Transl Clin Pharmacol.  2019 Sep;27(3):89-91. 10.12793/tcp.2019.27.3.89.

Non-compartmental data analysis using SimBiology and MATLAB

• Park JS
• Kim JR

• KMID: 2458947
• DOI: http://doi.org/10.12793/tcp.2019.27.3.89

Abstract

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.

Keyword

Data Analysis; Noncompartmental; Pharmacodynamics; Pharmacokinetics; Software

MeSH Terms

Dataset
Linear Models
Methods
Pharmacokinetics
Pharmacology, Clinical
Statistics as Topic*

Reference

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