Park Jin-Sol, Kim Jung-Ryul
Department of Clinical Pharmacology and Therapeutics, Samsung Medical Center, Seoul 06351, Republic of Korea.
Department of Clinical Research Design & Evaluation, SAIHST, Sungkyunkwan University, Seoul 06351, Republic of Korea.
Transl Clin Pharmacol. 2019 Sep;27(3):89-91. doi: 10.12793/tcp.2019.27.3.89. Epub 2019 Sep 30.
MATLAB® is widely used for numerical analysis, modeling, and simulation. One of MATLAB's tools, SimBiology®, is often used for pharmacokinetic, pharmacodynamic model and dynamic systems; however, SimBiology seems to be rarely used for non-compartmental analysis (NCA), and the published official documentation provides a poor description of the analysis algorithm for NCA. Therefore, we conducted NCAs with a hypothetical dataset and some scenarios and compared the results. According to the results of this study, SimBiology estimates parameters using the unweighted linear regression for the terminal slope and linear interpolation method. Moreover, although the documentation describing the actual analysis algorithm used to process non-numeric data is not easily accessible to users, users may introduce numeric data at time zero to perform NCA properly. Using the command window, users can perform analyses more quickly and effectively. If the NCA official documentation were improved, SimBiology might be more widely adopted to perform NCA in clinical pharmacology.
MATLAB®广泛用于数值分析、建模和仿真。MATLAB的工具之一SimBiology®常用于药代动力学、药效学模型和动态系统；然而，SimBiology似乎很少用于非房室分析（NCA），并且已发布的官方文档对NCA的分析算法描述不佳。因此，我们使用一个假设数据集和一些场景进行了NCA，并比较了结果。根据本研究的结果，SimBiology使用终端斜率的未加权线性回归和线性插值方法估计参数。此外，尽管用户不容易获取描述用于处理非数值数据的实际分析算法的文档，但用户可以在零时刻引入数值数据以正确执行NCA。使用命令窗口，用户可以更快、更有效地进行分析。如果NCA官方文档得到改进，SimBiology可能会在临床药理学中更广泛地用于执行NCA。
