scholarly journals Application of Size and Maturation Functions to Population Pharmacokinetic Modeling of Pediatric Patients

Pharmaceutics ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 259 ◽  
Author(s):  
Hyun-moon Back ◽  
Jong Bong Lee ◽  
Nayoung Han ◽  
Sungwoo Goo ◽  
Eben Jung ◽  
...  
Keyword(s):  
Clinical Data ◽  
Goodness Of Fit ◽  
Pediatric Patients ◽  
Visual Predictive Check ◽  
Modeling Method ◽  
Population Pharmacokinetic ◽  
Mixed Effect ◽  
Population Pharmacokinetic Modeling ◽  
Nonlinear Mixed Effect ◽  
One Year

Traditionally, dosage for pediatric patients has been optimized using simple weight-scaled methods, but these methods do not always meet the requirements of children. To overcome this discrepancy, population pharmacokinetic (PK) modeling of size and maturation functions has been proposed. The main objective of the present study was to evaluate a new modeling method for pediatric patients using clinical data from three different clinical studies. To develop the PK models, a nonlinear mixed effect modeling method was employed, and to explore PK differences in pediatric patients, size with allometric and maturation with Michaelis–Menten type functions were evaluated. Goodness of fit plots, visual predictive check and bootstrap were used for model evaluation. Single application of size scaling to PK parameters was statistically significant for the over one year old group. On the other hand, simultaneous use of size and maturation functions was statistically significant for infants younger than one year old. In conclusion, population PK modeling for pediatric patients was successfully performed using clinical data. Size and maturation functions were applied according to established criteria, and single use of size function was applicable for over one year ages, while size and maturation functions were more effective for PK analysis of neonates and infants.

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 Population Pharmacokinetic/Pharmacogenetic Model for Optimization of Efavirenz Therapy in Caucasian HIV-Infected Patients

2011 ◽  
Vol 55 (11) ◽  
pp. 5314-5324 ◽  
Author(s):  
Almudena Sánchez ◽  
Salvador Cabrera ◽  
Dolores Santos ◽  
M. Paz Valverde ◽  
Aurelio Fuertes ◽  
...  
Keyword(s):  
High Performance ◽  
Plasma Concentrations ◽  
Compartment Model ◽  
Population Pharmacokinetic ◽  
Nucleotide Polymorphisms ◽  
Mixed Effect ◽  
Factors Affecting ◽  
Nonlinear Mixed Effect ◽  
Study Population ◽  
Major Factors

ABSTRACTDespite extensive clinical experience with efavirenz (EFV), unpredictable interindividual variabilities in efficacy and toxicity remain important limitations associated with the use of this antiretroviral. The purpose of this study was to determine the factors affecting EFV pharmacokinetics and to develop a pharmacokinetic/pharmacogenetic (PK/PG) model in a Caucasian population of HIV-infected patients. In total, 869 EFV plasma concentrations from 128 HIV-infected patients treated with EFV were quantitatively assessed using a validated high-performance liquid chromatography technique. All patients were genotyped for 90 single nucleotide polymorphisms (SNPs) in genes coding for proteins involved in the metabolism and transport of EFV, using a MassArray platform provided by Sequenom. The influence of these polymorphisms on EFV pharmacokinetics and the effects of demographic, clinical, biochemical, lifestyle, and concurrent drug covariates were evaluated. Plasma concentrations were fitted by a one-compartment model, with first-order absorption and elimination using nonlinear mixed-effect modeling (NONMEM program). The CYP2B6*6 allele, multidrug resistance-associated protein 4 (MRP4) 1497C→T, and gamma-glutamyltranspeptidase (GGT) were identified as major factors influencing the apparent EFV oral clearance (CL/F), reducing the initial interindividual variability by 54.8%, according to the model CL/F = (12.2 − 0.00279·GGT)·0.602CYP2B6*6 [G/T]·0.354CYP2B6*6 [T/T]·0.793MRP4 1497C→T, where CYP2B6*6 [G/T], CYP2B6*6 [T/T], and MRP4 1497C→T take values of 0 or 1 to indicate the absence or presence of polymorphisms. The detailed genetic analysis conducted in this study identified two of 90 SNPs that significantly impacted CL/F, which might indicate that the remaining SNPs analyzed do not influence this PK parameter, at least in Caucasian populations with characteristics similar to those of our study population.

scholarly journals Prediction of steady-state plasma concentrations of olanzapine in Chinese Han in patients based on a retrospective population pharmacokinetic model

2021 ◽  
Vol 20 (11) ◽  
pp. 2433-2441
Author(s):  
Xiaoyue Wang ◽  
Yong Han ◽  
Hong Zhou ◽  
Bin Cao ◽  
Miaomiao Zhu ◽  
...  
Keyword(s):  
Steady State ◽  
Smoking Status ◽  
Mental Health Center ◽  
Plasma Concentrations ◽  
Visual Predictive Check ◽  
Apparent Volume ◽  
Population Pharmacokinetic ◽  
Chinese Han ◽  
Mixed Effect ◽  
State Plasma

Purpose: To develop robust methods of establishing a population pharmacokinetics (Pop-PK) model of olanzapine, using existing hospital in-patient information, in order to predict the steady-state plasma concentration of olanzapine tablets in Chinese Han inpatients, thus providing guidance for individualized therapy for mental disorders.Methods: A retrospective study analyzing and predicting the steady-state plasma olanzapineconcentration was performed using nonlinear mixed-effect modeling (Phoenix® NLME8). The effects of ten potential covariates, including age, gender, Body Mass Index, fasting lipid, family history, alcohol and smoking status in 107 Chinese Han patients with steady-state plasma olanzapine concentration were collected from the hospital information system (HIS) in Wuhan Mental Health Center from Feb 2017 to Jul 2019.Results: The final model was validated using bootstrap and visual predictive check (VPC) and was found to fit the one-compartment mixed error model. Smoking status was found to be the only factor affecting olanzapine tablets clearance. The standard Pop-PK parameters apparent volume of distribution (VL/F) and clearance (CL/F) were 223 L and 12.4 Lꞏh-1, respectively.Conclusion: The Pop-PK model for olanzapine established with the data from HIS is effective inpredicting the plasma olanzapine tablets concentration of individual Chinese in-patients. This Pop-PK model approach can now be adapted to optimize other antipsychotic drugs.

scholarly journals Dose Tailoring of Vancomycin Through Population Pharmacokinetic Modeling Among Surgical Patients in Pakistan

2021 ◽  
Vol 12 ◽  
Author(s):  
Muhammad Muaaz Munir ◽  
Huma Rasheed ◽  
Muhammad Imran Khokhar ◽  
Rizwan Rasul Khan ◽  
Hafiz Asad Saeed ◽  
...  
Keyword(s):  
Body Weight ◽  
Plasma Concentration ◽  
Goodness Of Fit ◽  
Volume Of Distribution ◽  
Surgical Patients ◽  
Pharmacokinetic Parameters ◽  
Population Pharmacokinetic ◽  
Time Data ◽  
Concentration Data ◽  
Population Pharmacokinetic Modeling

Background: Vancomycin is a narrow therapeutic agent, and it is necessary to optimize the dose to achieve safe therapeutic outcomes. The purpose of this study was to identify the significant covariates for vancomycin clearance and to optimize the dose among surgical patients in Pakistan.Methods: Plasma concentration data of 176 samples collected from 58 surgical patients treated with vancomycin were used in this study. A population pharmacokinetic model was developed on NONMEM® using plasma concentration–time data. The effect of all available covariates was evaluated on the pharmacokinetic parameters of vancomycin by stepwise covariate modeling. The final model was evaluated using bootstrap, goodness-of-fit plots, and visual predictive checks.Results: The pharmacokinetics of vancomycin followed a one-compartment model with first-order elimination. The vancomycin clearance (CL) and volume of distribution (Vd) were 2.45 L/h and 22.6 l, respectively. Vancomycin CL was influenced by creatinine clearance (CRCL) and body weight of the patients; however, no covariate was significant for its effect on the volume of distribution. Dose tailoring was performed by simulating dosage regimens at a steady state based on the CRCL of the patients. The tailored doses were 400, 600, 800, and 1,000 mg for patients with a CRCL of 20, 60, 100, and 140 ml/min, respectively.Conclusion: Vancomycin CL is influenced by CRCL and body weight of the patient. This model can be helpful for the dose tailoring of vancomycin based on renal status in Pakistani patients.

scholarly journals Population pharmacokinetics and dose optimization of vancomycin in neonates

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Soon Min Lee ◽  
Seungwon Yang ◽  
Soyoung Kang ◽  
Min Jung Chang
Keyword(s):  
Pharmacokinetic Analysis ◽  
Dose Optimization ◽  
Pharmacokinetic Parameters ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Optimal Dosage ◽  
Mixed Effect ◽  
Final Model ◽  
Population Pharmacokinetic Modeling ◽  
First Order

AbstractThe pharmacokinetics of vancomycin vary among neonates, and we aimed to conduct population pharmacokinetic analysis to determine the optimal dosage of vancomycin in Korean neonates. From a retrospective chart review, neonates treated with vancomycin from 2008 to 2017 in a neonatal intensive care unit (NICU) were included. Vancomycin concentrations were collected based on therapeutic drug monitoring, and other patient characteristics were gathered through electronic medical records. We applied nonlinear mixed-effect modeling to build the population pharmacokinetic model. One- and two-compartment models with first-order elimination were evaluated as potential structural pharmacokinetic models. Allometric and isometric scaling was applied to standardize pharmacokinetic parameters for clearance and volume of distribution, respectively, using fixed powers (0.75 and 1, respectively, for clearance and volume). The predictive performance of the final model was developed, and dosing strategies were explored using Monte Carlo simulations with AUC0–24 targets 400–600. The patient cohort included 207 neonates, and 900 vancomycin concentrations were analyzed. Only 37.4% of the analyzed concentrations were within trough concentrations 5–15 µg/mL. A one-compartment model with first-order elimination best described the vancomycin pharmacokinetics in neonates. Postmenstrual age (PMA) and creatinine clearance (CLcr) affected the clearance of vancomycin, and model evaluation confirmed the robustness of the final model. Population pharmacokinetic modeling and dose optimization of vancomycin in Korean neonates showed that vancomycin clearance was related to PMA and CLcr, as well as body weight. A higher dosage regimen than the typical recommendation is suggested.

scholarly journals Gentamicin Population Pharmacokinetics in Pediatric Patients—A Prospective Study with Data Analysis Using the saemix Package in R

Pharmaceutics ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1596
Author(s):  
Paolo Paioni ◽  
Vera F. Jäggi ◽  
Romy Tilen ◽  
Michelle Seiler ◽  
Philipp Baumann ◽  
...  
Keyword(s):  
Prospective Study ◽  
Plasma Levels ◽  
Pediatric Patients ◽  
Plasma Concentrations ◽  
Compartment Model ◽  
R Package ◽  
Pharmacokinetic Modeling ◽  
Therapeutic Window ◽  
Population Pharmacokinetic ◽  
Population Pharmacokinetic Modeling

The aminoglycoside gentamicin is used for the empirical treatment of pediatric infections. It has a narrow therapeutic window. In this prospective study at University Children’s Hospital Zurich, Switzerland, we aimed to characterize the pharmacokinetics of gentamicin in pediatric patients and predict plasma concentrations at typical recommended doses. We recruited 109 patients aged from 1 day to 14 years, receiving gentamicin (7.5 mg/kg at age ≥ 7 d or 5 mg/kg). Plasma levels were determined 30 min, 4 h and 24 h after the infusion was stopped and then transferred, together with patient data, to the secure BioMedIT node Leonhard Med. Population pharmacokinetic modeling was performed with the open-source R package saemix on the SwissPKcdw platform in Leonhard Med. Data followed a two-compartment model. Bodyweight, plasma creatinine and urea were identified as covariates for clearance, with bodyweight as a covariate for central and peripheral volumes of distribution. Simulations with 7.5 mg/kg revealed a 95% CI of 13.0–21.2 mg/L plasma concentration at 30 min after the stopping of a 30-min infusion. At 24 h, 95% of simulated plasma levels were < 1.8 mg/L. Our study revealed that the recommended dosing is appropriate. It showed that population pharmacokinetic modeling using R provides high flexibility in a secure environment.

Sign in / Sign up

Export Citation Format

Share Document