cycles in multiple systems. Regular dosing of therapy may lead to compensatory mechanisms and are associated with adaptation of the immune system that may prohibit a maximal clinical effect.
This open-label study will test the implementation of controlled randomization of time of administration of Dimethyl fumarate to patients with MS. Random changes in the time of administration and dosages of Dimethyl fumarate within pre-defined approved limits which are within the approved therapeutic window will be provided to patient by a designated cellular application. Patients will be followed for 12 weeks for clinical improvement using the Expanded Disability Status Scale (EDSS) and MRI.
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Locations
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Jerusalem, Israel
- Hadassah Medical Center
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Age between 18-60 at the time of enrollment
- A diagnosis of MS and treatment with dimethyl fumarateDimethyl fumarate or Diroximel fumarate for at least 6 months
- Females of childbearing potential must be non-pregnant (as determined by a serum pregnancy test at enrollment) and agree to use adequate contraceptive means throughout the study.
- Patients must be able to adhere to the visit schedule and protocol requirements and be available to complete the study.
- Patients must satisfy a medical examiner about their fitness to participate in the study.
- Patients must provide written informed consent to participate in the study.
Exclusion Criteria:
1. Active malignancy or any malignancy diagnosed in the last 5 years or previous diagnosis of hepatocellular carcinoma at any time.
2. Known human deficiency virus (HIV) or Hepatitis virus infections. 3. The use of steroids, or other immunosuppression. 4. Participation in another clinical trial within 30 days prior to intervention.
5. Patients with an inability to communicate well with the PI and staff (i.e., language problem, poor mental development or impaired cerebral function).
6. Patients who will be unavailable for the duration of the trial, are likely to be noncompliant with the protocol, or who are felt to be unsuitable by the PI for any other reason.
7. Any underlying medical condition that in the opinion of the study investigator impair the ability of the patient to complete the follow-up or to receive the planned treatment regimen
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Device Feasibility
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
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Experimental: patients using the app for dosing regimen
All of the enrolled patients will receive their dimethyl fumarate prescribed by their GP.
During the 12 weeks' study period, patients in the intervention arm will receive the medication timed by the app- dose and time of administration will be determined using a designated app.
The app will implement random changes in time of administration limited by a pre-defined range assigned by the therapeutic windows
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patients will receive their dimethyl fumarate treatment and the dose and time of administration will be determined using a designated app.
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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safety assessment
Time Frame: 12 weeks
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The primary outcome is to assess to assess the safety of incorporating controlled randomization to Dimethyl fumarate dosing regimen provided by an app in patients with MS.
Safety will be assessed through clinical follow-up which will include history taking with emphasize on possible AE
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12 weeks
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assessment of AE
Time Frame: 12 weeks
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physical examination and assessment by EDSS score
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12 weeks
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assessment of AE
Time Frame: 12 weeks
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laboratory tests - detect changes in cbc for lymphopenia (below 1.03 10e9/L)
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12 weeks
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Collaborators and Investigators
Sponsor
Investigators
- Study Director: yoav hershkovtiz, md, Hadassah Medical Organization
Publications and helpful links
General Publications
- Gold R, Arnold DL, Bar-Or A, Fox RJ, Kappos L, Chen C, Parks B, Miller C. Safety and efficacy of delayed-release dimethyl fumarate in patients with relapsing-remitting multiple sclerosis: 9 years' follow-up of DEFINE, CONFIRM, and ENDORSE. Ther Adv Neurol Disord. 2020 May 12;13:1756286420915005. doi: 10.1177/1756286420915005. eCollection 2020. Erratum In: Ther Adv Neurol Disord. 2020 Oct 21;13:1756286420968357.
- Chinea A, Amezcua L, Vargas W, Okai A, Williams MJ, Su R, Parks B, Mendoza JP, Lewin JB, Jones CC. Real-World Safety and Effectiveness of Dimethyl Fumarate in Hispanic or Latino Patients with Multiple Sclerosis: 3-Year Results from ESTEEM. Neurol Ther. 2020 Dec;9(2):495-504. doi: 10.1007/s40120-020-00192-6. Epub 2020 May 29.
- Barros A, Sequeira J, de Sousa A, Parra J, Brum M, Pedrosa R, Capela C. Real-Word Effectiveness and Safety of Dimethyl Fumarate in a Multiple Sclerosis Portuguese Population. Clin Neuropharmacol. 2020 May/Jun;43(3):55-60. doi: 10.1097/WNF.0000000000000391.
- Lanzillo R, Moccia M, Palladino R, Signoriello E, Carotenuto A, Maniscalco GT, Sacca F, Bonavita S, Russo CV, Iodice R, Petruzzo M, Sinisi L, De Angelis M, Lavorgna L, De Rosa A, Romano F, Orlando V, Ronga B, Florio C, Lus G, Brescia Morra V. Clinical predictors of Dimethyl Fumarate response in multiple sclerosis: a real life multicentre study. Mult Scler Relat Disord. 2020 Feb;38:101871. doi: 10.1016/j.msard.2019.101871. Epub 2019 Nov 25.
- Miclea A, Leussink VI, Hartung HP, Gold R, Hoepner R. Safety and efficacy of dimethyl fumarate in multiple sclerosis: a multi-center observational study. J Neurol. 2016 Aug;263(8):1626-32. doi: 10.1007/s00415-016-8175-3. Epub 2016 Jun 3.
- Goldberger AL. Non-linear dynamics for clinicians: chaos theory, fractals, and complexity at the bedside. Lancet. 1996 May 11;347(9011):1312-4. doi: 10.1016/s0140-6736(96)90948-4. No abstract available.
- Singh N, Moneghetti KJ, Christle JW, Hadley D, Plews D, Froelicher V. Heart Rate Variability: An Old Metric with New Meaning in the Era of using mHealth Technologies for Health and Exercise Training Guidance. Part One: Physiology and Methods. Arrhythm Electrophysiol Rev. 2018 Aug;7(3):193-198. doi: 10.15420/aer.2018.27.2.
- Shields RW Jr. Heart rate variability with deep breathing as a clinical test of cardiovagal function. Cleve Clin J Med. 2009 Apr;76 Suppl 2:S37-40. doi: 10.3949/ccjm.76.s2.08.
- Konig N, Singh NB, Baumann CR, Taylor WR. Can Gait Signatures Provide Quantitative Measures for Aiding Clinical Decision-Making? A Systematic Meta-Analysis of Gait Variability Behavior in Patients with Parkinson's Disease. Front Hum Neurosci. 2016 Jun 30;10:319. doi: 10.3389/fnhum.2016.00319. eCollection 2016.
- Nayyar S, Hasan MA, Roberts-Thomson KC, Sullivan T, Baumert M. Effect of Loss of Heart Rate Variability on T-Wave Heterogeneity and QT Variability in Heart Failure Patients: Implications in Ventricular Arrhythmogenesis. Cardiovasc Eng Technol. 2017 Jun;8(2):219-228. doi: 10.1007/s13239-017-0299-9. Epub 2017 Mar 3.
- Moon Y, Sung J, An R, Hernandez ME, Sosnoff JJ. Gait variability in people with neurological disorders: A systematic review and meta-analysis. Hum Mov Sci. 2016 Jun;47:197-208. doi: 10.1016/j.humov.2016.03.010. Epub 2016 Mar 26.
- Moon Y, Sung J, An R, Hernandez ME, Sosnoff JJ. Gait variability in people with neurological disorders: A systematic review and meta-analysis. Hum Mov Sci. 2016;47:197-208. 14. Leino AD, King EC, Jiang W, et al. Assessment of tacrolimus intrapatient variability in stable adherent transplant recipients: Establishing baseline values. Am J Transplant. 2018. 15. Gueta I, Markovits N, Yarden-Bilavsky H, et al. High tacrolimus trough level variability is associated with rejections after heart transplant. Am J Transplant. 2018;18(10):2571-2578. 16. Gueta I, Markovits N, Yarden-Bilavsky H, et al. Intrapatient variability in tacrolimus trough levels after solid organ transplantation varies at different postoperative time periods. Am J Transplant. 2018. 17. Del Bello A, Congy-Jolivet N, Danjoux M, et al. High tacrolimus intra-patient variability is associated with graft rejection, and de novo donor-specific antibodies occurrence after liver transplantation. World J Gastroenterol. 2018;24(16):1795-1802. 18. Contin M, Alberghini L, Candela C, Benini G, Riva R. Intrapatient variation in antiepileptic drug plasma concentration after generic substitution vs stable brand-name drug regimens. Epilepsy Res. 2016;122:79-83. 19. Elgart V, Lin JR, Loscalzo J. Determinants of drug-target interactions at the single cell level. PLoS Comput Biol. 2018;14(12):e1006601. 20. Niederer SA, Lumens J, Trayanova NA. Computational models in cardiology. Nat Rev Cardiol. 2019;16(2):100-111. 21. Ilan Y. Overcoming Compensatory Mechanisms toward Chronic Drug Administration to Ensure Long-Term, Sustainable Beneficial Effects. Mol Ther Methods Clin Dev. 2020;18:335-344. 22. Kyriazis M. Practical applications of chaos theory to the modulation of human ageing: nature prefers chaos to regularity. Biogerontology. 2003;4(2):75-90. 23. Kessler A, Weksler-Zangen S, Ilan Y. Role of the Immune System and the Circadian Rhythm in the Pathogenesis of Chronic Pancreatitis: Establishing a Personalized Signature for Improving the Effect of Immunotherapies for Chronic Pancreatitis. Pancreas. 2020;49(8):1024-1032. 24. Potruch A, Khoury ST, Ilan Y. The role of chronobiology in drug-resistance epilepsy: The potential use of a variability and chronotherapy-based individualized platform for improving the response to anti-seizure drugs. Seizure. 2020;80:201-211. 25. Khoury T, Ilan Y. Introducing Patterns of Variability for Overcoming Compensatory Adaptation of the Immune System to Immunomodulatory Agents: A Novel Method for Improving Clinical Response to Anti-TNF Therapies. Front Immunol. 2019;10:2726. 26. Khoury T, Ilan Y. Introducing Patterns of Variability for Overcoming Compensatory Adaptation of the Immune System to Immunomodulatory Agents: A Novel Method for Improving Clinical Response to Anti-TNF Therapies. Frontiers in immunology. 2019;10:2726-2726. 27. Gelman R, Bayatra A, Kessler A, Schwartz A, Ilan Y. Targeting SARS-CoV-2 receptors as a means for reducing infectivity and improving antiviral and immune response: an algorithm-based method for overcoming resistance to antiviral agents. Emerg Microbes Infect. 2020;9(1):1397-1406.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 170886-HMO-CTIL
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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