Tacrolimus dose individualization in "de novo" patients after 10 years of experience in liver transplantation: pharmacokinetic considerations and patient pathophysiology.

AIM: To determine how changes in tacrolimus (TAC) immunosuppression clinical practice, in the first 15 days post liver transplantation (LT) and across a decade, impact a clinical covariate - pharmacokinetic (PK) model, developed in data from 1998, thus testing its utility in dose individualization across time. Patient cohorts from 1998 (Reference: R-1998) and 2007 (EVALUATION: E-2007) were compared. METHODS: Analysis of monitoring observations (Cmin and Cmin/dose) and the biochemical variables aspartate aminotransferase (AST), hematocrit (HCT), albumin (ALB) and serum creatinine (SCr) was done for 0 - 3 and 4 - 15 days post transplantation (PT). The population PK model developed for R-1998 [1] was re-evaluated for the two cohorts. RESULTS: Significant differences in R-1998 vs. E-2007 existed in Cmin and Cmin/dose and in covariates AST (as hepatic function marker) and SCr (as toxicity marker). E-2007 had lower levels of Cmin and Cmin/dose (1/CL), lower AST with faster recovery and lower variability in Cmin/dose for similar dose. AST was a covariate on CL/F in the 0 - 3 day PT period. In 4 - 15 days PT for E-2007, low levels of HCT and ALB as CL/F predictors confirmed a subgroup with higher CL/F (23.8 l/h vs. 19.3 l/h). The R-1998 model's original structure was confirmed. CONCLUSIONS: Ten years of use of TAC shows gain in therapeutic targeting efficiency, due to improvement in LT methods, knowledge of the drug and consideration of PK steady state. The remaining uncertainty with TAC monitoring in LT can be resolved with application of PK principles combined with patients' diosyncrasies in the model developed for TAC dose individualization in R-1998. The applicability of the model as nucleus in Bayes individualization remains intact across a decade.

A predictive pharmacokinetic/pharmacodynamic model of fentanyl for analgesia/sedation in neonates based on a semi-physiologic approach.

BACKGROUND AND OBJECTIVES: Fentanyl is a synthetic opioid commonly used as an anesthetic and also increasingly popular as a sedative agent in neonates. Initial dosage regimens in this population are often empirically derived from adults on a body weight basis. However, ontogenic maturation processes related to drug disposition are not necessarily always body weight correlates. We developed a predictive pharmacokinetic/pharmacodynamic model that includes growth and maturation physiologic changes for fentanyl in neonatal care. METHODS: Key pharmacokinetic variables and principles (protein binding, clearance, distribution) as related to fentanyl pharmacokinetic/pharmacodynamic behavior in adults (tricompartmental model) and to neonatal physiologic data (organ weights and blood flows, body composition, renal and hepatic function, etc.) were used to guide the building of a semi-physiologic ontogenic model. The model applies to a normal-term neonate without any other intervention. Then, extension to a pharmacokinetic/pharmacodynamic link model for fentanyl was made. The final model was evaluated by predicting the time course of plasma concentrations and the effect of a standard regimen of 10.5 µg/kg over a 1-h period followed by 1.5 µg/kg/h for 48 h. RESULTS: Hepatic clearance was linked to ontogeny of unbound fraction and of α1-acid glycoprotein. All parameters were reduced in the neonate compared to adults but in a differing proportion due to qualitative changes in physiology that are analyzed and accounted for. Systemic clearance (CLS), volume of the central compartment (V1) and steady-state volume of distribution predicted by the model were 0.028 L/min, 1.26 L, and 22.04 L, respectively. Weight-corrected parameters generally decreased in adults compared with neonates, but differentially, e.g., CLS = 0.0093 versus 0.0088 L/min/kg, while V1 = 0.42 versus 0.18 L/kg (neonates vs. adults). Under such complexity a pharmacokinetic/pharmacodynamic model is the appropriate method for rational efficacy targeting. Fentanyl pharmacodynamics in neonates were considered to be similar to those in adults except for the equilibrium rate constant, which was also scaled on an ontogenic basis. The model adequately predicted the reported mean expected concentration-time profiles for the standard regimen. CONCLUSIONS: Integrated pharmacokinetic/pharmacodynamic modeling showed that the usually prescribed dosage regimens of fentanyl in neonates may not always provide the optimum degree of sedation. The model could be used in optimal design of clinical trials for this vulnerable population. Prospective clinical testing is the reasonable next step.

Tacrolimus pharmacokinetics in the early post-liver transplantation period and clinical applicability via Bayesian prediction.

PURPOSE: To define and validate a pharmacokinetic (PK) model for tacrolimus (TAC) that includes patient pathophysiology and has clinical applicability in the first 2 weeks post-liver transplantation (PLT). METHODS: Routine monitoring records [dose, trough levels (C(min)), demographics, biochemistry] from 75 patients treated with TAC (Prograf®) PLT were used to develop a population PK model (employing NONMEM®) testing for predictors of oral clearance (CL/F) according to bedside evidence and primarily with aspartate aminotransferase (AST), albumin (ALB), and hematocrit (HCT). Patients were catergorized into subgroups with above and below "normal" thresholds for AST (500 U/L), ALB (2.5 g/dL), and HCT (28 %), respectively. The model was validated with ten patients from the same period and 15 more recent patients. An empirical Bayes method was developed and applied to the prediction of individual profiles serving as a dose adjustment tool. RESULTS: The number of days PLT (Days PLT) was a key variable during the first 2 weeks, with a dichotomy in the mono-compartmental parameters for 0-3 Days PLT and 4-15 Days PLT. During 0-3 Days PLT, AST levels, indicative of allograft functionality (and TAC metabolism), were crucial predictors of elimination. Three groups were identified with the following clearances: CL/F0₋3 = 8.93 L/h for AST ≥ 500 U/L and CL/F0₋3 = 11.0 L/h for AST <500 U/L. During 4-15 Day PLT, low values of ALB (<2.5 g/dL) and HCT (<28 %) combined were determinant of a patient subgroup with a tendency to underexposure and complexity in empirical dose adjustment. The CL/F4₋15 = 25.1 L/h for this subgroup compared to CL/F4₋15 = 17.1 L/h for the others in that period. The elimination half-life for individual patients varied over tenfold so that a large number of subjects were not at steady state, making the use of a PK model necessary to achieve rapidly and safely the target concentration for TAC in LT. Validation of the model demonstrated that both bias and precision were within acceptable limits. CONCLUSION: For TAC therapy, covariate models using mixed effects methods are most useful when combined with patient-specific biochemical assays as well as clinical evidence. In such cases, the observed C(min) and Bayes methods can provide the most likely individual PK parameters, hence the optimal next dose to reach individualized target levels for each patient.

Pathophysiological idiosyncrasies and pharmacokinetic realities may interfere with tacrolimus dose titration in liver transplantation.

PURPOSE: To explore the main factors that make it difficult to empirically monitor tacrolimus (TAC) in the early period post-liver transplantation (LTx), with a specific focus on those aspects related to patient idiosyncrasy and clinical status as well as to the pharmacokinetic (PK) assumptions on which drug individualization in clinical practice is based. METHODS: Retrospective monitoring data from 75 de novo liver transplant patients treated with twice daily with TAC and followed for up to 15 days were analyzed. An extensive battery of laboratory measurements were available. Dose adjustment was performed empirically using trough levels (C(min)). The population was separated into two major background groups according to low or high values of aspartate aminotransferase (AST) (Group 1 and 2, respectively) based on AST measurements made during the first 4 days post-LTx. Each of these two major groups was then further subdivided into two subgroups based on elevated (Groups 1A, 2A) or reduced (Groups 1B, 2B) combined albumin (cut-off 2.5 g/dl) and hematocrit (cut-off 28%). RESULTS: The C(min)/Dose ratio [inversely proportional to systemic clearance (CL)] had a variability [coefficient of variation (CV) >80%) that was incongruently higher for the ratio than for C(min) and Dose separately. This was attributed to most patients not being at steady state or physiologically stable in the early post-LTx period. Group 1 patients were more predictable than Group 2 patients, who were responsible for the variability in the ratio. C(min) was lower in the reduced ALB and HCT patient groups when AST conditions were similar (1A vs. 1B and 2A vs. 2B), likely due to increased TAC metabolic clearance (reduced C(min)/Dose). This situation existed for two periods: 0-15 days post-LTx and 4-15 days post-LTx observations. Group 2A patients were the main source of the paradoxical variability in C(min)/Dose (higher ratio of 2.7; CV = 100%), suggesting a lower clearance and difficulty in the recovery of stability. In contrast, Group 2B patients had the lower ratio (1.4; 47%) but required the highest number of dose adjustments as the variability was hard to identify clinically. Group 1A patients were the most predictable empirically. When observations from 15 new patients who entered the clinic in 2007 and 2008 were used for the analysis, the same sub-groups existed in the same proportions in both years. CONCLUSION: The difficulty in empirical dose adjustment of TAC is associated to the inevitable non-fulfillment of PK assumptions early post-LTx and also to the inherent complexity of the clinical condition, leading to increased uncertainty for the clinician regarding dose selection. Identifying these sub-categories provides a rational means of classifying patients akin to a phenotype. The complexity of the kinetics in LTx and TAC treatment does not invalidate C(min) as a biomarker, but a Bayes algorithm including a full PK structure and these covariates would be optimal.

Simulation of sirolimus exposures and population variability immediately post renal transplantation: importance of the patient's CYP3A5 genotype in tailoring treatment.

The rapid achievement of efficacious exposure to sirolimus (SRL) after renal transplantation is crucial. However, there is high unpredictability in the dose to exposure relationship. Part of the variation is related to patients originating from subpopulations of fast or slow metabolizers via the CYP3A5*1/*3 genotype. The probability of achieving therapeutic SRL blood concentrations for each subpopulation under two equal-intensity increasing-frequency protocols after the start of treatment was explored with Monte Carlo simulation. The population pharmacokinetic model and inter-patient variability distributions of Djebli et al. (DRH2006) were sampled. They developed a base and final model with a genotype covariate for CL/F in patients receiving calcineurin inhibitor (CNI)-free therapy with SRL, mycophenolate mofetil and corticosteroids. Fast metabolizers (expressers) had a CL/F of 28.3 l/h whilst slow metabolizers (non-expressers) had a CL/F of 14.1 l/h. Here, in simulation, a standard 10 mg QD SRL was contrasted with a higher frequency of 5 mg BID SRL as related to the proportion of next dosed patients being within the 15-30 ng/ml trough levels on day 7 after transplantation. Near 0% of expressers on either regimen reached or exceeded the 30 ng/ml trough on day 7. Expressers showed protocol dependence for the chance of being within the 15-30 ng/ml range with the 5 mg BID protocol doubling those chances. Non-expressers appeared less protocol dependent for the probability of being above or below the 15-30 ng/ml range. The ability to determine the genotype early on may help to rationalize the initial titration of individual patients receiving CNI-free renal transplantation treatment with SRL.

Modeling methadone pharmacokinetics in rats in presence of P-glycoprotein inhibitor valspodar.

PURPOSE: To quantify the in vivo role of P-glycoprotein (P-gp) in the pharmacokinetics of methadone after intravenous and oral administration, using valspodar as a P-gp inhibitor. MATERIALS AND METHODS: Methadone plasma concentrations after intravenous (0.35 mg/kg) and oral (6 mg/kg) administration were analyzed, in absence and presence of valspodar, using nonlinear mixed effects modeling (NONMEM V). Non-parametric bootstrap analysis and posterior predictive check were employed as model evaluation techniques. RESULTS: The pharmacokinetics of methadone in the rat was successfully modeled using a two-compartmental model with a linear elimination from the central compartment and a first-order absorption process with lag time. Valspodar increased methadone F by 122% (95%CI: 34-269%) and decreased the V ( c ) and V ( p ) by 35% (95%CI: 16-49%) and 81% (95%CI: 63-93%), respectively. No effect of valspodar on other pharmacokinetic parameters was discernible. The non-parametric bootstrap analysis confirmed the absence of bias on the parameter estimates, and visual predictive check evidence the adequacy of the model to reproduce the observed time course of methadone plasma concentrations. CONCLUSION: Valspodar increased methadone's bioavailability as consequence of P-gp inhibition, which resulted in an increased analgesic effect of methadone.

The role of unbound drug in pharmacokinetics/pharmacodynamics and in therapy.

The evolution of research on drug protein binding is discussed with the unbound concentration (Cu) and the unbound fraction (fu) as protagonists. Particular attention is paid to the mechanisms via which alterations in binding affect the pharmacokinetics (PK) and the effect, or independently the pharmacodynamics (PD). Apart from albumin, the important alpha-acid glycoprotein (AGP), as well as specific drug classes and applications in the clinic and development (routine monitoring, cancer and HIV therapy, allometry) are addressed. The flaws with the classical method of indirectly calculating the Cu or the unbound PK/PD parameters, based on the fu in vitro, are related to the intrinsic complexity and variability in the outcomes. Increased focus is urged on directly estimating the unbound PK/PD and also on using population statistical methods.

Bicompartmental kinetics of tobramycin analysed with a wide range of covariates.

The pharmacokinetics of tobramycin was studied in adult patients (N = 151) admitted either for initial suspicion of Gram-negative infection or for prophylaxis. In addition to age, weight, height and creatinine clearance (CrCL), a range of other covariates were also analysed, including type of pathology, co-medication, fever, sex and ethnicity (Basque or not). All patients received 100mg tobramycin every 8 h and samples were collected at three time points after the first dose and at two time points after the fourth dose and assayed with a fluorescence polarisation immunoassay. The population mixed effects bicompartmental parameters were obtained from 725 concentration measurements using NONMEM, FOCE method, and were: systemic clearance, CL = 6.03 L/h (between-subject coefficient of variation (CV) %, 29.4%); volume of distribution, V = 15.04 L (7.3%); and intercompartmental constants, k(12) = 0.192 h(-1) (56%) and k(21) = 0.55 h(-1) (no CV% determined). Covariate modelling was performed within NONMEM. Two alternative significant covariate models (Models 1 and 2) are proposed, with functions of CrCL and/or sex (Model 2). However, for clinical purposes, differentiation by sex is insignificant. Model 1 is for CL = 3.1 + 0.05.CrCLL/h (17.3%); V = 14.6 L (12%); k(12) = 0.224 h(-1) (63%) and k(21) = 0.468 h(-1). Stochastic simulation was used to predict the expected concentration 95th percentiles after the recommended 7 mg/kg dose and for minimum inhibitory concentration (MIC) = 1 mg/L, as well as alternative once-daily dosing regimens for MIC = 2 mg/L. It is seen that once-daily high-dose tobramycin is an appropriate strategy with respect to pharmacodynamic indices, C(peak)/MIC or AUC/MIC (where C(peak) is the peak plasma concentration and AUC is the area under the concentration-time curve).

Pharmacokinetic-pharmacodynamic modeling of the hydroxy lerisetron metabolite L6-OH in rats: an integrated parent-metabolite model.

PURPOSE: The twofold aim of this study was to characterize in vivo in rats the pharmacokinetics (PK) and pharmacodynamics (PD) of L6-OH, a metabolite of lerisetron with in vitro pharmacological activity, and evaluate the extent to which L6-OH contributes to the overall effect. METHODS: The PK of L6-OH was determined directly postmetabolite i.v. dose (PK-1), and also simultaneously for L (lerisetron concentration) and for generated L6-OH after lerisetron dose (200 microg kg(-1), i.v.), using Nonlinear Mixed Effects Modeling with an integrated parent-metabolite PK model (PK-2). Surrogate effect was measured by inhibition of serotonin-induced bradycardia. Protein binding was assayed via ultrafiltration and all quantification was performed via liquid chromatography-electrospray ionization-mass spectrometry. RESULTS: L6-OH showed elevated plasma and renal clearances, and volume of distribution (PK-1). The in vivo potency (PD) of L6-OH was high (EC(50) = 0.098 ng mL(-1) and EC(50unbound) = 0.040 ng mL(-1)). Total clearance for L (PK-2) in the presence of generated L6-OH (CL(L) = CL(-->L6-OH) + CL(n)) was 0.0139 L min(-1). Most of this clearance was L6-OH formation (F(c) = 99.6%), but only an 8.6% fraction of L6-OH was released into the bloodstream. The remainder undergoes biliar and fecal elimination. The parameters estimated from PK-2 were used to predict concentrations of L6-OH (Cp(L6)) generated after a lerisetron therapeutic dose (10 microg kg(-1)) in the rat. These concentrations are needed for the PD model and are below the quantification limit. Cp(L6max) was less than the EC(50) of L6-OH. CONCLUSIONS: We conclude that after lerisetron administration, L6-OH is extensively formed in the rat but it is quickly eliminated; therefore, besides being equipotent with the parent drug, the L6-OH metabolite does not influence the effect of lerisetron.