Premium
Design of experiments for development and optimization of a liquid chromatography coupled to tandem mass spectrometry bioanalytical assay
Author(s) -
Thorsteinsdóttir Unnur Arna,
Thorsteinsdóttir Margrét
Publication year - 2021
Publication title -
journal of mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.475
H-Index - 121
eISSN - 1096-9888
pISSN - 1076-5174
DOI - 10.1002/jms.4566
Subject(s) - design of experiments , bioanalysis , chemistry , resolution (logic) , tandem , chromatography , high resolution , response surface methodology , tandem mass spectrometry , function (biology) , mass spectrometry , biochemical engineering , process engineering , computer science , artificial intelligence , statistics , aerospace engineering , geology , engineering , biology , remote sensing , mathematics , evolutionary biology
Design of experiment (DoE) is a chemometric approach to study the influence of each experimental factor simultaneously at various levels with a predefined number of experiments, considering all possible interactions between the factors. In this tutorial special feature article, Margrét Thorsteinsdóttir and colleague provide an overview of the basic concepts of DoE and a strategy for implementation of DoE for the optimization of a quantitative LC‐MS/MS methods. Indeed, DoE is an excellent tool for the development and optimization of hyphenated techniques such as LC‐MS/MS, where several experimental factors need to be simultaneously optimized to obtain maximum sensitivity with adequate resolution between closely eluting peaks. The results are expressed as a mathematical function of the experimental conditions providing a mean to predict and estimate results at levels that were not directly studied. The data can be explored by use of counter plots and response surface plots to visualize how the response is affected by the factors studied and for finding a combination of factor settings that will result in optimum analytical conditions. With better designed experiments, flow of measurements to knowledge can proceed in the most cost‐effective way. Margrét Thorsteinsdóttir (PhD) is Professor at the Faculty of Pharmaceutical Science at the University of Iceland (Reykjavik, Iceland). Her main research interest is focused on the development of high‐performance separation science with applications in clinical MS.