scholarly journals O11 Characterising the pharmacokinetics of phenobarbitone in neonates to facilitate future individualised dosing

2019 ◽  
Vol 104 (6) ◽  
pp. e5.1-e5 ◽  
Author(s):  
A Williams ◽  
T Donovan ◽  
B Charles ◽  
C Staatz
Keyword(s):  
Oral Bioavailability ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Volume Of Distribution ◽  
Absolute Bioavailability ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
List Type ◽  
Young Infants ◽  
Intravenous And Oral Administration

BackgroundPhenobarbitone is commonly used as a first-line drug in the treatment of neonatal seizures. Previous studies, with small subject numbers, have identified covariates that may influence the pharmacokinetics of phenobarbitone but results have been inconsistent. In particular, oral bioavailability is poorly described with doses reported as being identical for intravenous and oral administration, however, 2 recent studies have reported oral bioavailability of 49% and 59% respectively.1,2MethodsA population pharmacokinetic model was built based on routine therapeutic drug monitoring data from 112 infants at the Royal Brisbane and Women’s Hospital Neonatal Intensive Care Unit. Population modelling was performed using NONMEM 7.3 and PsN 4.7 with assistance from R studio and the packages Xpose and VPC. Body weight with allometric scaling on Clearance (CL) and Volume of Distribution (V) were included a priori in the structural model. Covariates tested included age (post-menstrual, gestational and post-natal), Apgar scores, concomitant phenytoin treatment, infection and method of nutrition.ResultsA one-compartment model provided an adequate fit to the data. Typical clearance increased with patient post-natal age (PNA) and was best modelled using the equation CL = 5.1 *WT0.75 * (PNA/6.25)0.43 (mL/h) were weight is in kg, PNA in days and 6.25 is the median post-natal age. Volume of distribution (V) was best modelled using the equation V = 799 * WT1.0 (mL). Oral bioavailability (F) was 85%. Between-subject variability was 25% and 30% respectively for CL and V.ConclusionThis study describes the largest population pharmacokinetic model of phenobarbitone developed to date with estimates of CL and V similar to previously published models. Estimated F is higher than previously reported but still lower than the implied F of 100% in most recommended dosing regimens. The model could be used to assist with future individualisation of dosing in this cohort.ReferencesMarsot A, et al. Pharmacokinetics and absolute bioavailability of phenobarbital in neonates and young infants, a population pharmacokinetic modelling approach. Fundam Clin Pharmacol 2014;28(4):465–71.Voller S, et al. Model-based clinical dose optimization for phenobarbital in neonates: An illustration of the importance of data sharing and external validation. Eur J Pharm Sci 2017;109s:S90–S97.Disclosure(s)Nothing to disclose

scholarly journals Influence of Mechanical Ventilation on the Pharmacokinetics of Vancomycin Administered by Continuous Infusion in Critically Ill Patients

2017 ◽  
Vol 61 (12) ◽  
Author(s):  
Susanna Edith Medellín-Garibay ◽  
Silvia Romano-Moreno ◽  
Pilar Tejedor-Prado ◽  
Noelia Rubio-Álvaro ◽  
Aida Rueda-Naharro ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Creatinine Clearance ◽  
Continuous Infusion ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Volume Of Distribution ◽  
Stochastic Simulations ◽  
Population Pharmacokinetic

ABSTRACT Pathophysiological changes involved in drug disposition in critically ill patients should be considered in order to optimize the dosing of vancomycin administered by continuous infusion, and certain strategies must be applied to reach therapeutic targets on the first day of treatment. The aim of this study was to develop a population pharmacokinetic model of vancomycin to determine clinical covariates, including mechanical ventilation, that influence the wide variability of this antimicrobial. Plasma vancomycin concentrations from 54 critically ill patients were analyzed simultaneously by a population pharmacokinetic approach. A nomogram for dosing recommendations was developed and was internally evaluated through stochastic simulations. The plasma vancomycin concentration-versus-time data were best described by a one-compartment open model with exponential interindividual variability associated with vancomycin clearance and the volume of distribution. Residual error followed a homoscedastic trend. Creatinine clearance and body weight significantly dropped the objective function value, showing their influence on vancomycin clearance and the volume of distribution, respectively. Characterization based on the presence of mechanical ventilation demonstrated a 20% decrease in vancomycin clearance. External validation (n = 18) was performed to evaluate the predictive ability of the model; median bias and precision values were 0.7 mg/liter (95% confidence interval [CI], −0.4, 1.7) and 5.9 mg/liter (95% CI, 5.4, 6.4), respectively. A population pharmacokinetic model was developed for the administration of vancomycin by continuous infusion to critically ill patients, demonstrating the influence of creatinine clearance and mechanical ventilation on vancomycin clearance, as well as the implications for targeting dosing rates to reach the therapeutic range (20 to 30 mg/liter).

scholarly journals Pharmacokinetic Modeling and Optimal Sampling Strategies for Therapeutic Drug Monitoring of Rifampin in Patients with Tuberculosis

2015 ◽  
Vol 59 (8) ◽  
pp. 4907-4913 ◽  
Author(s):  
Marieke G. G. Sturkenboom ◽  
Leonie W. Mulder ◽  
Arthur de Jager ◽  
Richard van Altena ◽  
Rob E. Aarnoutse ◽  
...  
Keyword(s):  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Mean Squared Error ◽  
Geometric Mean ◽  
Plasma Concentrations ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Wide Range

ABSTRACTRifampin, together with isoniazid, has been the backbone of the current first-line treatment of tuberculosis (TB). The ratio of the area under the concentration-time curve from 0 to 24 h (AUC0–24) to the MIC is the best predictive pharmacokinetic-pharmacodynamic parameter for determinations of efficacy. The objective of this study was to develop an optimal sampling procedure based on population pharmacokinetics to predict AUC0–24values. Patients received rifampin orally once daily as part of their anti-TB treatment. A one-compartmental pharmacokinetic population model with first-order absorption and lag time was developed using observed rifampin plasma concentrations from 55 patients. The population pharmacokinetic model was developed using an iterative two-stage Bayesian procedure and was cross-validated. Optimal sampling strategies were calculated using Monte Carlo simulation (n= 1,000). The geometric mean AUC0–24value was 41.5 (range, 13.5 to 117) mg · h/liter. The median time to maximum concentration of drug in serum (Tmax) was 2.2 h, ranging from 0.4 to 5.7 h. This wide range indicates that obtaining a concentration level at 2 h (C2) would not capture the peak concentration in a large proportion of the population. Optimal sampling using concentrations at 1, 3, and 8 h postdosing was considered clinically suitable with anr2value of 0.96, a root mean squared error value of 13.2%, and a prediction bias value of −0.4%. This study showed that the rifampin AUC0–24in TB patients can be predicted with acceptable accuracy and precision using the developed population pharmacokinetic model with optimal sampling at time points 1, 3, and 8 h.

scholarly journals Mining Small Routine Clinical Data: A Population Pharmacokinetic Model and Optimal Sampling Times of Capecitabine and its Metabolites

2019 ◽  
Vol 22 ◽  
pp. 112-121 ◽  
Author(s):  
Esther Oyaga-Iriarte ◽  
Asier Insausti ◽  
Lorea Bueno ◽  
Onintza Sayar ◽  
Azucena Aldaz
Keyword(s):  
Clinical Practice ◽  
Clinical Data ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Visual Predictive Check ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Optimal Sampling ◽  
Multicompartmental Model ◽  
Sampling Times

Purpose: The present study was performed to demonstrate that small amounts of routine clinical data allow to generate valuable knowledge. Concretely, the aims of this research were to build a joint population pharmacokinetic model for capecitabine and three of its metabolites (5-DFUR, 5-FU and 5-FUH2) and to determine optimal sampling times for therapeutic drug monitoring. Methods: We used data of 7 treatment cycles of capecitabine in patients with metastatic colorectal cancer. The population pharmacokinetic model was built as a multicompartmental model using NONMEM and was internally validated by visual predictive check. Optimal sampling times were estimated using PFIM 4.0 following D-optimality criterion. Results: The final model was a multicompartmental model which represented the sequential transformations from capecitabine to its metabolites 5-DFUR, 5-FU and 5-FUH2 and was correctly validated. The optimal sampling times were 0.546, 0.892, 1.562, 4.736 and 8 hours after the administration of the drug. For its correct implementation in clinical practice, the values were rounded to 0.5, 1, 1.5, 5 and 8 hours after the administration of the drug. Conclusions: Capecitabine, 5-DFUR, 5-FU and 5-FUH2 can be correctly described by the joint multicompartmental model presented in this work. The aforementioned times are optimal to maximize the information of samples. Useful knowledge can be obtained for clinical practice from small databases.

scholarly journals Optimization of Dosage Regimen of Meropenem in Patients Undergoing Venoarterial Extracorporeal Membrane Oxygenation: A Prospective Cohort Study

2021 ◽  
Author(s):  
Soyoung Kang ◽  
Seungwon Yang ◽  
Jongsung Hahn ◽  
June Young Jang ◽  
Kyoung Lok Min ◽  
...  
Keyword(s):  
Cohort Study ◽  
Dosage Regimen ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Volume Of Distribution ◽  
Population Pharmacokinetic ◽  
Optimal Dosage ◽  
Optimal Dosage Regimen ◽  
Venoarterial Extracorporeal Membrane Oxygenation ◽  
Va Ecmo

Abstract BackgroundPatients receiving venoarterial extracorporeal membrane oxygenation (VA ECMO) therapy often require antibiotics to prevent and treat infections. Our objective was to determine an optimal dosage regimen of meropenem in patients receiving VA ECMO by developing a population pharmacokinetic model.MethodsThis was a prospective cohort study. Blood samples were collected during ECMO (ECMO-ON) and after ECMO (ECMO-OFF). The population pharmacokinetic model was developed using nonlinear mixed-effects modelling. A Monte Carlo simulation was used (n=10,000) to assess the probability of target attainment.ResultsThirteen adult patients on ECMO receiving meropenem were included. Meropenem pharmacokinetics was best fitted by a two-compartment model. Covariate analysis indicated that continuous renal replacement therapy (CRRT) was negatively correlated with clearance (CL). The final pharmacokinetic model was: CL (L/h) = 3.79 × 0.44CRRT; where use of CRRT = 1, no CRRT = 0, central volume of distribution (L) = 2.4, peripheral volume of distribution (L) = 8.56, and intercompartmental clearance (L/h) = 21.3. According to the simulation results, 1–2 g q8h intravenous administration over 20 min was sufficient in patients without CRRT for both susceptible (minimum inhibitory concentration (MIC) = 2 mg/L) and resistant (MIC = 8 mg/L) pathogens, regardless of ECMO use (40% fT>MIC target). However, if more aggressive treatment is needed (100% fT>MIC target), dose increment or extended infusion is recommended.ConclusionsWe established a population pharmacokinetic model for meropenem in patients receiving VA ECMO and suggested an optimal dosage regimen. These results should improve treatment success and survival in VA ECMO patients. Clinicaltrials.gov registration # NCT02581280

scholarly journals A population pharmacokinetic model for individualised dosage regimens of vancomycin in Chinese neonates and young infants

Oncotarget ◽  
2017 ◽  
Vol 8 (62) ◽  
pp. 105211-105221 ◽  
Author(s):  
Lin Song ◽  
Cui-Yao He ◽  
Nan-Ge Yin ◽  
Fang Liu ◽  
Yun-Tao Jia ◽  
...  
Keyword(s):  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Population Pharmacokinetic ◽  
Young Infants ◽  
Dosage Regimens
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