In mycophenolate mofetil (MMF)-treated organ transplant recipients, lower mycophenolic acid (MPA) plasma concentrations have been found in cyclosporine (CsA) compared with tacrolimus (Tac)-based immunosuppressive regimens. We previously demonstrated that CsA decreases exposure to MPA and increases exposure to its metabolite MPAglucuronide (MPAG), possibly by interfering with the biliary excretion of MPAG. To elucidate the role of the multidrug resistance-associated protein (Mrp)-2 in the interaction between MMF and CsA, we treated three groups of 10 Mrp2-deficient rats (TR− rat) for 6 days with either vehicle, CsA (8 mg/kg) or Tac (4 mg/kg) by oral gavage. Hereafter, co-administration with MMF (20 mg/kg) was started in all groups and continued through day 14. The 24-h MPA/MPAG area under the concentration-time curve (AUC) was determined after single (day 7) and multiple MMF doses (day 14). On both study days, there were no significant differences in the mean MPA and MPAG AUC between CsA and Tac-treated animals. We conclude that the pharmacokinetics of MMF are comparable in Mrp2-deficient rats receiving either CsA or Tac as comedication. This finding suggests that CsA-mediated inhibition of the biliary excretion of MPAG by the Mrp2 transporter is the mechanism responsible for the interaction between CsA and MMF.

Large between-and within-patient variability has been observed in the pharmacokinetics of mycophenolic acid (MPA). However, conflicting results exist about the influence of patient characteristics that explain the variability in MPA exposure. This population pharmacokinetic meta-analysis of MPA in renal transplant recipients was performed to explore whether race, renal function, albumin level, delayed graft function, diabetes, and co-medication are determinants of total MPA exposure. A total of 13,346 MPA concentration-time data points from 468 renal transplant patients who participated in six clinical studies were combined and analyzed retrospectively. Sampling occasions ranged from day 1 after transplantation to 10 yr after transplantation. Concentration-time data were analyzed with nonlinear mixed-effect modeling. Exposure to total MPA, as determined by MPA clearance, significantly increased with increasing renal function, albumin level, and hemoglobin as well as decreasing cyclosporine predose level (P < 0.001). These variables could explain 18% of the between-patient and 38% of the within-patient variability in MPA exposure. Differences in MPA exposure between patients with or without delayed graft function or between patients of different races are likely to be caused by the effect of renal function on MPA exposure. Diabetes did not have an effect on MPA exposure. The clinical implication is that a change in renal function or albumin level provides an indication for therapeutic drug monitoring as MPA exposure may be altered. Patients in whom cyclosporine and mycophenolate mofetil are combined may need higher mycophenolate mofetil doses, especially during the early phase after transplantation than currently recommended for optimal MPA exposure.

Mycophenolic acid (MPA), the active compound of mycophenolate mofetil (MMF), is used to prevent graft rejection in renal transplant recipients. MPA is glucuronidated to the metabolite MPAG, which exhibits enterohepatic recirculation (EHC). MPA binds for 97% and MPAG binds for 82% to plasma proteins. Low plasma albumin concentrations, impaired renal function and coadministration of cyclosporine have been reported to be associated with increased clearance of MPA. The aim of the study was to develop a population pharmacokinetic model describing the relationship between MMF dose and total MPA (tMPA), unbound MPA (fMPA), total MPAG (tMPAG) and unbound MPAG (fMPAG). In this model the correlation between pharmacokinetic parameters and renal function, plasma albumin concentrations and cotreatment with cyclosporine was quantified. tMPA, fMPA, tMPAG and fMPAG concentration-time profiles of renal transplant recipients cotreated with cyclosporine (n = 48) and tacrolimus (n = 45) were analyzed using NONMEM. A 2-and 1-compartment model were used to describe the pharmacokinetics of fMPA and fMPAG. The central compartments of fMPA and fMPAG were connected with an albumin compartment allowing competitive binding (bMPA and bMPAG). tMPA and tMPAG were modeled as the sum of the bound and unbound concentrations. EHC was modeled by transport of fMPAG to a separate gallbladder compartment. This transport was decreased in case of 123J Pharmacokinet Pharmacodyn (2009) 36:541-564 DOI 10.1007 cyclosporine cotreatment (P \ 0.001). In the model, clearance of fMPAG decreased when creatinine clearance (CrCL) was reduced (P \ 0.001), and albumin concentration was correlated with the maximum number of binding sites available for MPA and MPAG (P \ 0.001). In patients with impaired renal function cotreated with cyclosporine the model adequately described that increasing fMPAG concentrations decreased tMPA AUC due to displacement of MPA from its binding sites. The accumulated MPAG could also be reconverted to MPA by the EHC, which caused increased tMPA AUC in patients cotreated with tacrolimus. Changes in CrCL had hardly any effect on fMPA exposure. A decrease in plasma albumin concentration from 0.6 to 0.4 mmol/l resulted in ca. 38% reduction of tMPA AUC, whereas no reduction in fMPA AUC was seen. In conclusion, a pharmacokinetic model has been developed which describes the relationship between dose and both total and free MPA exposure. The model adequately describes the influence of renal function, plasma albumin and cyclosporine co-medication on MPA exposure. Changes in protein binding due to altered renal function or plasma albumin concentrations influence tMPA exposure, whereas fMPA exposure is hardly affected.

The developed population pharmacokinetic model adequately describes the pharmacokinetics of MPA in renal transplant recipients. The identified correlations appear to explain part of the observed inter- and intrapatient pharmacokinetic variability. The clinical consequences of the observed correlations remain to be investigated.

Initial adequate anti-infective therapy is associated with significantly improved clinical outcomes for patients with severe infections. However, in critically ill patients, several pathophysiological and/or iatrogenic factors may affect the pharmacokinetics of anti-infective agents leading to suboptimal drug exposure, in particular during the early phase of therapy. Therapeutic drug monitoring (TDM) may assist to overcome this problem. We discuss the available evidence on the use of TDM in critically ill patient populations for a number of anti-infective agents, including aminoglycosides, β-lactams, glycopeptides, antifungals and antivirals. Also, we present the available evidence on the practices of anti-infective TDM and describe the potential utility of TDM to improve treatment outcome in critically ill patients with severe infections. For aminoglycosides, glycopeptides and voriconazole, beneficial effects of TDM have been established on both drug effectiveness and potential side effects. However, for other drugs, therapeutic ranges need to be further defined to optimize treatment prescription in this setting.