Paper Info
Title
Sampling schedule design towards optimal drug monitoring for individualizing therapy.
Abstract
We study the individualization of therapy by simultaneously taking into account the design of sampling schedule and optimal therapeutic drug monitoring. The sampling schedule design in this work is to determine the number of samples, the sampling times, the switching time from the loading to the maintenance period, and the drug dosages. A closed-loop control policy is employed to determine the sampling schedule, and an advanced stochastic global optimization algorithm, which integrates the stochastic approximation and simulated annealing techniques, is implemented to search the optimal sampling schedule. A simulated one-compartment model of intravenous theophylline therapy is used to illustrate our method. This method can be readily extended to multiple compartment systems and allow incorporating other criteria of drug control. While currently the method is mainly of theoretical interest, it offers a starting point for practical applications and thus is hopefully of great value for the clinically individualizing therapy in the future.
Year
DOI
Venue
2005
10.1016/j.cmpb.2005.06.002
Computer Methods and Programs in Biomedicine
Keywords
Field
DocType
optimal therapeutic drug monitoring,sampling time,drug dosage,individualizing therapy,advanced stochastic global optimization,sampling schedule,drug control,optimal sampling schedule,intravenous theophylline therapy,sampling schedule design,optimal drug monitoring,simulated annealing,closed loop control,stochastic approximation
Simulated annealing,Mathematical optimization,Global optimization algorithm,Computer science,Drug dosages,Sampling (statistics),Stochastic approximation
Journal
Volume
Issue
ISSN
80
1
0169-2607
Citations 
PageRank 
References 
0
0.34
1
Authors
4
Name
Order
Citations
PageRank
Shaolin Ji192.76
Yingzhi Zeng2225.59
Ping Wu300.68
Edmund Jon Deoon Lee470.84