A population pharmacokinetics analysis was performed after intravenous ganciclovir and oral valganciclovir in solid organ transplant patients with cytomegalovirus. Patients received ganciclovir at 5 mg/kg of body weight (5 days) and then 900 mg of valganciclovir (16 days), both twice daily with dose adjustment for renal function. A total of 382 serum concentrations from days 5 and 15 were analyzed with NONMEM VI. Renal function given by creatinine clearance (CL_CR) was the most influential covariate in CL. The final pharmacokinetic parameters were as follows: ganciclovir clearance (CL) was 7.49·(CL_CR/57) liter/h (57 was the mean population value of CL_CR); the central and peripheral distribution volumes were 31.9 liters and 32.0 liters, respectively; intercompartmental clearance was 10.2 liter/h; the first-order absorption rate constant was 0.895 h⁻¹; bioavailability was 0.825; and lag time was 0.382 h. The CL_CRwas the best predictor of CL, making dose adjustment by this covariate important to achieve the most efficacious ganciclovir exposure.

The goal of this study was to establish the population pharmacokinetics (PK) of high-dose methotrexate (HD-MTX) treatment in children with osteosarcoma and to explore the influence of patient covariates and between-occasion variability on drug disposition. Patient covariates and concentration-time data were collected. PK data analysis from 209 HD-MTX cycles from 14 patients was performed using the population approach (NONMEM V). Internal and external validations were performed to confirm the model. PK of methotrexate was best described by a 2-compartment open PK model with first-order elimination from the central compartment. Between-subject variability (BSV) was included in total plasma clearance (CL) and in central compartment distribution volume (V1) [coefficient of variation (CV) 11.9% and 8.9%, respectively]. The CV of BSV in the residual error was 25.5%. Between-occasion variability was only retained for CL (CV 8.2%). RE consisted of a proportional error of 41.6%. Age and body weight in CL and body weight in V1 were identified as the appropriate covariates. The final estimates of total CL and V1 were given by the equations CL = 88.5.(AGE/15) + 27.4 x (WGT/50) L/d and V1 = 11.0 + 5.6 x (WGT/50) L, respectively. Internal validation results showed that the 95% confidence interval covered all the observed MTX concentrations. Mean bias and precision of the individual predicted concentrations, calculated in a validation dataset, resulted in -1.36% and 19.71%, respectively. A population PK model was developed for HD-MTX in children with osteosarcoma. Validation studies confirmed the suitability of the model for further dose individualization by means of a Bayesian approach.

Introduction: Tacrolimus is the backbone immunosuppressant after solid organ transplantation. Tacrolimus has a narrow therapeutic window with large intra- and inter-patient pharmacokinetic variability leading to frequent over- and under-immunosuppression. While routine therapeutic drug monitoring (TDM) remains the standard of care, tacrolimus pharmacokinetic variability may be influenced by circadian rhythms. Our aim was to analyze tacrolimus pharmacokinetic/pharmacodynamic profiles on circadian rhythms comparing morning and night doses of a twice-daily tacrolimus formulation.Methods: This is a post-hoc analysis from a clinical trial to study the area under curve (AUC) and the area under effect (AUE) profiles of calcineurin inhibition after tacrolimus administration in twenty-five renal transplant patients. Over a period of 24 h, an intensive sampling (0, 0.5, 1, 1.5, 2, 3, 4, 6, 8, 12, 12.5, 13, 13.5, 14, 15, 20, and 24 h) was carried out. Whole blood and intracellular tacrolimus concentrations and calcineurin activity were measured by UHPLC-MS/MS.Results: Whole blood and intracellular AUC_12–24 h and C_max achieved after tacrolimus night dose was significantly lower than after morning dose administration (AUC_0–12 h) (p < 0.001 for both compartments). AUE_0–12 h and AUE_12–24 h were not statistically different after morning and night doses. Total tacrolimus daily exposure (AUC_0–24 h), in whole blood and intracellular compartments, was over-estimated when assessed by doubling the morning AUC_0–12 h data.Conclusion: The lower whole blood and intracellular tacrolimus concentrations after night dose might be influenced by a distinct circadian clock. This significantly lower tacrolimus exposure after night dose was not translated into a significant reduction of the pharmacodynamic effect. Our study may provide conceptual bases for better understanding the TDM of twice-daily tacrolimus formulation.