Improving the Effect of Multiple Sclerosis Drugs by Chronobiology

NCT06385197 | Completed

• 1 other identifier: 170886-HMO-CTIL
• Study Type: interventional
• Target: 8
• Locations: 1 country
• Sites: 1

Brief Summary

A trial for evaluating the ability to improve the effect of dimethyl fumarate in patients with Multiple Sclerosis (MS) by chronobiology A controlled-randomization dosing regimen administered to patients with MS and provided by a designated app. The treatment limitations of time interval is pre-defined according to approved therapeutic windows.

Conditions

Multiple Sclerosis

Outcome Measures

Primary Outcomes (3)

• safety assessment

  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

  12 weeks

• assessment of AE

  physical examination and assessment by EDSS score

  12 weeks

• assessment of AE

  laboratory tests - detect changes in cbc for lymphopenia (below 1.03 10e9/L)

  12 weeks

Study Arms (1)

patients using the app for dosing regimen

EXPERIMENTAL

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

Device: App randomizing dosing regimen

Interventions

App randomizing dosing regimen DEVICE

patients will receive their dimethyl fumarate treatment and the dose and time of administration will be determined using a designated app.

patients using the app for dosing regimen

Eligibility Criteria

• Age: 18 Years - 60 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64)

You may qualify if:

• 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.

You may not qualify if:

• \. Active malignancy or any malignancy diagnosed in the last 5 years or previous diagnosis of hepatocellular carcinoma at any time.
• \. 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.
• \. Patients with an inability to communicate well with the PI and staff (i.e., language problem, poor mental development or impaired cerebral function).
• \. 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.
• \. 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

Sponsors & Collaborators

• Hadassah Medical Organization: lead

Study Sites (1)

Hadassah Medical Center

Jerusalem, Israel

Location

Related Publications (12)

• 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.

  PMID: 32426039 BACKGROUND

• 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.

  PMID: 32472385 BACKGROUND

• 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.

  PMID: 32384308 BACKGROUND

• 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.

  PMID: 31786463 BACKGROUND

• 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.

  PMID: 27260297 BACKGROUND

• 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.

  PMID: 8622511 BACKGROUND

• 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.

  PMID: 30416733 BACKGROUND

• 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.

  PMID: 19376980 BACKGROUND

• 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.

  PMID: 27445759 BACKGROUND

• 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.

  PMID: 28258544 BACKGROUND

• 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.

  PMID: 27023045 BACKGROUND

• 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.

  BACKGROUND

MeSH Terms

Conditions

Multiple Sclerosis

Condition Hierarchy (Ancestors)

Demyelinating Autoimmune Diseases, CNS; Autoimmune Diseases of the Nervous System; Nervous System Diseases; Demyelinating Diseases; Autoimmune Diseases; Immune System Diseases

Study Officials

• yoav hershkovtiz, md

  Hadassah Medical Organization

  STUDY DIRECTOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DEVICE FEASIBILITY
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: A controlled-randomization dosing regimen administered to patients with MS and provided by a designated app. The treatment limitations of time interval is pre-defined according to approved therapeutic windows.

Study Record Dates

• First Submitted: April 17, 2024
• First Posted: April 25, 2024
• Study Start: May 8, 2022
• Primary Completion: June 1, 2023
• Study Completion: June 2, 2023
• Last Updated: May 6, 2024

Record last verified: 2023-11

Locations

IL (1)