External Evaluation of Population Pharmacokinetic Models of Piperacillin in Preterm and Term Patients from Neonatal Intensive Care.

BACKGROUND AND OBJECTIVES: Piperacillin/tazobactam is extensively used off-label to treat late-onset neonatal sepsis, but safety and pharmacokinetic data in this population are limited. Additionally, the organic immaturity of the newborns contributes to a high piperacillin pharmacokinetic variability. This affects the clinical efficacy of the antibiotic treatment and increases the probability of developing drug resistance. This study aimed to evaluate the predictive performance of reported piperacillin population pharmacokinetic models for their application in a model-informed precision dosing strategy in preterm and term Mexican neonatal intensive care patients. METHODS: Published population pharmacokinetic models for piperacillin which included neonates in their study population were identified. From the reference models, structured models, population pharmacokinetic parameters, and interindividual and residual variability data were extracted to be replicated in pharmacokinetic software (NONMEM® version 7.4). For the clinical study, a sampling schedule was designed, and 2-3 blood samples of 250 µL were taken from neonates who met the inclusion criteria. Piperacillin plasma concentrations were determined by liquid chromatography/tandem mass spectrometry. The clinical treatment data were collected, and piperacillin plasma concentrations were estimated using reference pharmacokinetic models for an a priori or Bayesian approach. Statistical methods were used in terms of bias and precision to evaluate the differences between observed and estimated neonatal piperacillin plasma concentrations with the different approaches and to identify the pharmacokinetic model that best fits the neonatal data. RESULTS: A total of 70 plasma samples were collected from 25 neonatal patients, of which 15 were preterm neonates. The overall median value (range) postnatal age, gestational age, body weight, and serum creatinine at the sampling collecting day were 12 (3-26) days, 34.2 (26-41.1) weeks, 1.78 (0.08-3.90) Kg, 0.47 (0.20-0.90) mg/dL, respectively. Three population pharmacokinetic models for piperacillin in infants up to 2 months were identified, and their predictive performance in neonatal data was evaluated. No pharmacokinetic model was suitable for our population using an a priori approach. The model published by Cohen-Wolkowiez et al. in 2014 with a Bayesian approach showed the best performance of the pharmacokinetic models evaluated in our neonatal data. The procedure requires two blood samples (predose and postdose), and, when applied, it predicted 66.6% of the observations with a relative median absolute predicted error of less than 30%. CONCLUSIONS: The population pharmacokinetic model developed by Cohen-Wolkowiez et al. in 2014 demonstrated superior performance in predicting the plasma concentration of piperacillin in preterm and term Mexican neonatal intensive care patients. The Bayesian approach, including two different piperacillin plasma concentrations, was clinically acceptable regarding bias and precision. Its application for model-informed precision dosing can be an option to optimize the piperacillin dosage in our population.

Methotrexate Triglutamate as a Determinant of Clinical Response in Mexican Patients With Rheumatoid Arthritis: Pharmacokinetics and Dose Recommendation.

Methotrexate is the gold standard treatment in rheumatoid arthritis. Once absorbed, it is internalized in cells, where glutamate residues are added to produce polyglutamated forms, which are responsible for the effect of methotrexate. The aim of the current study is to determine the relationship between methotrexate triglutamate concentrations and the clinical evolution in rheumatoid arthritis patients, as well as to characterize the variability in both features to propose strategies for low-dose methotrexate optimization. The quantification of methotrexate triglutamate concentration in red blood cells was performed through ultra-performance liquid chromatography coupled with mass spectrometry. Polymorphisms of genes involved in the formation of polyglutamates were determined by real-time polymerase chain reaction. A multivariate regression was performed to determine the covariates involved in the variability of methotrexate triglutamate concentrations and a population pharmacokinetics model was developed through nonlinear mixed-effects modeling. Disease activity score changed according to methotrexate triglutamate concentrations; patients with good response to treatment had higher concentrations than moderate or nonresponding patients. The methotrexate triglutamate concentrations were related to time under treatment, dose, red blood cells, and body mass index. A 1-compartment open model was selected to estimate the pharmacokinetic parameters; the typical total clearance (L/day) was determined as 1.45 * (body mass index/28 kg/m2 ) * (red blood cells/4.6 × 106 cells/µL) and the volume of distribution was 52.4 L, with an absorption rate of 0.0346/day and a fraction metabolized of 1.03%. Through the application of the model, the initial dose of methotrexate is proposed on the basis of stochastic simulations and considering methotrexate triglutamate concentrations found in responders patients.

Population Pharmacokinetics of Amikacin Administered Once Daily in Patients with Different Renal Functions.

The aim of this work was to evaluate the pharmacokinetics of amikacin in Mexican patients with different renal functions receiving once-daily dosing regimens and the influence of clinical and demographical covariates that may influence the optimization of this antibiotic. A prospective study was performed in a total of 63 patients with at least one determination of amikacin plasma concentration. Population pharmacokinetic (PK) parameters were estimated by nonlinear mixed-effects modeling; validations were performed for dosing recommendation purposes based on PK/pharmacodynamic simulations. The concentration-versus-time data were best described by a one-compartment open model with proportional interindividual variability associated with amikacin clearance (CL) and volume of distribution (V); residual error followed a homoscedastic trend. Creatinine clearance (CLCR) and ideal body weight (IBW) demonstrated significant influence on amikacin CL and V, respectively. The final model [CL (liters/h) = 7.1 × (CLCR/130)0.84 and V (liters) = 20.3 × (IBW/68)2.9] showed a mean prediction error of 0.11 mg/liter (95% confidence interval, -3.34, 3.55) in the validation performed in a different group of patients with similar characteristics. There is a wide variability in amikacin PK parameters in Mexican patients. This leads to inadequate dosing regimens, especially in patients with augmented renal clearance (CLCR of >130 ml/min). Optimization based on the final population PK model in Mexican patients may be useful, since reliability and clinical applicability have been demonstrated in this study.