Delay differential equations based models in NONMEM
Publication in refereed journal


摘要Delay differential equations (DDEs) are commonly used in pharmacometric models to describe delays present in phar-macokinetic and pharmacodynamic data analysis. Several DDE solvers have been implemented in NONMEM 7.5 for the first time. Two of them are based on algorithms already applied elsewhere, while others are extensions of existing ordinary differential equations (ODEs) solvers. The purpose of this tutorial is to introduce basic concepts underlying DDE based models and show how they can be developed using NONMEM. The examples include previously published DDE models such as logistic growth, tumor growth inhibition, indirect response with precursor pool, rheumatoid arthritis, and ery-thropoiesis-stimulating agents. We evaluated the accuracy of NONMEM DDE solvers, their ability to handle stiff prob-lems, and their performance in parameter estimation using both first-order conditional estimation (FOCE) and the expectation–maximization (EM) method. NONMEM control streams and excerpts from datasets are provided for all discussed examples. All DDE solvers provide accurate and precise solutions with the number of significant digits con-trolled by the error tolerance parameters. For estimation of population parameters, the EM method is more stable than FOCE regardless of the DDE solver.
著者Xiaoyu Yan, Robert Bauer, Gilbert Koch, Johannes Schropp, Juan Jose Perez Ruixo, Wojciech Krzyzanski
期刊名稱Journal of Pharmacokinetics and Pharmacodynamics

上次更新時間 2021-28-11 於 00:24