Clinical Pharmacokinetics

, Volume 50, Issue 12, pp 759–772 | Cite as

Maximum A Posteriori Bayesian Estimation of Mycophenolic Acid Area Under the Concentration-Time Curve: Is This Clinically Useful for Dosage Prediction Yet?

  • Christine E. Staatz
  • Susan E. Tett
Review Article


This review seeks to summarize the available data about Bayesian estimation of area under the plasma concentration-time curve (AUC) and dosage prediction for mycophenolic acid (MPA) and evaluate whether sufficient evidence is available for routine use of Bayesian dosage prediction in clinical practice. A literature search identified 14 studies that assessed the predictive performance of maximum a posteriori Bayesian estimation of MPA AUC and one report that retrospectively evaluated how closely dosage recommendations based on Bayesian forecasting achieved targeted MPA exposure. Studies to date have mostly been undertaken in renal transplant recipients, with limited investigation in patients treated with MPA for autoimmune disease or haematopoietic stem cell transplantation. All of these studies have involved use of the mycophenolate mofetil (MMF) formulation of MPA, rather than the enteric-coated mycophenolate sodium (EC-MPS) formulation. Bias associated with estimation of MPA AUC using Bayesian forecasting was generally less than 10%. However some difficulties with imprecision was evident, with values ranging from 4% to 34% (based on estimation involving two or more concentration measurements). Evaluation of whether MPA dosing decisions based on Bayesian forecasting (by the free website service achieved target drug exposure has only been undertaken once. When MMF dosage recommendations were applied by clinicians, a higher proportion (72–80%) of subsequent estimated MPA AUC values were within the 30–60mg · h/L target range, compared with when dosage recommendations were not followed (only 39–57% within target range). Such findings provide evidence that Bayesian dosage prediction is clinically useful for achieving target MPA AUC. This study, however, was retrospective and focussed only on adult renal transplant recipients. Furthermore, in this study, Bayesian-generated AUC estimations and dosage predictions were not compared with a later full measured AUC but rather with a further AUC estimate based on a second Bayesian analysis. This study also provided some evidence that a useful monitoring schedule for MPA AUC following adult renal transplant would be every 2 weeks during the first month post-transplant, every 1–3 months between months 1 and 12, and each year thereafter. It will be interesting to see further validations in different patient groups using the free website service. In summary, the predictive performance of Bayesian estimation of MPA, comparing estimated with measured AUC values, has been reported in several studies. However, the next step of predicting dosages based on these Bayesian-estimated AUCs, and prospectively determining how closely these predicted dosages give drug exposure matching targeted AUCs, remains largely unaddressed. Further prospective studies are required, particularly in non-renal transplant patients and with the EC-MPS formulation. Other important questions remain to be answered, such as: do Bayesian forecasting methods devised to date use the best population pharmacokinetic models or most accurate algorithms; are the methods simple to use for routine clinical practice; do the algorithms actually improve dosage estimations beyond empirical recommendations in all groups that receive MPA therapy; and, importantly, do the dosage predictions, when followed, improve patient health outcomes?


Population Pharmacokinetic Model Bayesian Forecast Dosage Prediction Adult Renal Transplant Recipient Adult Kidney Transplant Recipient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors acknowledge financial support from National Health and Medical Research Council Project Grant ♯511109. C. Staatz is currently supported by a Lions Medical Research Fellowship. The authors thank Drs F. Saint-Marcoux and P. Marquet for sharing information about the Limoges University Hospital website service ( for Bayesian forecasting.

S. Tett has no conflict of interest to declare; C. Staatz has been a member of a project team for a Cellcept® Project Research Grant 2009.


  1. 1.
    Staatz CE, Tett SE. Clinical pharmacokinetics and pharmacodynamics of mycophenolate in solid organ transplant recipients. Clin Pharmacokinet 2007; 46(1): 13–58PubMedCrossRefGoogle Scholar
  2. 2.
    van Hest R, Mathot R, Vulto A, et al. Predicting the usefulness of therapeutic drug monitoring of mycophenolic acid: a computer simulation. Ther Drug Monit 2005 Apr; 27(2): 163–7PubMedCrossRefGoogle Scholar
  3. 3.
    Gaston RS, Kaplan B, Shah T, et al. Fixed- or controlled-dose mycophenolate mofetil with standard- or reduced-dose calcineurin inhibitors: the Opticept trial. Am J Transplant 2009 Jul; 9(7): 1607–19PubMedCrossRefGoogle Scholar
  4. 4.
    Le Meur Y, Buchler M, Thierry A, et al. Individualized mycophenolate mofetil dosing based on drug exposure significantly improves patient outcomes after renal transplantation. Am J Transplant 2007 Nov; 7(11): 2496–503PubMedCrossRefGoogle Scholar
  5. 5.
    Kuypers DR, Le Meur Y, Cantarovich M, et al. Consensus report on therapeutic drug monitoring of mycophenolic acid in solid organ transplantation. Clin J Am Soc Nephrol 2010 Feb; 5(2): 341–58PubMedCrossRefGoogle Scholar
  6. 6.
    Barraclough KA, Staatz CE, Isbel NM, et al. Therapeutic monitoring of mycophenolate in transplantation: is it justified? Curr Drug Metab 2009 Feb; 10(2): 179–87PubMedCrossRefGoogle Scholar
  7. 7.
    Pelletier RP, Akin B, Henry ML, et al. The impact of mycophenolate mofetil dosing patterns on clinical outcome after renal transplantation. Clin Transplant 2003 Jun; 17(3): 200–5PubMedCrossRefGoogle Scholar
  8. 8.
    Knoll GA, MacDonald I, Khan A, et al. Mycophenolate mofetil dose reduction and the risk of acute rejection after renal transplantation. J Am Soc Nephrol 2003 Sep; 14(9): 2381–6PubMedCrossRefGoogle Scholar
  9. 9.
    Knight SR, Morris PJ. Does the evidence support the use of mycophenolate mofetil therapeutic drug monitoring in clinical practice? A systematic review. Transplantation 2008 Jun 27; 85(12): 1675–85PubMedCrossRefGoogle Scholar
  10. 10.
    Kiberd BA, Lawen J, Fraser AD, et al. Early adequate mycophenolic acid exposure is associated with less rejection in kidney transplantation. Am J Transplant 2004 Jul; 4(7): 1079–83PubMedCrossRefGoogle Scholar
  11. 11.
    Zuk DM, Pearson GJ. Monitoring of mycophenolate mofetil in orthotopic heart transplant recipients: a systematic review. Transplant Rev (Orlando) 2009 Jul; 23(3): 171–7CrossRefGoogle Scholar
  12. 12.
    Sagcal-Gironella AC, Fukuda T, Wiers K, et al. Pharmacokinetics and pharmacodynamics of mycophenolic acid and their relation to response to therapy of childhood-onset systemic lupus erythematosus. Semin Arthritis Rheum 2011 Feb; 40(4): 307–13PubMedCrossRefGoogle Scholar
  13. 13.
    Djabarouti S, Breilh D, Duffau P, et al. Steady-state mycophenolate mofetil pharmacokinetic parameters enable prediction of systemic lupus erythematosus clinical flares: an observational cohort study [published erratum appears in Arthritis Res Ther 2011; 13 (2): 401]. Arthritis Res Ther 2010; 12(6): R217PubMedCrossRefGoogle Scholar
  14. 14.
    Hao C, Anwei M, Bing C, et al. Monitoring mycophenolic acid pharmacokinetic parameters in liver transplant recipients: prediction of occurrence of leukopenia. Liver Transpl 2008 Aug; 14(8): 1165–73PubMedCrossRefGoogle Scholar
  15. 15.
    Roland M, Barbet C, Paintaud G, et al. Mycophenolate mofetil in patients with systemic lupus erythematosus: a prospective pharmacokinetic study. Lupus 2009 Apr; 18(5): 441–7PubMedCrossRefGoogle Scholar
  16. 16.
    Zahr N, Arnaud L, Marquet P, et al. Mycophenolic acid area under the curve correlates with disease activity in lupus patients treated with mycophenolate mofetil. Arthritis Rheum 2010 Jul; 62(7): 2047–54PubMedGoogle Scholar
  17. 17.
    van der Meer AF, Marcus MA, Touw DJ, et al. Optimal sampling strategy development methodology using maximum a posteriori Bayesian estimation. Ther Drug Monit 2011 Apr; 33(2): 133–46PubMedGoogle Scholar
  18. 18.
    Sherwin CM, Fukuda T, Brunner HI, et al. The evolution of population pharmacokinetic models to describe the enterohepatic recycling of mycophenolic acid in solid organ transplantation and autoimmune disease. Clin Pharmacokinet 2011 Jan 1; 50(1): 1–24PubMedCrossRefGoogle Scholar
  19. 19.
    Arns W, Cibrik DM, Walker RG, et al. Therapeutic drug monitoring of mycophenolic acid in solid organ transplant patients treated with mycophenolate mofetil: review of the literature. Transplantation 2006 Oct 27; 82(8): 1004–12PubMedCrossRefGoogle Scholar
  20. 20.
    van Hest RM, Mathot RA, Pescovitz MD, et al. Explaining variability in mycophenolic acid exposure to optimize mycophenolate mofetil dosing: a population pharmacokinetic meta-analysis of mycophenolic acid in renal transplant recipients. J Am Soc Nephrol 2006 Mar; 17(3): 871–80PubMedCrossRefGoogle Scholar
  21. 21.
    de Winter BC, Mathot RA, Sombogaard F, et al. Differences in clearance of mycophenolic acid among renal transplant recipients, hematopoietic stem cell transplant recipients, and patients with autoimmune disease. Ther Drug Monit 2010 Oct; 32(5): 606–14PubMedCrossRefGoogle Scholar
  22. 22.
    van Gelder T, Silva HT, de Fijter JW, et al. Comparing mycophenolate mofetil regimens for de novo renal transplant recipients: the Fixed-Dose Concentration-Controlled trial. Transplantation 2008 Oct 27; 86(8): 1043–51PubMedCrossRefGoogle Scholar
  23. 23.
    Byrne R, Yost SE, Kaplan B. Mycophenolate mofetil monitoring: is there evidence that it can improve outcomes? Clin Pharmacol Ther 2011 Aug; 90(2): 204–6PubMedCrossRefGoogle Scholar
  24. 24.
    van Gelder T. Therapeutic drug monitoring for mycophenolic acid is value for (little) money. Clin Pharmacol Ther 2011 Aug; 90(2): 203–4PubMedCrossRefGoogle Scholar
  25. 25.
    Kuypers DR. Immunosuppressive drug monitoring: what to use in clinical practice today to improve renal graft outcome. Transpl Int 2005 Feb; 18(2): 140–50PubMedCrossRefGoogle Scholar
  26. 26.
    Barraclough KA, Isbel NM, Staatz CE. Evaluation of the mycophenolic acid exposure estimation methods used in the APOMYGERE, FDCC, and Opticept trials. Transplantation 2010 Jul 15; 90(1): 44–51PubMedCrossRefGoogle Scholar
  27. 27.
    Dosch AO, Ehlermann P, Koch A, et al. A comparison of measured trough levels and abbreviated AUC estimation by limited sampling strategies for monitoring mycophenolic acid exposure in stable heart transplant patients receiving cyclosporin A-containing and cyclosporin A-free immunosuppressive regimens. Clin Ther 2006 Jun; 28(6): 893–905PubMedCrossRefGoogle Scholar
  28. 28.
    Zicheng Y, Xianghui W, Peijun Z, et al. Evaluation of the practicability of limited sampling strategies for the estimation of mycophenolic acid exposure in Chinese adult renal recipients. Ther Drug Monit 2007 Oct; 29(5): 600–6PubMedCrossRefGoogle Scholar
  29. 29.
    Tett SE, Saint-Marcoux F, Staatz CE, et al. Mycophenolate, clinical pharmacokinetics, formulations, and methods for assessing drug exposure. Transplant Rev (Orlando) 2011 Apr; 25(2): 47–57CrossRefGoogle Scholar
  30. 30.
    van Hest RM, Mathot RA, Vulto AG, et al. Within-patient variability of mycophenolic acid exposure: therapeutic drug monitoring from a clinical point of view. Ther Drug Monit 2006 Feb; 28(1): 31–4PubMedCrossRefGoogle Scholar
  31. 31.
    Barraclough KA, Isbel NM, Franklin ME, et al. Evaluation of limited sampling strategies for mycophenolic acid after mycophenolate mofetil intake in adult kidney transplant recipients. Ther Drug Monit 2010 Dec; 32(6): 723–33PubMedCrossRefGoogle Scholar
  32. 32.
    Ting LS, Villeneuve E, Ensom MH. Beyond cyclosporine: a systematic review of limited sampling strategies for other immunosuppressants. Ther Drug Monit 2006 Jun; 28(3): 419–30PubMedCrossRefGoogle Scholar
  33. 33.
    Saint-Marcoux F, van dierdonck S, Premaud A, et al. Large scale analysis of routine dose adjustments of mycophenolate mofetil based on global exposure in renal transplant patients. Ther Drug Monit 2011; 33(3): 285–94PubMedCrossRefGoogle Scholar
  34. 34.
    Premaud A, Le Meur Y, Debord J, et al. Maximum a posteriori Bayesian estimation of mycophenolic acid pharmacokinetics in renal transplant recipients at different postgrafting periods. Ther Drug Monit 2005 Jun; 27(3): 354–61PubMedCrossRefGoogle Scholar
  35. 35.
    Figurski MJ, Nawrocki A, Pescovitz MD, et al. Development of a predictive limited sampling strategy for estimation of mycophenolic acid area under the concentration time curve in patients receiving concomitant sirolimus or cyclosporine. Ther Drug Monit 2008 Aug; 30(4): 445–55PubMedGoogle Scholar
  36. 36.
    Sheiner LB, Rosenberg B, Melmon KL. Modelling of individual pharmacokinetics for computer-aided drug dosage. Comput Biomed Res 1972 Oct; 5(5): 411–59PubMedCrossRefGoogle Scholar
  37. 37.
    Bruchet NK, Ensom MH. Limited sampling strategies for mycophenolic acid in solid organ transplantation: a systematic review. Expert Opin Drug Metab Toxicol 2009 Sep; 5(9): 1079–97PubMedCrossRefGoogle Scholar
  38. 38.
    Saint-Marcoux F, Guigonis V, Decramer S, et al. Development of a Bayesian estimator for the therapeutic drug monitoring of mycophenolate mofetil in children with idiopathic nephrotic syndrome. Pharmacol Res 2011 May; 63(5): 423–31PubMedCrossRefGoogle Scholar
  39. 39.
    Thomson AH, Whiting B. Bayesian parameter estimation and population pharmacokinetics. Clin Pharmacokinet 1992 Jun; 22(6): 447–67PubMedCrossRefGoogle Scholar
  40. 40.
    Ludden TM, Beal SL, Sheiner LB. Comparison of the Akaike information criterion, the Schwarz criterion and the F test as guides to model selection. J Pharmacokinet Biopharm 1994 Oct; 22(5): 431–45PubMedCrossRefGoogle Scholar
  41. 41.
    Cremers S, Schoemaker R, Scholten E, et al. Characterizing the role of enterohepatic recycling in the interactions between mycophenolate mofetil and calcineurin inhibitors in renal transplant patients by pharmacokinetic modelling. Br J Clin Pharmacol 2005 Sep; 60(3): 249–56PubMedCrossRefGoogle Scholar
  42. 42.
    van Hest RM, van Gelder T, Bouw R, et al. Time-dependent clearance of mycophenolic acid in renal transplant recipients. Br J Clin Pharmacol 2007 Jun; 63(6): 741–52PubMedCrossRefGoogle Scholar
  43. 43.
    Kuypers DR, Claes K, Evenepoel P, et al. Long-term changes in mycophenolic acid exposure in combination with tacrolimus and corticosteroids are dose dependent and not reflected by trough plasma concentration: a prospective study in 100 de novo renal allograft recipients. J Clin Pharmacol 2003 Aug; 43(8): 866–80PubMedCrossRefGoogle Scholar
  44. 44.
    de Winter BC, Mathot RA, Sombogaard F, et al. Nonlinear relationship between mycophenolate mofetil dose and mycophenolic acid exposure: implications for therapeutic drug monitoring. Clin J Am Soc Nephrol 2011 Mar; 6(3): 656–63PubMedCrossRefGoogle Scholar
  45. 45.
    Premaud A, Rousseau A, Le Meur Y, et al. Feasibility of, and critical paths for mycophenolate mofetil Bayesian dose adjustment: pharmacological reappraisal of a concentration-controlled versus fixed-dose trial in renal transplant recipients. Pharmacol Res 2010 Feb; 61(2): 167–74PubMedCrossRefGoogle Scholar
  46. 46.
    Musuamba FT, Rousseau A, Bosmans JL, et al. Limited sampling models and Bayesian estimation for mycophenolic acid area under the curve prediction in stable renal transplant patients co-medicated with ciclosporin or sirolimus. Clin Pharmacokinet 2009; 48(11): 745–58PubMedCrossRefGoogle Scholar
  47. 47.
    Le Guellec C, Bourgoin H, Buchler M, et al. Population pharmacokinetics and Bayesian estimation of mycophenolic acid concentrations in stable renal transplant patients. Clin Pharmacokinet 2004; 43(4): 253–66PubMedCrossRefGoogle Scholar
  48. 48.
    Hulin A, Blanchet B, Audard V, et al. Comparison of 3 estimation methods of mycophenolic acid AUC based on a limited sampling strategy in renal transplant patients. Ther Drug Monit 2009 Apr; 31(2): 224–32PubMedCrossRefGoogle Scholar
  49. 49.
    Premaud A, Weber LT, Tonshoff B, et al. Population pharmacokinetics of mycophenolic acid in pediatric renal transplant patients using parametric and nonparametric approaches. Pharmacol Res 2011 Mar; 63(3): 216–24PubMedCrossRefGoogle Scholar
  50. 50.
    Payen S, Zhang D, Maisin A, et al. Population pharmacokinetics of mycophenolic acid in kidney transplant pediatric and adolescent patients. Ther Drug Monit 2005 Jun; 27(3): 378–88PubMedCrossRefGoogle Scholar
  51. 51.
    Monchaud C, De Winter B, Premaud A, et al. Bayesian estimation of mycophenolate mofetil (MMF) in lung transplantation using a population pharmacokinetic model developed in renal and lung transplant recipients [abstract]. Fundam Clin Pharmacol 2011; 25 Suppl. 1: 46Google Scholar
  52. 52.
    de Winter BC, Neumann I, van Hest RM, et al. Limited sampling strategies for therapeutic drug monitoring of mycophenolate mofetil therapy in patients with autoimmune disease. Ther Drug Monit 2009 Jun; 31(3): 382–90PubMedCrossRefGoogle Scholar
  53. 53.
    Sam WJ, Joy MS. Population pharmacokinetics of mycophenolic acid and metabolites in patients with glomerulonephritis. Ther Drug Monit 2010 Oct; 32(5): 594–605PubMedCrossRefGoogle Scholar
  54. 54.
    Zahr N, Amoura Z, Debord J, et al. Pharmacokinetic study of mycophenolate mofetil in patients with systemic lupus erythematosus and design of Bayesian estimator using limited sampling strategies. Clin Pharmacokinet 2008; 47(4): 277–84PubMedCrossRefGoogle Scholar
  55. 55.
    Saint-Marcoux F, Royer B, Debord J, et al. Pharmacokinetic modelling and development of Bayesian estimators for therapeutic drug monitoring of mycophenolate mofetil in reduced-intensity haematopoietic stem cell transplantation. Clin Pharmacokinet 2009; 48(10): 667–75PubMedCrossRefGoogle Scholar
  56. 56.
    Zhao W, Elie V, Baudouin V, et al. Population pharmacokinetics and Bayesian estimator of mycophenolic acid in children with idiopathic nephrotic syndrome. Br J Clin Pharmacol 2010 Apr; 69(4): 358–66PubMedCrossRefGoogle Scholar
  57. 57.
    Beal S, Sheiner LB, Boeckmann A, et al. NONMEM user’s guides (1989–2011). Ellicott City (MD): Icon Development Solutions, 2011Google Scholar
  58. 58.
    Fleming DH, Mathew BS, Prasanna S, et al. A possible simplification for the estimation of area under the curve (AUC) of enteric-coated mycophenolate sodium in renal transplant patients receiving tacrolimus. Ther Drug Monit 2011 Apr; 33(2): 165–70PubMedGoogle Scholar
  59. 59.
    Barraclough KA, Lee KJ, Staatz CE. Pharmacogenetic influences on mycophenolate therapy. Pharmacogenomics 2010 Mar; 11(3): 369–90PubMedCrossRefGoogle Scholar
  60. 60.
    Picard N, Marquet P. The influence of pharmacogenetics and cofactors on clinical outcomes in kidney transplantation. Expert Opin Drug Metab Toxicol 2011 Jun; 7(6): 731–43PubMedCrossRefGoogle Scholar
  61. 61.
    Raggi MC, Siebert SB, Steimer W, et al. Customized mycophenolate dosing based on measuring inosine-monophosphate dehydrogenase activity significantly improves patients’ outcomes after renal transplantation. Transplantation 2010 Dec 27; 90(12): 1536–41PubMedCrossRefGoogle Scholar
  62. 62.
    van Gelder T. Mycophenolate blood level monitoring: recent progress. Am J Transplant 2009 Jul; 9(7): 1495–9PubMedCrossRefGoogle Scholar

Copyright information

© Adis Data Information BV 2011

Authors and Affiliations

  1. 1.School of PharmacyUniversity of QueenslandBrisbaneAustralia

Personalised recommendations