scholarly journals Near-Optimal Sampling Strategies for Multivariate Function Approximation on General Domains

2020 ◽  
Vol 2 (3) ◽  
pp. 607-630
Author(s):  
Ben Adcock ◽  
Juan M. Cardenas
Keyword(s):  
Function Approximation ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Multivariate Function

scholarly journals Optimal Sampling Strategies for Detecting Zoonotic Disease Epidemics

2014 ◽  
Vol 10 (6) ◽  
pp. e1003668 ◽  
Author(s):  
Jake M. Ferguson ◽  
Jessica B. Langebrake ◽  
Vincent L. Cannataro ◽  
Andres J. Garcia ◽  
Elizabeth A. Hamman ◽  
...  
Keyword(s):  
Zoonotic Disease ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Disease Epidemics

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 in Quicksort and Quickselect

2001 ◽  
Vol 31 (3) ◽  
pp. 683-705 ◽  
Author(s):  
Conrado Martínez ◽  
Salvador Roura
Keyword(s):  
Optimal Sampling ◽  
Sampling Strategies

Determining optimal sampling strategies for monitoring mercury and reproductive success in common loons in the Adirondacks of New York

Ecotoxicology ◽  
2019 ◽  
Vol 29 (10) ◽  
pp. 1786-1793 ◽  
Author(s):  
Yang Yang ◽  
Ruth D. Yanai ◽  
Nina Schoch ◽  
Valerie L. Buxton ◽  
Kara E. Gonzales ◽  
...  
Keyword(s):  
New York ◽  
Reproductive Success ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Common Loons

A Randomized Algorithm for Multivariate Function Approximation

2017 ◽  
Vol 39 (3) ◽  
pp. A983-A1002 ◽  
Author(s):  
Yeonjong Shin ◽  
Dongbin Xiu
Keyword(s):  
Function Approximation ◽  
Randomized Algorithm ◽  
Multivariate Function

scholarly journals Optimal Sampling Strategies to Assess Inulin Clearance in Children by the Inulin Single-Injection Method

2003 ◽  
Vol 49 (7) ◽  
pp. 1170-1179 ◽  
Author(s):  
Lyonne K van Rossum ◽  
Ron A A Mathot ◽  
Karlien Cransberg ◽  
Arnold G Vulto
Keyword(s):  
Pediatric Patients ◽  
Bolus Injection ◽  
Single Injection ◽  
Inulin Clearance ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Injection Method ◽  
Validation Set ◽  
Sampling Times ◽  
Single Bolus Injection

Abstract Background: Glomerular filtration rate in patients can be determined by estimating the plasma clearance of inulin with the single-injection method. In this method, a single bolus injection of inulin is administered and several blood samples are collected. For practical and convenient application of this method in children, it is important that a minimal number of samples are drawn. The aim of this study was to develop and validate sampling strategies with fewer samples for reliable prediction of inulin clearance in pediatric patients by the inulin single-bolus-injection method. Methods: Complete inulin plasma concentration-time curves of 154 patients were divided into an index (n = 100) and a validation set (n = 54). A population pharmacokinetic model was developed for the index set. Optimal sampling times were selected based on D-optimality theory. For the validation set, Bayesian estimates of clearance were generated using the derived population parameters and concentrations at two to four sampling times. Bayesian estimates of clearance were compared with the individual reference values of clearance. Results: The strategies with samples taken at 10/30/90/240 min, 10/30/240 min, 10/90/240 min, 30/90/240 min, and 90/240 min allowed accurate prediction of inulin clearance (bias <3% and not significantly different from 0; imprecision <15%). Conclusions: Strategies involving two to four samples, including a sample at 240 min after administration of inulin, in the inulin single-injection method allow accurate prediction of inulin clearance in pediatric patients. Even one blood sample at 240 min showed acceptable performance. The proposed strategies are practical and convenient to children, and reduce repetitive blood sampling without compromising accuracy.

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