A review on estimation of stochastic differential equations for pharmacokinetic/pharmacodynamic models

作者：Donnet Sophie; Samson Adeline^*

来源：Advanced Drug Delivery Reviews, 2013, 65(7): 929-939.

DOI：10.1016/j.addr.2013.03.005

• Stochastic differential equations
• Pharmacokinetic
• Pharmacodynamic
• Population approach
• Maximum likelihood estimation
• Kalman filter
• EM algorithm
• Hermite expansion
• Gauss quadrature
• Bayesian estimation

This paper is a survey of existing estimation methods for pharmacokinetic/pharmacodynamic (PK/PD) models based on stochastic differential equations (SDEs). Most parametric estimation methods proposed for SDEs require high frequency data and are often poorly suited for PK/PD data which are usually sparse. Moreover, PK/PD experiments generally include not a single individual but a group of subjects, leading to a population estimation approach. This review concentrates on estimation methods which have been applied to PK/PD data, for SDEs observed with and without measurement noise, with a standard or a population approach. Besides, the adopted methodologies highly differ depending on the existence or not of an explicit transition density of the SDE solution.

• 出版日期2013-6-30