ICON Development Solutions, Hanover, MD 21076, USA.
Comput Methods Programs Biomed. 2013 Sep;111(3):715-34. doi: 10.1016/j.cmpb.2013.05.026. Epub 2013 Jun 27.
S-ADAPT is a version of the ADAPT program that contains additional simulation and optimization abilities such as parametric population analysis. S-ADAPT utilizes LSODA to solve ordinary differential equations (ODEs), an algorithm designed for large dimension non-stiff and stiff problems. However, S-ADAPT does not have a solver for delay differential equations (DDEs). Our objective was to implement in S-ADAPT a DDE solver using the methods of steps. The method of steps allows one to solve virtually any DDE system by transforming it to an ODE system. The solver was validated for scalar linear DDEs with one delay and bolus and infusion inputs for which explicit analytic solutions were derived. Solutions of nonlinear DDE problems coded in S-ADAPT were validated by comparing them with ones obtained by the MATLAB DDE solver dde23. The estimation of parameters was tested on the MATLB simulated population pharmacodynamics data. The comparison of S-ADAPT generated solutions for DDE problems with the explicit solutions as well as MATLAB produced solutions which agreed to at least 7 significant digits. The population parameter estimates from using importance sampling expectation-maximization in S-ADAPT agreed with ones used to generate the data.
S-ADAPT 是 ADAPT 程序的一个版本,它包含了额外的模拟和优化功能,如参数群体分析。S-ADAPT 使用 LSODA 来求解常微分方程(ODE),这是一种专为大维度非刚性和刚性问题设计的算法。然而,S-ADAPT 没有用于延迟微分方程(DDE)的求解器。我们的目标是在 S-ADAPT 中实现一个使用分步法的 DDE 求解器。分步法允许通过将 DDE 系统转换为 ODE 系统来求解几乎任何 DDE 系统。对于具有一个延迟和推注和输注输入的标量线性 DDE,我们推导了显式解析解,并对求解器进行了验证。通过将 S-ADAPT 中编码的非线性 DDE 问题的解与 MATLAB DDE 求解器 dde23 获得的解进行比较,对其进行了验证。对 MATLB 模拟群体药代动力学数据进行了参数估计测试。使用重要性抽样期望最大化在 S-ADAPT 中生成的 DDE 问题的解与显式解以及 MATLAB 生成的解之间的比较至少有 7 位有效数字是一致的。使用 S-ADAPT 中的重要性抽样期望最大化进行的群体参数估计与用于生成数据的参数估计一致。