scholarly journals Development of a population pharmacokinetic model and optimal sampling strategies for intravenous ciprofloxacin.

1993 ◽  
Vol 37 (5) ◽  
pp. 1065-1072 ◽  
Author(s):  
A Forrest ◽  
C H Ballow ◽  
D E Nix ◽  
M C Birmingham ◽  
J J Schentag
Keyword(s):  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Population Pharmacokinetic ◽  
Optimal Sampling ◽  
Sampling Strategies

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 Optimal sampling strategies for darunavir and external validation of the underlying population pharmacokinetic model

2020 ◽  
Author(s):  
Gabriel Stillemans ◽  
Leila Belkhir ◽  
Bernard Vandercam ◽  
Anne Vincent ◽  
Vincent Haufroid ◽  
...  
Keyword(s):  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
External Validation ◽  
Diagnostic Methods ◽  
Validation Dataset ◽  
Pharmacokinetic Parameters ◽  
Population Pharmacokinetic ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Validation Set

Abstract Purpose A variety of diagnostic methods are available to validate the performance of population pharmacokinetic models. Internal validation, which applies these methods to the model building dataset and to additional data generated through Monte Carlo simulations, is often sufficient, but external validation, which requires a new dataset, is considered a more rigorous approach, especially if the model is to be used for predictive purposes. Our first objective was to validate a previously published population pharmacokinetic model of darunavir, an HIV protease inhibitor boosted with ritonavir or cobicistat. Our second objective was to use this model to derive optimal sampling strategies that maximize the amount of information collected with as few pharmacokinetic samples as possible. Methods A validation dataset comprising 164 sparsely sampled individuals using ritonavir-boosted darunavir was used for validation. Standard plots of predictions and residuals, NPDE, visual predictive check, and bootstrapping were applied to both the validation set and the combined learning/validation set in NONMEM to assess model performance. D-optimal designs for darunavir were then calculated in PopED and further evaluated in NONMEM through simulations. Results External validation confirmed model robustness and accuracy in most scenarios but also highlighted several limitations. The best one-, two-, and three-point sampling strategies were determined to be pre-dose (0 h); 0 and 4 h; and 1, 4, and 19 h, respectively. A combination of samples at 0, 1, and 4 h was comparable to the optimal three-point strategy. These could be used to reliably estimate individual pharmacokinetic parameters, although with fewer samples, precision decreased and the number of outliers increased significantly. Conclusions Optimal sampling strategies derived from this model could be used in clinical practice to enhance therapeutic drug monitoring or to conduct additional pharmacokinetic studies.

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 Model for Intravenous ASN100 in Healthy Subjects

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S529-S529
Author(s):  
Scott A Van Wart ◽  
Christopher Stevens ◽  
Zoltan Magyarics ◽  
Steven A Luperchio ◽  
Paul G Ambrose
Keyword(s):  
Healthy Subjects ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Population Pharmacokinetic

scholarly journals Pharmacokinetics and Pharmacogenetics of Cyclophosphamide in a Neonate and Infant Childhood Cancer Patient Population

2021 ◽  
Vol 14 (3) ◽  
pp. 272
Author(s):  
Shelby Barnett ◽  
Julie Errington ◽  
Julieann Sludden ◽  
David Jamieson ◽  
Vianney Poinsignon ◽  
...  
Keyword(s):  
Cancer Patient ◽  
Childhood Cancer ◽  
Patient Population ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Drug Clearance ◽  
Current Data ◽  
Population Pharmacokinetic ◽  
Older Children ◽  
Patient Groups

Infants and young children represent an important but much understudied childhood cancer patient population. The pharmacokinetics and pharmacogenetics of the widely used anticancer prodrug cyclophosphamide were investigated in children <2 years of age. Concentrations of cyclophosphamide and selected metabolites were determined in patients administered cyclophosphamide at doses ranging from 100–1500 mg/m2 (5–75 mg/kg), with various infusion times as determined by the standard treatment regimen that each patient was receiving. Polymorphisms in genes including CYP2B6 and CYP2C19 were investigated. Data generated for cyclophosphamide were analysed using a previously published population pharmacokinetic model. Cyclophosphamide pharmacokinetics was assessed in 111 samples obtained from 25 patients ranging from 4–23 months of age. The average cyclophosphamide clearance for the patients was 46.6 mL/min/m2 (ranging from 9.4–153 mL/min/m2), with marked inter-patient variability observed (CV 41%). No significant differences in cyclophosphamide clearance or exposure (AUC) were observed between patient groups as separated by age or body weight. However, marked differences in drug clearance and metabolism were noted between the current data in children <2 years of age and recently published results from a comparable study conducted by our group in older children, which reported significantly lower cyclophosphamide clearance values and metabolite exposures using the same population pharmacokinetic model for analysis. Whilst this study demonstrates no significant differences in cyclophosphamide clearance in patients <2 years, it highlights large differences in dosing protocols across tumour types. Furthermore, the study suggests marked differences in cyclophosphamide clearance in children less than two years of age as compared to older patients.

scholarly journals Novel Population Pharmacokinetic Model for Linezolid in Critically Ill Patients and Evaluation of the Adequacy of the Current Dosing Recommendation

Pharmaceutics ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 54 ◽  
Author(s):  
Amaia Soraluce ◽  
Helena Barrasa ◽  
Eduardo Asín-Prieto ◽  
Jose Ángel Sánchez-Izquierdo ◽  
Javier Maynar ◽  
...  
Keyword(s):  
Critically Ill ◽  
Critically Ill Patients ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Standard Dose ◽  
Compartment Model ◽  
Antimicrobial Treatment ◽  
Population Pharmacokinetic ◽  
Renal Replacement Therapies ◽  
Continuous Renal Replacement Therapies

Antimicrobial treatment in critically ill patients remains challenging. The aim of this study was to develop a population pharmacokinetic model for linezolid in critically ill patients and to evaluate the adequacy of current dosing recommendation (600 mg/12 h). Forty inpatients were included, 23 of whom were subjected to continuous renal replacement therapies (CRRT). Blood and effluent samples were drawn after linezolid administration at defined time points, and linezolid levels were measured. A population pharmacokinetic model was developed, using NONMEM 7.3. The percentage of patients that achieved the pharmacokinetic/pharmacodynamic (PK/PD) targets was calculated (AUC24/MIC > 80 and 100% T>MIC). A two-compartment model best described the pharmacokinetics of linezolid. Elimination was conditioned by the creatinine clearance and by the extra-corporeal clearance if the patient was subjected to CRRT. For most patients, the standard dose of linezolid did not cover infections caused by pathogens with MIC ≥ 2 mg/L. Continuous infusion may be an alternative, especially when renal function is preserved.

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