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Pharmacokinetic Study of Tacrolimus in Cystic Fibrosis and Non-Cystic Fibrosis Lung Transplant Patients and Design of Bayesian Estimators Using Limited Sampling Strategies

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Abstract

Objectives

To: (i) test different pharmacokinetic models to fit full tacrolimus concentration-time profiles; (ii) estimate the tacrolimus pharmacokinetic characteristics in stable lung transplant patients with or without cystic fibrosis (CF); (iii) compare the pharmacokinetic parameters between these two patient groups; and (iv) design maximum a posteriori Bayesian estimators (MAP-BE) for pharmacokinetic forecasting in these patients using a limited sampling strategy.

Methods

Tacrolimus blood concentration-time profiles obtained on three occasions within a 5-day period in 22 adult lung transplant recipients (11 with CF and 11 without CF) were retrospectively studied. Three different one-compartment models with first-order elimination were tested to fit the data: one with first-order absorption, one convoluted with a gamma distribution to describe the absorption phase, and one convoluted with a double gamma distribution able to describe secondary concentration peaks. Finally, Bayesian estimation using the best model and a limited sampling strategy was tested in the two groups of patients for its ability to provide accurate estimates of the main tacrolimus pharmacokinetic parameters and exposure indices.

Results

The one-compartment model with first-order elimination convoluted with a double gamma distribution gave the best results in both CF and non-CF lung transplant recipients. The patients with CF required higher doses of tacrolimus than those without CF to achieve similar drug exposure, and population modelling had to be performed in CF and non-CF patients separately. Accurate Bayesian estimates of area under the blood concentration-time curve from 0 to 12 hours (AUC12), AUC from 0 to 4 hours, peak blood concentration (Cmax) and time to reach Cmax were obtained using three blood samples collected at 0, 1 and 3 hours in non-CF patients (correlation coefficient between observed and estimated AUC12, R2 = 0.96), and at 0, 1.5 and 4 hours in CF patients (R2 = 0.91).

Conclusion

A particular pharmacokinetic model was designed to fit the complex and highly variable tacrolimus blood concentration-time profiles. Moreover, MAP-BE allowing tacrolimus therapeutic drug monitoring based on AUC12 were developed.

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References

  1. Peters DH, Fitton A, Plosker GL, et al. Tacrolimus: a review of its pharmacology, and therapeutic potential in hepatic and renal transplantation. Drugs 1993; 46: 746–94

    Article  PubMed  CAS  Google Scholar 

  2. Scott LJ, McKeage K, Keam SJ, et al. Tacrolimus: a further update of its use in the management of organ transplantation. Drugs 2003; 63: 1247–97

    Article  PubMed  CAS  Google Scholar 

  3. Hertz MI, Taylor DO, Trulock EP, et al. The registry of the International Society for Heart and Lung Transplantation: 19th official report, 2002. J Heart Lung Transplant 2002; 21: 950–70

    Article  PubMed  Google Scholar 

  4. McCurry KR, Zaldonis DB, Keenan RJ, et al. Long term follow-up of a prospective randomised trial of tacrolimus versus cyclosporine in human lung transplantation [abstract]. Am J Transplant 2002; 2 Suppl. 3: S159

    Google Scholar 

  5. Zuckermann A, Reichenspurner H, Jacksch P, et al. Long term follow-up of a prospective randomized trial comparing tacrolimus versus cyclosporine in combination with MMF after lung transplantation. J Heart Lung Transplant 2003; 22 Suppl. 1: S76–7

    Article  Google Scholar 

  6. Treede H, Reichenspurner H, Meiser B, et al. Influence of four different immunosuppressive protocols on acute and chronic rejection (BOS) after lung transplantation: experience in 120 patients [abstract]. J Heart Lung Transplant 2001; 20: 176

    Article  PubMed  Google Scholar 

  7. Treede H, Klepetko W, Reichenspurner H, et al. Tacrolimus versus cyclosporine after lung transplantation: a prospective randomized two-center trial comparing two different immunosuppressive protocols. J Heart Lung Transplant 2001; 20: 511–7

    Article  PubMed  CAS  Google Scholar 

  8. Roman A, Bravo C, Monforte V, et al. Preliminary results of rescue therapy with tacrolimus and mycophenolate mofetil in lung transplanted patients with bronchiolitis obliterans. Transplant Proc 2002; 34: 146–7

    Article  PubMed  CAS  Google Scholar 

  9. Vitulo P, Oggionni T, Cascina A, et al. Efficacy of tacrolimus rescue therapy in refractory acute rejection after lung transplantation. J Heart Lung Transplant 2002; 21: 435–9

    Article  PubMed  Google Scholar 

  10. Fieguth H, Krueger S, Wiedenmann D, et al. Tacrolimus for treatment of bronchiolitis obliterans syndrome after unilateral and bilateral lung transplantation. Transplant Proc 2002; 34: 1884–9

    Article  PubMed  CAS  Google Scholar 

  11. Verderlen GM, Buyse B, Delcroix M, et al. Changing cyclosporine to tacrolimus after lung transplantation: reasons and outcome [abstract]. Eur Respir J 2000; 16 Suppl. 1: S510

    Google Scholar 

  12. Klepetko W, Sarahrudi K, Corris P, et al. Efficacy of conversion from cyclosporin A to tacrolimus in lung transplantation [abstract]. Am J Transplant 2002; 2 Suppl. 3: S159

    Google Scholar 

  13. Kahan BD, Keown P, Levy GA, et al. Therapeutic drug monitoring of immunosupressant drugs in clinical practice. Clin Ther 2002; 24: 330–50

    Article  PubMed  CAS  Google Scholar 

  14. Fukatsu S, Yano I, Igarashi T, et al. Population pharmacokinetics of tacrolimus in adult recipients receiving living-donor liver transplantation. Eur J Clin Pharmacol 2001; 57: 479–84

    Article  PubMed  CAS  Google Scholar 

  15. Staatz CE, Willis C, Taylor PJ, et al. Toward better outcomes with tacrolimus therapy: population pharmacokinetics and individualized dosage prediction in adult liver transplantation. Liver Transpl 2003; 9: 130–7

    Article  PubMed  Google Scholar 

  16. Staatz CE, Willis C, Taylor PJ, et al. Population pharmacokinetics of tacrolimus in adult kidney transplant recipients. Clin Pharmacol Ther 2002; 70: 660–9

    Article  Google Scholar 

  17. Zahir H. MacLachlan AJ, Nelson A, et al. Population pharmacokinetic estimation of tacrolimus apparent clearance in adult liver transplant recipients. Ther Drug Monit 2005; 27(4): 422–30

    Article  PubMed  CAS  Google Scholar 

  18. Antignac M, Hulot JS, Boleslawski E, et al. Population pharmacokinetics of tacrolimus in full liver transplant patients: modelling of the post-operative clearance. Eur J Clin Pharmacol 2005; 61(5-6): 409–16

    Article  PubMed  CAS  Google Scholar 

  19. Macchi-Andanson M, Charpiat Jelliffe RW, et al. Failure of traditional trough levels to predict tacrolimus concentrations. Ther Drug Monit 2001; 23: 129–33

    Article  PubMed  CAS  Google Scholar 

  20. Fukudo M, Yano I, Fukatsu S, et al. Forecasting of blood concentrations based on the Bayesian method in adult patients receiving living-donor liver transplantation. Clin Pharmacokinet 2003; 42: 1161–78

    Article  PubMed  CAS  Google Scholar 

  21. Willis C, Staatz CE, Tett SE. Bayesian forecasting and prediction of tacrolimus concentrations in pediatric and adult renal transplant patients. Ther Drug Monit 2003; 25: 158–66

    Article  PubMed  CAS  Google Scholar 

  22. Debord J, Risco E, Harel M, et al. Application of a gamma model of absorption to oral cyclosporin. Clin Pharmacokinet 2001; 40: 375–82

    Article  PubMed  CAS  Google Scholar 

  23. Léger F, Debord J, Le Meur Y, et al. Maximum a posteriori bayesian estimation of oral cyclosporine pharmacokinetics in stable renal transplant patients. Clin Pharmacokinet 2002; 41: 71–80

    Article  PubMed  Google Scholar 

  24. Monchaud C, Léger F, Rousseau A, et al. Bayesian forecasting of oral cyclosporine in cardiac transplant recipients. Eur J Clin Pharmacol 2003; 58: 813–20

    PubMed  CAS  Google Scholar 

  25. Rousseau A, Monchaud C, Debord J, et al. Bayesian forecasting of oral cyclosporin in stable lung transplant recipients with and without cystic fibrosis. Ther Drug Monit 2003; 25: 28–35

    Article  PubMed  CAS  Google Scholar 

  26. Akaike H. A new look at the statistical model identification. IEEE Trans Automat Control 1974; 19: 716–23

    Article  Google Scholar 

  27. D’argenio DZ. Optimal sampling times for pharmacokinetics experiments. J Pharmacokinet Biopharm 1981; 9: 739–5

    PubMed  Google Scholar 

  28. Staatz CE, Tett SE. Clinical phamacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation. Clin Pharmacokinet 2004; 43(10): 623–53

    Article  PubMed  CAS  Google Scholar 

  29. Saeki T, Ueda K, Tanigawara Y, et al. Human P-glycoprotein transports cyclosporin A and FK506. J Biol Chem 1993; 268: 6077–80

    PubMed  CAS  Google Scholar 

  30. Hashida T, Masuda S, Uemoto S, et al. Pharmacokinetic and prognostic significance of intestinal MDR1 expression in recipients of living-donor liver transplantation. Clin Pharmacol Ther 2001; 69(5): 308–16

    Article  PubMed  CAS  Google Scholar 

  31. Susanto M, Benet LZ. Can enhanced renal clearance of antibiotics in cystic fibrosis patients be explained by P-glycoprotein transport. Pharm Res 2002; 19(4): 457–62

    Article  PubMed  CAS  Google Scholar 

  32. Morton JM, Kear M, Williamson S, et al. Trough levels are inadequate for monitoring tacrolimus pharmacokinetics in lung transplantation. J Heart Lung Transplant 2002; 21: 143–4

    Article  Google Scholar 

Download references

Acknowledgements

The authors did not receive any funding for this study, and have no conflicts of interest that are directly relevant to the content of this study.

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Correspondence to Pierre Marquet.

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Saint-Marcoux, F., Knoop, C., Debord, J. et al. Pharmacokinetic Study of Tacrolimus in Cystic Fibrosis and Non-Cystic Fibrosis Lung Transplant Patients and Design of Bayesian Estimators Using Limited Sampling Strategies. Clin Pharmacokinet 44, 1317–1328 (2005). https://doi.org/10.2165/00003088-200544120-00010

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  • DOI: https://doi.org/10.2165/00003088-200544120-00010

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