Population pharmacokinetics of tacrolimus in adult kidney transplant recipients

Objectives: The aims of this study were to investigate the population pharmacokinetics of tacrolimus in adult kidney transplant recipients and to identify factors that explain variability. Methods: Population analysis was performed on retrospective data from 70 patients who received oral tacrolimus twice daily. Morning blood trough concentrations were measured by liquid chromatography-tandem mass spectrometry. Maximum likelihood estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F), with the use of NONMEM (GloboMax LLC, Hanover, Md). Factors screened for influence on these parameters were weight, age, gender, postoperative day, days of tacrolimus therapy, liver function tests, creatinine clearance, hematocrit fraction, corticosteroid dose, and potential interacting drugs. Results. CL/F was greater in patients with abnormally low hematocrit fraction (data from 21 patients only), and it decreased with increasing days of therapy and AST concentrations (P

Toward better outcomes with tacrolimus therapy: Population pharmacokinetics and individualized dosage prediction in adult liver transplantation

Patient outcomes in transplantation would improve if dosing of immunosuppressive agents was individualized. The aim of this study is to develop a population pharmacokinetic model of tacrolimus in adult liver transplant recipients and test this model in individualizing therapy. Population analysis was performed on data from 68 patients. Estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F) using the nonlinear mixed effects model program (NONMEM). Factors screened for influence on these parameters were weight, age, sex, transplant type, biliary reconstructive procedure, postoperative day, days of therapy, liver function test results, creatinine clearance, hematocrit, corticosteroid dose, and interacting drugs. The predictive performance of the developed model was evaluated through Bayesian forecasting in an independent cohort of 36 patients. No linear correlation existed between tacrolimus dosage and trough concentration (r(2) = 0.005). Mean individual Bayesian estimates for CL/F and V/F were 26.5 8.2 (SD) L/hr and 399 +/- 185 L, respectively. CL/F was greater in patients with normal liver function. V/F increased with patient weight. CL/F decreased with increasing hematocrit. Based on the derived model, a 70-kg patient with an aspartate aminotransferase (AST) level less than 70 U/L would require a tacrolimus dose of 4.7 mg twice daily to achieve a steady-state trough concentration of 10 ng/mL. A 50-kg patient with an AST level greater than 70 U/L would require a dose of 2.6 mg. Marked interindividual variability (43% to 93%) and residual random error (3.3 ng/mL) were observed. Predictions made using the final model were reasonably nonbiased (0.56 ng/mL), but imprecise (4.8 ng/mL). Pharmacokinetic information obtained will assist in tacrolimus dosing; however, further investigation into reasons for the pharmacokinetic variability of tacrolimus is required.

Effect of atorvastatin on cyclosporine pharmacokinetics in liver transplant recipients

BACKGROUND: The development of hyperlipidemia after liver transplant is frequently treated with hydroxymethylglutaryl coenzyme A reductase inhibitors (statins) such as atorvastatin. As atorvastatin and the primary immunosuppressant drug, cyclosporine, are metabolized by the same pathway, there is the potential for an interaction. OBJECTIVE: To determine the effect of atorvastatin on cyclosporine pharmacokinetics in liver transplant recipients. METHODS: Six stable, long-term adult liver transplant recipients from a single center who developed posttransplant dyslipidemia were recruited to participate in a 14-day, open-label study of atorvastatin 10 mg/d coadministered with standard posttransplant immunosuppression using constant oral doses-of cyclosporine and corticosteroids. A 10-point pharmacokinetic profile was performed prior to and on day 14 after commencement of atorvastatin therapy. Cyclosporine concentrations were measured by HPLC-electrospray-tandem mass spectrometry. The AUC was calculated by the linear trapezoidal rule, with other parameters determined by visual inspection. RESULTS: Atorvastatin coadministration increased the cyclosporine AUC by 9% (range 0-20.6%; 3018 vs 3290 ng(.)h/mL; p = 0.04). No significant change was evident for other cyclosporine pharmacokinetic parameters. Total cholesterol and low-density lipoprotein cholesterol levels were significantly lower on day 14 than at baseline (p < 0.02). One patient developed a twofold increase in transaminases after 2 weeks of atorvastatin therapy, but no other clinical or biochemical adverse events were recorded. CONCLUSIONS: Atorvastatin coadministration increases the cyclosporine AUC by approximately 10% in stable liver transplant recipients. This change in systemic exposure to cyclosporine is of questionable clinical significance. Atorvastatin is effective in reducing cholesterol levels in liver transplant recipients.

Sampling times for monitoring tacrolimus in stable adult liver transplant recipients

The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R-2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).

Clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation

The aim of this review is to analyse critically the recent literature on the clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplant recipients. Dosage and target concentration recommendations for tacrolimus vary from centre to centre, and large pharmacokinetic variability makes it difficult to predict what concentration will be achieved with a particular dose or dosage change. Therapeutic ranges have not been based on statistical approaches. The majority of pharmacokinetic studies have involved intense blood sampling in small homogeneous groups in the immediate post-transplant period. Most have used nonspecific immunoassays and provide little information on pharmacokinetic variability. Demographic investigations seeking correlations between pharmacokinetic parameters and patient factors have generally looked at one covariate at a time and have involved small patient numbers. Factors reported to influence the pharmacokinetics of tacrolimus include the patient group studied, hepatic dysfunction, hepatitis C status, time after transplantation, patient age, donor liver characteristics, recipient race, haematocrit and albumin concentrations, diurnal rhythm, food administration, corticosteroid dosage, diarrhoea and cytochrome P450 (CYP) isoenzyme and P-glycoprotein expression. Population analyses are adding to our understanding of the pharmacokinetics of tacrolimus, but such investigations are still in their infancy. A significant proportion of model variability remains unexplained. Population modelling and Bayesian forecasting may be improved if CYP isoenzymes and/or P-glycoprotein expression could be considered as covariates. Reports have been conflicting as to whether low tacrolimus trough concentrations are related to rejection. Several studies have demonstrated a correlation between high trough concentrations and toxicity, particularly nephrotoxicity. The best predictor of pharmacological effect may be drug concentrations in the transplanted organ itself. Researchers have started to question current reliance on trough measurement during therapeutic drug monitoring, with instances of toxicity and rejection occurring when trough concentrations are within 'acceptable' ranges. The correlation between blood concentration and drug exposure can be improved by use of non-trough timepoints. However, controversy exists as to whether this will provide any great benefit, given the added complexity in monitoring. Investigators are now attempting to quantify the pharmacological effects of tacrolimus on immune cells through assays that measure in vivo calcineurin inhibition and markers of immuno suppression such as cytokine concentration. To date, no studies have correlated pharmacodynamic marker assay results with immunosuppressive efficacy, as determined by allograft outcome, or investigated the relationship between calcineurin inhibition and drug adverse effects. Little is known about the magnitude of the pharmacodynamic variability of tacrolimus.

Insulin and Oleate Promote Translocation of Inosine-5' Monophosphate Dehydrogenase to Lipid Bodies

In the present study we identify inosine-5' monophosphate dehydrogenase (IMPDH), a key enzyme in de novo guanine nucleotide biosynthesis, as a novel lipid body-associated protein. To identify new targets of insulin we performed a comprehensive 2-DE analysis of P-32-labelled proteins isolated from 3T3-L1 adipocytes (Hill et al. J Biol Chem 2000; 275: 24313-24320). IMPDH was identified by liquid chromatography/tandem mass spectrometry as a protein which was phosphorylated in a phosphatidylinositol (PI) 3-kinase-dependent manner upon insulin treatment. Although insulin had no significant effect on IMPDH activity, we observed translocation of IMPDH to lipid bodies following insulin treatment. Induction of lipid body formation with oleic acid promoted dramatic redistribution of IMPDH to lipid bodies, which appeared to be in contact with the endoplasmic reticulum, the site of lipid body synthesis and recycling. Inhibition of PI 3-kinase blocked insulin- and oleate-induced translocation of IMPDH and reduced oleate-induced lipid accumulation. However, we found no evidence of oleate-induced IMPDH phosphorylation, suggesting phosphorylation and translocation may not be coupled events. These data support a role for IMPDH in the dynamic regulation of lipid bodies and fatty acid metabolism and regulation of its activity by subcellular redistribution in response to extracellular factors that modify lipid metabolism.

CEDIA (R) sirolimus assay compared with HPLC-MS/MS and HPLC-UV in transplant recipient specimens

The role of the therapeutic drug monitoring laboratory in support of immunosuppressant drug therapy is well established, and the introduction of sirolimus (SRL) is a new direction in this field. The lack of an immunoassay for several years has restricted the availability of SRL assay services. The recent availability of a CEDIA (R) SRL assay has the potential to improve this situation. The present communication has compared the CEDIA (R) SRL method with 2 established chromatographic methods, HPLC-UV and HPLC-MS/MS. The CEDIA (R) method, run on a Hitachi 917 analyzer, showed acceptable validation criteria with within-assay precision of 9.1% and 3.3%, and bias of 17.1% and 5.8%, at SRL concentrations of 5.0 mu g/L and 20 mu g/L, respectively. The corresponding between-run precision values were 11.5% and 3.3% and bias of 7.1% and 2.9% at 5.0 mu g/L and 20 mu g/L, respectively, The lower limit of quantification was found to be 3.0 mu g/L. A series of 96 EDTA whole-blood samples predominantly from renal transplant recipients were assayed by the 3 methods for comparison. It was found that the CEDIA (R) method showed a Deming regression line of CEDIA = 1.20 X HPLC-MS/MS - 0.07 (r = 0.934, SEE = 1.47), with a mean bias of 20.4%. Serial blood samples from 8 patients included in this evaluation showed that the CEDIA (R) method reflected the clinical fluctuations in the chromatographic methods, albeit with the variable bias noted. The CEDIA (R) method on the H917 analyzer is therefore a useful adjunct to SRL dosage individualization in renal transplant recipients.

Comparison of the pharmacokinetics of oxycodone and noroxycodone in male dark agouti and Sprague-Dawley rats: Influence of streptozotocin-induced diabetes

Purpose. The aims of this study are to evaluate whether cytochrome P450 (CYP)2D1/2D2-deficient dark agouti (DA) rats and/or CYP2D1/2D2-replete Sprague-Dawley (SD) rats are suitable preclinical models of the human, with respect to mirroring the very low plasma concentrations of metabolically derived oxymorphone seen in humans following oxycodone administration, and to examine the effects of streptozotocin-induced diabetes on the pharmacokinetics of oxycodone and its metabolites, noroxycodone and oxymorphone, in both rodent strains. Methods. High-performance liquid chromatography-electrospray ionization-tandem mass spectrometry was used to quantify the serum concentrations of oxycodone, noroxycodone, and oxymorphone following subcutaneous administration of bolus doses of oxycodone (2 mg/kg) to groups of nondiabetic and diabetic rats. Results. The mean (+/- SEM) areas under the serum concentration vs. time curves for oxycodone and noroxycodone were significantly higher in DA relative to SD rats (diabetic, p < 0.05; nondiabetic, p < 0.005). Serum concentrations of oxymorphone were very low (< 6.9 nM). Conclusions. Both DA and SD rats are suitable rodent models to study oxycodone's pharmacology, as their systemic exposure to metabolically derived oxymorphone (potent mu-opioid agonist) is very low, mirroring that seen in humans following oxycodone administration. Systemic exposure to oxycodone and noroxycodone was consistently higher for DA than for SD rats showing that strain differences predominated over diabetes status.