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Therapeutic Drug Monitoring Strategies for Envarsus in De Novo Kidney Transplant Patients Using Population Modelling and Simulations

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Abstract

Introduction

Tacrolimus, the cornerstone of transplantation immunosuppression, is a narrow therapeutic index drug with a low and highly variable bioavailability. Therapeutic drug monitoring based on trough level assessment is mandatory in order to target a personalised exposure and avoid both rejection and toxicity. Population pharmacokinetic (POPPK) models might be a useful tool for improving early attainment of target range by guiding initial doses until steady state is reached and trough levels can be reliably used as surrogate marker of exposure. Here we present the first POPPK for predicting the initial doses of the once-daily prolonged release tacrolimus Envarsus (LCPT) in adult kidney recipients.

Methods

The model was developed exploiting the data from a recent pharmacokinetic randomised clinical study, in which 69 de novo kidney recipients, 33 of whom treated with LCPT, underwent an intensive blood sampling strategy for tacrolimus including four complete pharmacokinetic profiles.

Results

The complex and prolonged absorption of LCPT is well described by the three-phase model that incorporates body weight and CYP3A5 genotype as significant covariates accounting for a great proportion of the inter-patient variability: in particular, CYP3A5*1/*3 expressors had a 66% higher LCPT clearance. We have then generated by simulation a personalised dosing strategy based on the model that could improve the early attainment of therapeutic trough levels by almost doubling the proportion of patients within target range (69.3% compared to 36.1% with the standard body weight-based approach) on post-transplantation day 4 and significantly reduce the proportion of overexposed patients at risk of toxicity.

Conclusions

A POPPK model was successfully developed for LCPT in de novo kidney recipients. The model could guide a personalised dosing strategy early after transplantation. For the model to be translated into clinical practice, its beneficial impact of earlier attainment of therapeutic trough levels should be demonstrated on hard clinical outcomes in further studies.

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References

  1. Hart A, Smith JM, Skeans MA, et al. OPTN/SRTR 2018 annual data report: kidney. Am J Transplant. 2020;20(s1):20–130. https://doi.org/10.1111/ajt.15672.

    Article  PubMed  Google Scholar 

  2. Mayer TU, Marx A. Five molecules we would take to a remote Island. Chem Biol. 2010;17(6):556–60. https://doi.org/10.1016/j.chembiol.2010.06.002.

    Article  CAS  PubMed  Google Scholar 

  3. Brunet M, Van Gelder T, Åsberg A, et al. Therapeutic drug monitoring of tacrolimus-personalized therapy: second consensus report. Ther Drug Monit. 2019;41(3):261–307. https://doi.org/10.1097/FTD.0000000000000640.

    Article  CAS  PubMed  Google Scholar 

  4. Staatz CE, Tett SE. Clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation. Clin Pharmacokinet. 2004;43(10):623–53. https://doi.org/10.2165/00003088-200443100-00001.

    Article  CAS  PubMed  Google Scholar 

  5. Piotti G, Cremaschi E, Maggiore U. Once-daily prolonged-release tacrolimus formulations for kidney transplantation: what the nephrologist needs to know. J Nephrol. 2017;30(1):53–61. https://doi.org/10.1007/s40620-016-0316-3.

    Article  CAS  PubMed  Google Scholar 

  6. Chapman JR. The KDIGO clinical practice guidelines for the care of kidney transplant recipients. Transplantation. 2010;89(6):644–5. https://doi.org/10.1097/TP.0b013e3181d62f1b.

    Article  PubMed  Google Scholar 

  7. Staatz CE, Tett SE. Clinical pharmacokinetics of once-daily tacrolimus in solid-organ transplant patients. Clin Pharmacokinet. 2015;54(10):993–1025. https://doi.org/10.1007/s40262-015-0282-2.

    Article  CAS  PubMed  Google Scholar 

  8. Staatz C, Taylor P, Tett S. Low tacrolimus concentrations and increased risk of early acute rejection in adult renal transplantation. Nephrol Dial Transplant. 2001;16(9):1905–9. https://doi.org/10.1093/ndt/16.9.1905.

    Article  CAS  PubMed  Google Scholar 

  9. Borobia AM, Romero I, Jimenez C, et al. Trough tacrolimus concentrations in the first week after kidney transplantation are related to acute rejection. Ther Drug Monit. 2009;31(4):436–42. https://doi.org/10.1097/FTD.0b013e3181a8f02a.

    Article  CAS  PubMed  Google Scholar 

  10. Richards KR, Hager D, Muth B, Astor BC, Kaufman D, Djamali A. Tacrolimus trough level at discharge predicts acute rejection in moderately sensitized renal transplant recipients. Transplantation. 2014;97(10):986–91. https://doi.org/10.1097/TP.0000000000000149.

    Article  CAS  PubMed  Google Scholar 

  11. Thervet E, Loriot MA, Barbier S, et al. Optimization of initial tacrolimus dose using pharmacogenetic testing. Clin Pharmacol Ther. 2010;87(6):721–6. https://doi.org/10.1038/clpt.2010.17.

    Article  CAS  PubMed  Google Scholar 

  12. Shuker N, Bouamar R, van Schaik RHN. A randomized controlled trial comparing the efficacy of Cyp3a5 genotype-based with body- weight-based tacrolimus dosing after living donor kidney transplantation. Am J Transplant. 2016;16:2085–96. https://doi.org/10.1111/ajt.13691.

    Article  CAS  PubMed  Google Scholar 

  13. Brooks E, Tett SE, Isbel NM, Staatz CE. Population pharmacokinetic modelling and bayesian estimation of tacrolimus exposure: is this clinically useful for dosage prediction yet? Clin Pharmacokinet. 2016;55(11):1295–335. https://doi.org/10.1007/s40262-016-0396-1.

    Article  CAS  PubMed  Google Scholar 

  14. Kirubakaran R, Stocker SL, Hennig S, Day RO, Carland JE. Population pharmacokinetic models of tacrolimus in adult transplant recipients: a systematic review. Springer International; 2020. https://doi.org/10.1007/s40262-020-00922-x.

    Book  Google Scholar 

  15. Holm P. Meltdose Technology by the US Patent and Trademark Office. US7217431. 2007.

  16. Nigro V, Glicklich A, Weinberg J. Improved bioavailability of MELTDOSE once-daily formulation of tacrolimus (LCP-Tacro) with controlled agglomeration allows for consistent absorption over 24 h: a scintigraphic and pharmacokinetic evaluation. Am J Transplants. 2013;13(5):B1034.

    Google Scholar 

  17. Grinyó JM, Petruzzelli S. Once-daily LCP-Tacro MeltDose tacrolimus for the prophylaxis of organ rejection in kidney and liver transplantations. Expert Rev Clin Immunol. 2014;10(12):1567–79. https://doi.org/10.1586/1744666X.2014.983903.

    Article  CAS  PubMed  Google Scholar 

  18. Gaber AO, Alloway RR, Bodziak K, Kaplan B, Bunnapradist S. Conversion from twice-daily tacrolimus capsules to once-daily extended-release tacrolimus (LCPT): a phase 2 trial of stable renal transplant recipients. Transplantation. 2013;96(2):191–7. https://doi.org/10.1097/TP.0b013e3182962cc1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Alloway RR. Conversion from twice daily tacrolimus capsules to once daily extended-release tacrolimus (LCP-Tacro): phase 2 trial of stable liver transplant recipients. Liver Transplant. 2014;20:564–75. https://doi.org/10.1002/lt.23844.

    Article  Google Scholar 

  20. Tremblay S, Nigro V, Weinberg J, Woodle ES, Alloway RR. A steady-state head-to-head pharmacokinetic comparison of All FK-506 (Tacrolimus) formulations (ASTCOFF): an open-label, prospective, randomized, two-arm. Three-period crossover study. Am J Transplant. 2017;17(2):432–42. https://doi.org/10.1111/ajt.13935.

    Article  CAS  PubMed  Google Scholar 

  21. Trofe-Clark J, Brennan DC, West-Thielke P, et al. Results of ASERTAA, a randomized prospective crossover pharmacogenetic study of immediate-release versus extended-release tacrolimus in African American kidney transplant recipients. Am J Kidney Dis. 2018;71(3):315–26. https://doi.org/10.1053/j.ajkd.2017.07.018.

    Article  CAS  PubMed  Google Scholar 

  22. Kamar N, Cassuto E, Piotti G, et al. Pharmacokinetics of prolonged-release once-daily formulations of tacrolimus in de novo kidney transplant recipients: a randomized, parallel-group, open-label. Multicenter study. Adv Ther. 2019;36(2):462–77. https://doi.org/10.1007/s12325-018-0855-1.

    Article  CAS  PubMed  Google Scholar 

  23. Envarsus Summary of Product Characteristics. Annex I. https://doi.org/10.2307/j.ctvdf0dxq.12. https://www.ema.europa.eu/en/documents/product-information/abecma-epar-product-information_en.pdf. Accessed 14 May 2021.

  24. Envarsus Product Information. https://www.accessdata.fda.gov/drugsatfda_docs/label/2018/206406s007lbl.pdf. Accessed 14 May 21.

  25. Woillard JB, Debord J, Monchaud C, Saint-Marcoux F, Marquet P. Population pharmacokinetics and bayesian estimators for refined dose adjustment of a new tacrolimus formulation in kidney and liver transplant patients. Clin Pharmacokinet. 2017;56(12):1491–8. https://doi.org/10.1007/s40262-017-0533-5.

    Article  CAS  PubMed  Google Scholar 

  26. 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. https://doi.org/10.1208/s12248-011-9255-z.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Bauer RJ, Boeckmann AJ. III. NONMEM Installation NM7.3. 2013; (November).

  28. Lindbom L, Ribbing J, Jonsson EN. Perl-speaks-NONMEM (PsN)—a perl module for NONMEM related programming. Comput Methods Prog Biomed. 2004;75(2):85–94. https://doi.org/10.1016/j.cmpb.2003.11.003.

    Article  Google Scholar 

  29. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna AU https://www.Rorg/. The R Project for Statistical Computing. http://www.R-Project.Org/. 2017.

  30. Bouamar R, Shuker N, Hesselink DA, et al. Tacrolimus predose concentrations do not predict the risk of acute rejection after renal transplantation: a pooled analysis from three randomized-controlled clinical trials. Am J Transplant. 2013;13(5):1253–61. https://doi.org/10.1111/ajt.12191.

    Article  CAS  PubMed  Google Scholar 

  31. Størset E, Åsberg A, Skauby M, et al. Improved tacrolimus target concentration achievement using computerized dosing in renal transplant recipients-a prospective. Randomized Study. Transplantation. 2015;99(10):2158–66. https://doi.org/10.1097/TP.0000000000000708.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Kuypers DRJ, de Jonge H, Naesens M, Vanrenterghem Y. A prospective, open-label, observational clinical cohort study of the association between delayed renal allograft function, tacrolimus exposure, and CYP3A5 genotype in adult recipients. Clin Ther. 2010;32(12):2012–23. https://doi.org/10.1016/j.clinthera.2010.11.010.

    Article  CAS  PubMed  Google Scholar 

  33. Sikma MA, Hunault CC, van de Graaf EA, et al. High tacrolimus blood concentrations early after lung transplantation and the risk of kidney injury. Eur J Clin Pharmacol. 2017;73(5):573–80. https://doi.org/10.1007/s00228-017-2204-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Lemaitre F, Lorcy N, Tron C, et al. Tacrolimus overexposure in kidney transplant recipients during the first post-operative week: caution is required in older patients. Fundam Clin Pharmacol. 2019;33(3):347–54. https://doi.org/10.1111/fcp.12432.

    Article  CAS  PubMed  Google Scholar 

  35. Vanhove T, Annaert P, Kuypers DRJ. Clinical determinants of calcineurin inhibitor disposition: a mechanistic review. Drug Metab Rev. 2016;48(1):88–112. https://doi.org/10.3109/03602532.2016.1151037.

    Article  CAS  PubMed  Google Scholar 

  36. Nanga TM, Doan TTP, Marquet P, Musuamba FT. Toward a robust tool for pharmacokinetic-based personalization of treatment with tacrolimus in solid organ transplantation: a model-based meta-analysis approach. Br J Clin Pharmacol. 2019;85(12):2793–823. https://doi.org/10.1111/bcp.14110.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Dirks NL, Huth B, Yates CR, Meibohm B. Pharmacokinetics of immunosuppressants: a perspective on ethnic differences. Int J Clin Pharmacol Ther. 2004;42(12):701–18. https://doi.org/10.5414/CPP42701.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

Funding

This study was funded by Chiesi Farmaceutici S.p.A., Parma, Italy. Chiesi Farmaceutici S.p.A. is also funding the Rapid Service Fee.

Authorship

All named authors meet the International Committee of Medical Journal Editors criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.

Author Contributions

Mirco Govoni and Giovanni Piotti conceived the project. Emilie Henin performed the research with the inputs of all the authors. All authors contributed to the data analysis. Emilie Henin and Giovanni Piotti wrote the manuscript. All authors revised the manuscript.

Disclosure

Mirco Govoni, Massimo Cella and Giovanni Piotti are all employees of Chiesi Farmaceutici S.p.A.

Emilie Henin and Christian Laveille received a consultancy assignment from Chiesi Farmaceutici S.p.A.

Compliance with Ethics Guidelines

All procedures performed in the study were according to the clinical study protocol, the International Council for Harmonization Good Clinical Practice guidelines, local guidelines and the Declaration of Helsinki (1964 and amendments). The independent ethics committee for the study was the Committee for the Protection of Persons South Mediterranean V, CHU de Nice-Hôpital De Cimiez. Informed consent was obtained from all individual participants included in the study. A specific patient information sheet–informed consent form for genotyping tests was also obtained.

Data Availability

The data sets analysed and/or generated during the current study are available from the corresponding author on reasonable request.

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Correspondence to Giovanni Piotti.

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Henin, E., Govoni, M., Cella, M. et al. Therapeutic Drug Monitoring Strategies for Envarsus in De Novo Kidney Transplant Patients Using Population Modelling and Simulations. Adv Ther 38, 5317–5332 (2021). https://doi.org/10.1007/s12325-021-01905-5

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  • DOI: https://doi.org/10.1007/s12325-021-01905-5

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