Estimation of the area under the concentration-versus-time curve of carboplatin following irinotecan using a limited sampling model

1998 ◽  
Vol 54 (9-10) ◽  
pp. 725-727 ◽  
Author(s):  
G. Asai ◽  
Y. Ando ◽  
H. Saka ◽  
M. Ando ◽  
S. Sugiura ◽  
...  
Keyword(s):  
Time Curve ◽  
Limited Sampling Model ◽  
Limited Sampling

A Limited Sampling Model to Estimate Exposure to Lenalidomide in Multiple Myeloma Patients

2014 ◽  
Vol 36 (4) ◽  
pp. 505-509 ◽  
Author(s):  
Seiji Shida ◽  
Naoto Takahashi ◽  
Masatomo Miura ◽  
Takenori Niioka ◽  
Morio Matsumoto ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Limited Sampling Model ◽  
Limited Sampling

Comparison of Algorithms for Oral Busulphan Area Under the Concentration–Time Curve Limited Sampling Estimate

2013 ◽  
Vol 34 (1) ◽  
pp. 43-52 ◽  
Author(s):  
Fredrik Sjöö ◽  
Ibrahim El-Serafi ◽  
Jon Enestig ◽  
Jonas Mattsson ◽  
Johan Liwing ◽  
...  
Keyword(s):  
Time Curve ◽  
Limited Sampling ◽  
Concentration Time ◽  
Comparison Of Algorithms

Limited Sampling Strategies to Estimate the Area under the Concentration-time Curve

2012 ◽  
Vol 51 (05) ◽  
pp. 383-394 ◽  
Author(s):  
M. Fukumoto ◽  
L. Bax ◽  
A. Kohno ◽  
Y. Morishita ◽  
H. Tsuruta
Keyword(s):  
Rate Constant ◽  
Elimination Rate ◽  
Estimation Method ◽  
Pharmacokinetic Parameters ◽  
Good Precision ◽  
Sampling Strategies ◽  
Time Curve ◽  
New Methods ◽  
Limited Sampling ◽  
Concentration Time

SummaryBackground: Over 100 limited sampling strategies (LSSs) have been proposed to reduce the number of blood samples necessary to estimate the area under the concentration-time curve (AUC). The conditions under which these strategies succeed or fail remain to be clarified.Objectives: We investigated the accuracy of existing LSSs both theoretically and numerically by Monte Carlo simulation. We also proposed two new methods for more accurate AUC estimations.Methods: We evaluated the following existing methods theoretically: i) nonlinear curve fitting algorithm (NLF), ii) the trapezium rule with exponential curve approximation (TZE), and iii) multiple linear regression (MLR). Taking busulfan (BU) as a test drug, we generated a set of theoretical concentration-time curves based on the identified distribution of pharmacokinetic parameters of BU and re-evaluated the existing LSSs using these virtual validation profiles. Based on the evaluation results, we improved the TZE so that unrealistic parameter values were not used. We also proposed a new estimation method in which the most likely curve was selected from a set of pre-generated theoretical concentration-time curves.Results: Our evaluation, based on clinical profiles and a virtual validation set, revealed: i) NLF sometimes overestimated the absorption rate constant Ka, ii) TZE overestimated AUC over 280% when Ka is small, and iii) MLR underestimated AUC over 30% when the elimination rate constant Ke is small. These results were consistent with our mathematical evaluations for these methods. In contrast, our two new methods had little bias and good precision.Conclusions: Our investigation revealed that existing LSSs induce different but specific biases in the estimation of AUC. Our two new LSSs, a modified TZE and one using model concentration-time curves, provided accurate and precise estimations of AUC.

CORRELATION BETWEEN HEPATIC VENO-OCCLUSIVE DISEASE (VOD) AND BUSULPHAN LEVELS USING LIMITED SAMPLING MODEL FOR DOSE ESTIMATION.

1999 ◽  
Vol 21 (4) ◽  
pp. 432
Author(s):  
M. Hassan ◽  
G. Öberg ◽  
P. Ljungman ◽  
C. Nilsson ◽  
M. Sandström ◽  
...  
Keyword(s):  
Occlusive Disease ◽  
Dose Estimation ◽  
Limited Sampling Model ◽  
Limited Sampling

scholarly journals Pharmacokinetic Modeling and Limited Sampling Strategies Based on Healthy Volunteers for Monitoring of Ertapenem in Patients with Multidrug-Resistant Tuberculosis

2017 ◽  
Vol 61 (4) ◽  
Author(s):  
S. P. van Rijn ◽  
M. A. Zuur ◽  
R. van Altena ◽  
O. W. Akkerman ◽  
J. H. Proost ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Sampling Strategy ◽  
Free Fraction ◽  
Limited Sampling Strategy ◽  
Population Pharmacokinetic ◽  
Time Curve ◽  
Limited Sampling ◽  
Mdr Tb

ABSTRACT Ertapenem is a broad-spectrum carbapenem antibiotic whose activity against Mycobacterium tuberculosis is being explored. Carbapenems have antibacterial activity when the plasma concentration exceeds the MIC at least 40% of the time (40% T MIC). To assess the 40% T MIC in multidrug-resistant tuberculosis (MDR-TB) patients, a limited sampling strategy was developed using a population pharmacokinetic model based on data for healthy volunteers. A two-compartment population pharmacokinetic model was developed with data for 42 healthy volunteers using an iterative two-stage Bayesian method. External validation was performed by Bayesian fitting of the model developed with data for volunteers to the data for individual MDR-TB patients (in which the fitted values of the area under the concentration-time curve from 0 to 24 h [AUC0–24, fit values] were used) using the population model developed for volunteers as a prior. A Monte Carlo simulation (n = 1,000) was used to evaluate limited sampling strategies. Additionally, the 40% T MIC with the free fraction (f 40% T MIC) of ertapenem in MDR-TB patients was estimated with the population pharmacokinetic model. The population pharmacokinetic model that was developed was shown to overestimate the area under the concentration-time curve from 0 to 24 h (AUC0–24) in MDR-TB patients by 6.8% (range, −17.2 to 30.7%). The best-performing limited sampling strategy, which had a time restriction of 0 to 6 h, was found to be sampling at 1 and 5 h (r 2 = 0.78, mean prediction error = −0.33%, root mean square error = 5.5%). Drug exposure was overestimated by a mean percentage of 4.2% (range, −15.2 to 23.6%). When a free fraction of 5% was considered and the MIC was set at 0.5 mg/liter, the minimum f 40% T MIC would have been exceeded in 9 out of 12 patients. A population pharmacokinetic model and limited sampling strategy, developed using data from healthy volunteers, were shown to be adequate to predict ertapenem exposure in MDR-TB patients.

A Limited Sampling Model with Bayesian Estimation to Determine Inulin Pharmacokinetics Using the Population Data Modelling Program P-PHARM

1995 ◽  
Vol 9 (5) ◽  
pp. 260-269 ◽  
Author(s):  
Jean-Marie Kinowski ◽  
Françoise Bressolle ◽  
Michel Rodier ◽  
Valérie Augey ◽  
David Fabre ◽  
...  
Keyword(s):  
Bayesian Estimation ◽  
Population Data ◽  
Data Modelling ◽  
Limited Sampling Model ◽  
Limited Sampling
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