Evaluation of the performance of a prior tacrolimus population pharmacokinetic kidney transplant model among adult allogeneic hematopoietic stem cell transplant patients

Jing Zhu, Olivia Campagne, Chad D Torrice, Gabrielle Flynn, Jordan A Miller, Tejendra Patel, Oscar Suzuki, Jonathan R Ptachcinski, Paul M Armistead, Tim Wiltshire, Donald E Mager, Daniel L Weiner, Daniel J Crona, Jing Zhu, Olivia Campagne, Chad D Torrice, Gabrielle Flynn, Jordan A Miller, Tejendra Patel, Oscar Suzuki, Jonathan R Ptachcinski, Paul M Armistead, Tim Wiltshire, Donald E Mager, Daniel L Weiner, Daniel J Crona

Abstract

Tacrolimus is a calcineurin inhibitor used to prevent acute graft versus host disease in adult patients receiving allogeneic hematopoietic stem cell transplantation (HCT). Previous population pharmacokinetic (PK) models have been developed in solid organ transplant, yet none exists for patients receiving HCT. The primary objectives of this study were to (1) use a previously published population PK model in adult patients who underwent kidney transplant and apply it to allogeneic HCT; (2) evaluate model-predicted tacrolimus steady-state trough concentrations and simulations in patients receiving HCT; and (3) evaluate covariates that affect tacrolimus PK in allogeneic HCT. A total of 252 adult patients receiving allogeneic HCT were included in the study. They received oral tacrolimus twice daily (0.03 mg/kg) starting 3 days prior to transplant. Data for these analyses included baseline clinical and demographic data, genotype data for single nucleotide polymorphisms in CYP3A4/5 and ABCB1, and the first tacrolimus steady-state trough concentration. A dosing simulation strategy based on observed trough concentrations (rather than model-based predictions) resulted in 12% more patients successfully achieving tacrolimus trough concentrations within the institutional target range (5-10 ng/ml). Stepwise covariate analyses identified HLA match and conditioning regimen (myeloablative vs. reduced intensity) as significant covariates. Ultimately, a previously published tacrolimus population PK model in kidney transplant provided a platform to help establish a model-based dose adjustment strategy in patients receiving allogenic HCT, and identified HCT-specific covariates to be considered for future prospective studies. Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? Tacrolimus is a cornerstone immunosuppressant used in patients who undergo organ transplantations. However, because of its narrow therapeutic index and wide interpatient pharmacokinetic (PK) variability, optimizing its dose is crucial to maximize efficacy and minimize tacrolimus-induced toxicities. Prior to this study, no tacrolimus population PK models have been developed for adult patients receiving allogeneic hematopoietic stem cell transplantation (HCT). Therefore, research effort was warranted to develop a population PK model that begins to propose more precision tacrolimus dosing and begins to address both a clinical and scientific gap in this patient population. WHAT QUESTION DID THIS STUDY ADDRESS? The study addressed whether there is value in utilizing the observed tacrolimus steady-state trough concentrations from patients receiving allogeneic HCT within the context of a pre-existing population PK model developed for kidney transplant. The study also addressed whether there are clinically relevant covariates specific to adult patients receiving allogeneic HCT. WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE? Inclusion of a single steady-state tacrolimus trough concentration is beneficial to model predictions. The dosing simulation strategy based on observed tacrolimus concentration, rather than the model-predicted concentration, resulted in more patients achieving the target range at first steady-state collection. Future studies should evaluate HLA matching and myeloablative conditioning versus reduced intensity conditioning regimens as covariates. These data and model-informed dose adjustments should be included in future prospective studies. This research could also serve as a template as to how to assess the utility of prior information for other disease settings. HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE? The M2 model fitting method and D2 dosing simulation method can be applied to other clinical pharmacology studies where only a single steady-state trough concentration is available per patient in the presence of a previously published population PK model.

Trial registration: ClinicalTrials.gov NCT04645667.

Conflict of interest statement

All authors declared no competing interests for this work.

© 2021 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics.

Figures

Figure 1
Figure 1
Dose adjustment schematic. Model‐based dose adjustment was performed based on this schematic to derive the final doses to be applied in the M2 model.
Figure 2
Figure 2
Steady‐state tacrolimus trough by CYP3A5 metabolizer phenotype. Tacrolimus trough concentration at steady‐state for CYP3A5 metabolizer phenotype. Associations between steady‐state tacrolimus trough concentrations measured on the day of allogeneic HCT (day 0) were evaluated. The black lines denote the median tacrolimus concentration. Abbreviations: CYP3A5, cytochrome P450 isoform 5; EM, extensive metabolizers; HCT, hematopoietic stem cell transplantation; IM, intermediate metabolizers; PM, poor metabolizers.
Figure 3
Figure 3
Modeling methods comparisons. Model‐predicted tacrolimus steady‐state trough concentration post‐dose adjustments were compared across the observed data, the M1 modeling method, and M2 modeling method. Vertical bars depict the number of patients who were subtherapeutic ( 10 ng/ml), respectively.
Figure 4
Figure 4
Dose adjustment method comparisons. Model‐predicted tacrolimus steady‐state trough concentration post‐dose adjustments were compared across the observed data, D1 dose adjustment method, and D2 dose adjustment method. Vertical bars depict the number of patients who were subtherapeutic ( 10 ng/ml), respectively.

References

    1. Przepiorka D, Devine SM, Fay JW, Uberti JP, Wingard JR. Practical considerations in the use of tacrolimus for allogeneic marrow transplantation. Bone Marrow Transplant. 1999;24(10):1053‐1056.
    1. Azzi JR, Sayegh MH, Mallat SG. Calcineurin inhibitors: 40 years later. can’t live without. J Immunol. 2013;191(12):5785‐5791.
    1. Kelly PA, Burckart GJ, Venkataramanan R. Tacrolimus: a new immunosuppressive agent. Am J Health Syst Pharm. 1995;52(14):1521‐1535.
    1. Astellas Pharma US . Prograf (tacrolimus) [package insert]. 2012.
    1. 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.
    1. Kuypers D, Claes K, Evenepoel P, Maes B, Vanrenterghem Y. Clinical efficacy and toxicity profile of tacrolimus and mycophenolic acid in relation to combined long‐term pharmacokinetics in de novo renal allograft recipients. Clin Pharmacol Ther. 2004;75(5):434‐447.
    1. Leino AD, King EC, Jiang W, et al. Assessment of tacrolimus intrapatient variability in stable adherent transplant recipients: establishing baseline values. Am J Transplant. 2019;19(5):1410‐1420.
    1. Staatz CE, Tett SE. Clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation. Clin Pharmacokinet. 2004;43(10):623‐653.
    1. Zhu J, Patel T, Miller JA et al. Influence of germline genetics on tacrolimus pharmacokinetics and pharmacodynamics in allogeneic hematopoietic stem cell transplant patients. Int J Mol Sci. 2020;21(3):858.
    1. Hamadeh IS, Zhang Q, Steuerwald N et al. Effect of CYP3A4, CYP3A5, and ABCB1 polymorphisms on intravenous tacrolimus exposure and adverse events in adult allogeneic stem cell transplant patients. Biol Blood Marrow Transplant. 2019;25(4):656‐663.
    1. Khaled SK, Palmer JM, Herzog J et al. Influence of absorption, distribution, metabolism, and excretion genomic variants on tacrolimus/sirolimus blood levels and graft‐versus‐host disease after allogeneic hematopoietic cell transplantation. Biol Blood Marrow Transplant. 2016;22(2):268‐276.
    1. Birdwell KA, Decker B, Barbarino JM et al. Clinical pharmacogenetics implementation consortium (CPIC) guidelines for CYP3A5 genotype and tacrolimus dosing. Clin Pharmacol Ther. 2015;98(1):19‐24.
    1. Lunenburg CATC, van der Wouden CH, Nijenhuis M et al. Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene–drug interaction of DPYD and fluoropyrimidines. Eur J Hum Genet. 2020;28(4):508‐517.
    1. Woillard J‐B, Mourad M, Neely M, et al. Tacrolimus updated guidelines through popPK modeling: how to benefit more from CYP3A pre‐emptive genotyping prior to kidney transplantation. Front Pharmacol. 2017;8:358.
    1. Dai Y, Hebert MF, Isoherranen N et al. Effect of cyp3a5 polymorphism on tacrolimus metabolic clearance in vitro. Drug Metab Dispos. 2006;34(5):836‐847.
    1. Hesselink DA, Bouamar R, Elens L, van Schaik RHN, van Gelder T. The role of pharmacogenetics in the disposition of and response to tacrolimus in solid organ transplantation. Clin Pharmacokinet. 2014;3(2):123‐139.
    1. Lamba J, Hebert JM, Schuetz EG, Klein TE, Altman RB. PharmGKB summary. Pharmacogenet Genomics. 2012;22(7):555‐558.
    1. Staatz CE, Goodman LK, Tett SE. Effect of CYP3A and ABCB1 single nucleotide polymorphisms on the pharmacokinetics and pharmacodynamics of calcineurin inhibitors: part II. Clin Pharmacokinet. 2010;49(4):207‐221.
    1. Zhao W, Elie V, Roussey G et al. Population pharmacokinetics and pharmacogenetics of tacrolimus in de novo pediatric kidney transplant recipients. Clin Pharmacol Ther. 2009;86(6):609‐618.
    1. Zhao C‐Y, Jiao Z, Mao J‐J, Qiu X‐Y. External evaluation of published population pharmacokinetic models of tacrolimus in adult renal transplant recipients. Br J Clin Pharmacol. 2016;81(5):891‐907.
    1. Moes DJAR, van der Bent SAS, Swen JJ et al. Population pharmacokinetics and pharmacogenetics of once daily tacrolimus formulation in stable liver transplant recipients. Eur J Clin Pharmacol. 2016;72(2):163‐174.
    1. Campagne O, Mager DE, Brazeau D, Venuto RC, Tornatore KM. Tacrolimus population pharmacokinetics and multiple CYP3A5 genotypes in black and white renal transplant recipients. J Clin Pharmacol. 2018;58(9):1184‐1195.
    1. Zhu L, Wang H, Sun X et al. The population pharmacokinetic models of tacrolimus in Chinese adult liver transplantation patients. J Pharm (Cairo). 2014;2014:713650.
    1. Han Y, Zhou H, Cai J et al. Prediction of tacrolimus dosage in the early period after heart transplantation: a population pharmacokinetic approach. Pharmacogenomics. 2019;20(1):21‐35.
    1. Fredj NB, Woillard JB, Debord J et al. Modeling of tacrolimus exposure in kidney transplant according to posttransplant time based on routine trough concentration data. Exp Clin Transplant. 2016;14(4):394‐400.
    1. Zhang Y, Yang J, Zhu LQ, Wang N. Effects on pharmacokinetics of tacrolimus in liver transplant patients. SM J Pharmac Ther. 2016;2(1):20‐23.
    1. Chinen J, Buckley RH. Transplantation immunology: Solid organ and bone marrow. J Allergy Clin Immunol. 2010;125(2 suppl. 2):1‐26.
    1. Dickinson AM, Norden J, Li S et al. Graft‐versus‐leukemia effect following hematopoietic stem cell transplantation for leukemia. Front Immunol. 2017;8:496.
    1. Mori T, Kato J, Shimizu T, et al. Effect of early posttransplantation tacrolimus concentration on the development of acute graft‐versus‐host disease after allogeneic hematopoietic stem cell transplantation from unrelated donors. Biol Blood Marrow Transpl. 2012;18:229‐234.
    1. Ganetsky A, Shah A, Miano TA, et al. Higher tacrolimus concentrations early after transplant reduce the risk of acute GvHD in reduced‐intensity allogeneic stem cell transplantation. Bone Marrow Transplant. 2016;51(4):568‐572.
    1. Suzuki O, Dong OM, Howard RM, Wiltshire T. Characterizing the pharmacogenome using molecular inversion probes for targeted next‐generation sequencing. Pharmacogenomics. 2019;20(14):1005‐1020.
    1. Brill MJE, Diepstraten J, van Rongen A et al. Impact of obesity on drug metabolism and elimination in adults and children. Clin Pharmacokinet. 2012;51:277‐304.
    1. Hanley M, Abernathy D, Greenblatt D. Effect of obesity on the pharmacokinetics of drugs in humans. Clin Pharmacokinet. 2010;49:71‐87.
    1. Barras M, Legg A. Drug dosing in obese adults. Aust Prescr. 2017;40(5):189‐193.
    1. Patel P, Patel H, Panchal S, Mehta T. Formulation strategies for drug delivery of tacrolimus: an overview. Int J Pharm Investig. 2012;2(4):169‐175.
    1. Antignac M, Barrou B, Farinotti R, Lechat P, Urien S. Population pharmacokinetics and bioavailability of tacrolimus in kidney transplant patients. Br J Clin Pharmacol. 2007;64(6):750‐757.
    1. Sikma MA, Van Maarseveen EM, Van De Graaf EA, et al. Pharmacokinetics and toxicity of tacrolimus early after heart and lung transplantation. Am J Transplant. 2015;15(9):2301‐2313.
    1. Johansson JE, Brune M, Ekman T. The gut mucosa barrier is preserved during allogeneic, haemopoietic stem cell transplantation with reduced intensity conditioning. Bone Marrow Transplant. 2001;28(8):737‐742.
    1. Kanda J. Effect of HLA mismatch on acute graft‐versus‐host disease. Int J Hematol. 2013;98(3):300‐308.
    1. Petersdorf EW. Role of major histocompatibility complex variation in graft‐versus‐host disease after hematopoietic cell transplantation. F1000Res. 2017;6(617):1‐12.
    1. Hagen PA, Adams W, Smith S, Tsai S, Stiff P. Low mean post‐transplantation tacrolimus levels in weeks 2–3 correlate with acute graft‐versus‐host disease in allogeneic hematopoietic stem cell transplantation from related and unrelated donors. Bone Marrow Transplant. 2019;54(1):155‐158.
    1. Mao JJ, Jiao Z, Yun HY, et al. External evaluation of population pharmacokinetic models for ciclosporin in adult renal transplant recipients. Br J Clin Pharmacol. 2018;84(1):153‐171.
    1. Tasa T, Kalamees R, Vilo J, Lutsar I, Metsvaht T. External evaluation of population pharmacokinetic models for vancomycin in neonates [published online ahead of print October 2018]. bioRxiv. 10.1101/458125.
    1. Elens L, Hesselink DA, Bouamar R et al. Impact of POR*28 on the pharmacokinetics of tacrolimus and cyclosporine A in renal transplant patients. Ther Drug Monit. 2014;36(1):71‐79.
    1. Kurzawski M, Malinowski D, Dziewanowski K, Droździka M. Impact of PPARA and POR polymorphisms on tacrolimus pharmacokinetics and new‐onset diabetes in kidney transplant recipients. Pharmacogenet Genomics. 2014;24(8):397‐400.
    1. Dorr CR, Wu B, Remmel RP, et al. Phenotype sampling and next generation sequencing. Pharmacogenomics J. 2019;19(4):375‐389.
    1. Marfo K, Altshuler J, Lu A. Tacrolimus pharmacokinetic and pharmacogenomic differences between adults and pediatric solid organ transplant recipients. Pharmaceutics. 2010;2(3):291‐299.

Source: PubMed

3
Abonner