Skip to main content
SpringerLink
Log in

Effect of Ponesimod Exposure on Total Lymphocyte Dynamics in Patients with Multiple Sclerosis

  • Original Research Article
  • Published:
Clinical Pharmacokinetics Aims and scope Submit manuscript

Abstract

Objective

The aim of this study was to characterize the relationship between ponesimod plasma concentrations and the temporal evolution of lymphocyte counts in multiple sclerosis (MS) patients.

Methods

Population pharmacokinetic (PK) and PK/pharmacodynamic (PD) models were developed using data from phase I, II, and III trials, and the impact of clinically relevant covariates on PK and PD parameters was assessed. Simulations were conducted to evaluate the maximal lymphocyte count reduction after ponesimod treatment, and the time required for total lymphocyte counts to return to normal values after treatment interruption.

Results

In MS patients, ponesimod PK were characterized by a low mean apparent plasma clearance (5.52 L/h) and a moderate mean apparent volume of distribution at steady state (239 L). The model developed indicated that none of the evaluated covariates (age, sex, formulation, food, body weight, clinical condition, and renal impairment) had a clinically relevant impact on the PK/PD parameters. In MS patients, total lymphocyte counts were characterized by a maximum reduction of 88.0% and a half maximal inhibitory concentration (IC50) of 54.9 ng/mL. Simulations indicated that in patients with normal hepatic function treated with ponesimod 20 mg daily, total lymphocyte counts were reduced to 41% of baseline at trough. After stopping treatment, lymphocyte counts were restored to normal levels within one week.

Conclusions

The population PK/PD model well-characterized the PK of ponesimod and the time course of total lymphocyte counts in MS patients. Additionally, none of the evaluated covariates had a clinically relevant impact. This should be taken into consideration when assessing the risk of infection, administration of live-attenuated vaccines, and concomitant use of immunosuppressants.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Modified from Lott et al. [17]. Circles denote compartments, solid lines denote drug flow with associated PK parameters, dotted lines indicate relationships. amp amplitude of the circadian rhythm, CL/F apparent clearance, Doral oral dose, Fr fraction of the drug absorbed via zero order, IC50 concentration required to reach half-maximum ponesimod effect, Imax maximum ponesimod effect, ka first-order absorption rate constant, kout first-order output rate constant, shift time shift of the circadian rhythm, PD pharmacodynamics, PK pharmacokinetics, Q/F apparent intercompartmental drug flow, Rin zero-order input rate, Tk0 duration of the zero-order absorption, Tlag absorption lag time, Vc/F apparent central volume of distribution, Vp/F apparent peripheral volume of distribution

Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Reich DS, Lucchinetti CF, Calabresi PA. Multiple Sclerosis. N Engl J Med. 2018;378(2):169–80.

    Article  CAS  Google Scholar 

  2. GBD 2016 Motor Neuron Disease Collaborators. Global, regional, and national burden of multiple sclerosis 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2016;18(3):269–85.

    Google Scholar 

  3. Dargahi NKM, Tselios T, Androutsou ME, de Courten M, Matsoukas J, Apostolopoulos V. Multiple Sclerosis: Immunopathology and Treatment Update. Brain Sci. 2017;7(7):78.

    Article  Google Scholar 

  4. David OJ, Kovarik JM, Schmouder RL. Clinical pharmacokinetics of fingolimod. Clin Pharmacokinet. 2012;51(1):15–28.

    Article  CAS  Google Scholar 

  5. Sartori A, Carle D, Freedman MS. Teriflunomide: a novel oral treatment for relapsing multiple sclerosis. Expert Opin Pharmacother. 2014;15(7):1019–27.

    Article  CAS  Google Scholar 

  6. Tovey MG, Lallemand C. Immunogenicity and other problems associated with the use of biopharmaceuticals. Ther Adv Drug Saf. 2011;2(3):113–28.

    Article  Google Scholar 

  7. Piali L, Froidevaux S, Hess P, Nayler O, Bolli MH, Schlosser E, et al. The selective sphingosine 1-phosphate receptor 1 agonist ponesimod protects against lymphocyte-mediated tissue inflammation. J Pharmacol Exp Ther. 2011;337(2):547–56.

    Article  CAS  Google Scholar 

  8. Bolli MH, Abele S, Binkert C, Bravo R, Buchmann S, Bur D, et al. 2-imino-thiazolidin-4-one derivatives as potent, orally active S1P1 receptor agonists. J Med Chem. 2010;53(10):4198–211.

    Article  CAS  Google Scholar 

  9. Chun J, Goetzl EJ, Hla T, Igarashi Y, Lynch KR, Moolenaar W, et al. International Union of Pharmacology XXXIV. Lysophospholipid receptor nomenclature. Pharmacol Rev. 2002;54(2):265–9.

    Article  CAS  Google Scholar 

  10. Cyster JG, Schwab SR. Sphingosine-1-phosphate and lymphocyte egress from lymphoid organs. Annu Rev Immunol. 2012;30:69–94.

    Article  CAS  Google Scholar 

  11. Matloubian M, Lo CG, Cinamon G, Lesneski MJ, Xu Y, Brinkmann V, et al. Lymphocyte egress from thymus and peripheral lymphoid organs is dependent on S1P receptor 1. Nature. 2004;427(6972):355–60.

    Article  CAS  Google Scholar 

  12. Olsson T, Boster A, Fernandez O, Freedman MS, Pozzilli C, Bach D, et al. Oral ponesimod in relapsing-remitting multiple sclerosis: a randomised phase II trial. J Neurol Neurosurg Psychiatry. 2014;85(11):1198–208.

    Article  Google Scholar 

  13. ClinicalTrials.gov. Oral Ponesimod Versus Teriflunomide in Relapsing MUltiple Sclerosis (OPTIMUM), ClinicalTrials.gov; 2015.

  14. Kappos L, Fox RJ, Burcklen M, et al. Ponesimod compared with teriflunomide in patients with relapsing multiple sclerosis in the active-comparator phase 3 OPTIMUM Study. JAMA Neurol. 2021. https://doi.org/10.1001/jamaneurol.2021.0405

    Article  PubMed  PubMed Central  Google Scholar 

  15. Juif PE, Kraehenbuehl S, Dingemanse J. Clinical pharmacology, efficacy, and safety aspects of sphingosine-1-phosphate receptor modulators. Expert Opin Drug Metab Toxicol. 2016;12(8):879–95.

    Article  CAS  Google Scholar 

  16. Boehler M, Juif PE, Hoch M, Dingemanse J. Absolute bioavailability of ponesimod, a selective S1P1 receptor modulator, in healthy male subjects. Eur J Drug Metab Pharmacokinet. 2017;42(1):129–34.

    Article  CAS  Google Scholar 

  17. Lott D, Lehr T, Dingemanse J, Krause A. Impact of demographics, organ impairment, disease, formulation, and food on the pharmacokinetics of the selective S1P1 receptor modulator ponesimod based on 13 clinical studies. Clin Pharmacokinet. 2017;56(4):395–408.

    Article  CAS  Google Scholar 

  18. Lott D, Krause A, Seemayer CA, Strasser DS, Dingemanse J, Lehr T. Modeling the effect of the selective S1P1 receptor modulator ponesimod on subsets of blood lymphocytes. Pharm Res. 2017;34(3):599–609.

    Article  CAS  Google Scholar 

  19. Brossard P, Derendorf H, Xu J, Maatouk H, Halabi A, Dingemanse J. Pharmacokinetics and pharmacodynamics of ponesimod, a selective S1P1 receptor modulator, in the first-in-human study. Br J Clin Pharmacol. 2013;76(6):888–96.

    Article  CAS  Google Scholar 

  20. Zhang L, Beal SL, Sheiner LB. Simultaneous vs. sequential analysis for population PK/PD data I: best-case performance. J Pharmacokinet Pharmacodyn. 2003;30(6):387–404.

    Article  Google Scholar 

  21. Mandema JW, Verotta D, Sheiner LB. Building population pharmacokinetic--pharmacodynamic models. I. Models for covariate effects. J Pharmacokinet Biopharm. 1992;20(5):511-28.

  22. Bergstrand M, Hooker AC, Wallin JE, Karlsson MO. Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models. AAPS J. 2011;13(2):143–51.

    Article  Google Scholar 

  23. Sheiner LB, Steimer JL. Pharmacokinetic/pharmacodynamic modeling in drug development. Annu Rev Pharmacol Toxicol. 2000;40:67–95.

    Article  CAS  Google Scholar 

  24. R Core Team, R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2017.

  25. Bauer RJ. ICON Development Solutions. NONMEM Users Guide: Introduction to NONMEM 7.2.0. 2011. Ellicott City, MD. https://nonmem.iconplc.com/nonmem720/guides/nm720.pdf. Accessed 20 Jan 2021.

  26. Simulo 8.0 version Expert. https://www.page-meeting.org/default.asp?abstract=9182. Accessed 20 Jan 2021.

  27. Mager DE, Lin SX, Blum RA, Lates CD, Jusko WJ. Dose equivalency evaluation of major corticosteroids: pharmacokinetics and cell trafficking and cortisol dynamics. J Clin Pharmacol. 2003;43(11):1216–27.

    Article  CAS  Google Scholar 

  28. Patel H, Egorin MJ, Remick SC, Mulkerin F, Takimoto CHM, Doroshow JH, et al. Comparison of Child-Pugh (CP) criteria and NCI organ dysfunction working group (NCI-ODWG) criteria for hepatic dysfunction (HD): Implications for chemotherapy dosing. J Clin Oncol. 2004;22(14 Suppl):6051.

    Article  Google Scholar 

  29. NCI. Protocol Template for Organ Dysfunction Studies. 2019. Available at: https://ctep.cancer.gov/protocoldevelopment/docs/ctep_organ_dysfunction_protocol_template.docx. Accessed 20 Jan 2021.

Download references

Acknowledgements

The authors thank the study participants, without whom this study would never have been accomplished, and all the investigators and their medical, nursing and laboratory staff for their participation in this study. The authors also thank Colleen Elliott for writing assistance and editorial support.

Author information

Author notes

  1. Quentin Leirens

    Present address: Pharmetheus AB, Uppsala, Sweden

Authors and Affiliations

  1. Janssen-Cilag Spain, Part of Janssen Pharmaceutical Companies of Johnson and Johnson, Madrid, Spain

    Belén Valenzuela & Juan-José Pérez-Ruixo

  2. SGS Exprimo, part of SGS Belgium NV, Mechelen, Belgium

    Quentin Leirens

  3. Janssen Research and Development, Beerse, Belgium

    Sivi Ouwerkerk-Mahadevan

  4. Janssen-Cilag Italy, part of the Janssen Pharmaceutical Companies of Johnson and Johnson, Cologno Monzese, Italy

    Italo Poggesi

Authors
  1. Belén Valenzuela
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Juan-José Pérez-Ruixo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Quentin Leirens
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sivi Ouwerkerk-Mahadevan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Italo Poggesi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Belén Valenzuela.

Ethics declarations

Funding

This study was supported by Actelion Pharmaceuticals Ltd, Part of Janssen Pharmaceutical Companies, Allschwil, Switzerland.

Conflicts of interest

Belén Valenzuela and Juan Jose Perez-Ruixo are employees of Janssen-Cilag Spain, part of the Janssen Pharmaceutical Company of Johnson & Johnson, and hold stock in Johnson & Johnson. Quentin Leirens was an employee of SGS Exprimo, part of SGS Belgium NV, at the time this analysis was conducted. Sivi Ouwerkerk-Mahadevan is an employee of Janssen NV, part of the Janssen Pharmaceutical Company of Johnson & Johnson, and holds stock in Johnson & Johnson. Italo Poggesi is an employee of Janssen-Cilag Italy, part of Janssen Pharmaceutical Company of Johnson & Johnson, and holds stock in Johnson & Johnson.

Ethics approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Protocols were reviewed and approved by an Institutional Review Board.

Consent to participate

Freely given, informed consent to participate was obtained for all human participants in this study.

Consent for publication

Not applicable.

Availability of data and material

The data sharing policy of the Janssen Pharmaceutical Companies of Johnson & Johnson is available at https://www.janssen.com/clinical–trials/transparency. As noted on that site, requests for access to the study data can be submitted through the Yale Open Data Access (YODA) Project site at http://yoda.yale.edu.

Code availability

Not applicable.

Author contributions

All authors participated in the original design of the studies and monitoring of data quality, and contributed to data interpretation, and development and review of this manuscript. They confirm that they have read the journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines. All authors meet the International Committee of Medical Journal Editors (ICMJE) criteria and all those who fulfilled those criteria are listed as authors. All authors had access to the study data, provided direction and comments on the manuscript, made the final decision on where to publish these data, and approved submission to this journal.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 477 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Valenzuela, B., Pérez-Ruixo, JJ., Leirens, Q. et al. Effect of Ponesimod Exposure on Total Lymphocyte Dynamics in Patients with Multiple Sclerosis. Clin Pharmacokinet 60, 1239–1250 (2021). https://doi.org/10.1007/s40262-021-01019-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40262-021-01019-9

Search

Navigation