Abstract
Designing a dosage regimen for a pharmacokinetic/pharmacodynamic system involves defining: i) a patient-dependent model, which includes structure, parameter, and measurement uncertainties; ii) the choice of controls, which can include dose amounts, dose times and /or sampling times; and iii) an appropriate performance index to evaluate achievement of a clinically chosen therapeutic goal. The control problem then is to choose the dosage regimen that optimizes the expected value of the performance index. This problem fits within the framework of stochastic control theory. Examples are given to illustrate the variety of this class of problems, including: optimal dose regimens for target level and target window cost; and optimal sampling schedules for maximal information. By varying the class of admissible controls, different strategies are generated. Control strategies to be discussed include: open loop, open loop feedback, separation principle, and iteration in policy space. Monte Carlo simulation studies of a terminal cost type problem are presented.
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Schumitzky, A. (1991). Application of Stochastic Control Theory to Optimal Design of Dosage Regimens. In: D’Argenio, D.Z. (eds) Advanced Methods of Pharmacokinetic and Pharmacodynamic Systems Analysis. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-9021-4_13
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DOI: https://doi.org/10.1007/978-1-4757-9021-4_13
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