Margrét Thorsteinsdóttir (Presenter)
Pharmaceutical Sciences, University of Iceland
Bio: I am an associate professor of Pharmaceutical Analytical Chemistry at the Faculty of Pharmaceutical Sciences, University of Iceland and the R&D director of ArcticMass a spin-off company from a Bioanalytical Laboratory at deCode Genetics. I built up and directed a laboratory for the past 10 years, supporting the entire compound development process from drug discovery through post-marketing trials. My current research interest includes development of analytical methods for quantification of clinical biomarkers utilizing liquid chromatography coupled to mass spectrometry (LC-MS/MS). I have extensive experience in the field of mass spectrometry, especially in development of assays for metabolite profiling and quantification of biomarkers in different cell lines and other biofluids utilizing chemometric approaches. I have been using design of experiments for many years and was co-chairman of the Scandinavian Symposium on Chemometrics (SSC) and a member of the scientific committee for SSC. I was chairmen of the board of the Icelandic Chemical Society and I am a scientific advisor in the Rare Kidney Stone Consortium (RKSC), responsible for implementation of UPLC-MS/MS assays for routine diagnostics. I am a principal investigator of a Marie Curie program, BluePharmTrain and I have supervised several Ph.D. students as well as M.Sc. students at the University of Iceland.
Authorship: Margret Thorsteinsdottir
Pharmaceutical Sciences, University of Iceland, Reykjavik, Iceland
| Short Abstract Method optimization of liquid chromatography-tandem mass spectrometry (LC-MS/MS) for quantification of biomarkers for support of clinical diagnosis and therapeutic drug monitoring can become much more efficient by utilizing design of experiments (DoE). This approach offers many advantages including performing experiments in accordance to predefined plan, modelling by empirical functions and graphical visualization. This paper will illustrate that using DoE for optimization of LC-MS/MS methods is much more efficient with only fraction of experiments that would be required by changing one-factor-at-time (COST) approach. Example will be given to illustrate how DoE works for optimization of LC-MS/MS clinical diagnostic assay. |
Long Abstract
Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is becoming a routine technique in clinical laboratories for support of clinical diagnosis and therapeutic drug monitoring. The LC-MS/MS has the capacity to analyze several analytes in the same assay with ultimate selectivity and sensitivity needed for quantification of biomarkers in biological matrices. The method development consists of several integrated steps from sample preparation, chromatographic separation, mass spectrometry detection as well as data analysis. The LC-MS/MS is a two stage process, liquid introduction and analytes ionization. The goal is to transfer the analytes from condensed phase to gas phase and maintain conditions that are compatible for both the LC and the MS. These processes involve many experimental factors which need to be simultaneously optimized to obtain maximum selectivity and sensitivity at minimum retention time. Optimization of experimental conditions for LC-MS/MS methods is usually performed by changing one-factor-at-time (COST) approach. However this procedure can be very ineffective and possible interactions between experimental factors studied are not taken into account. A much more effective strategy for optimization of quantitative LC-MS/MS clinical diagnostic methods is to implement a chemometric based technique such as design of experiments (DoE). DoE is a systematic approach where experiments are performed according to predefined plan in as few experiments as possible and modelling is by empirical functions and graphical visualization. This paper illustrates the benefits of utilizing design of experiments (DoE) for method development and optimization of quantitative LC-MS/MS methods. Examples will be presented from selected assay utilizing this chemometric strategy for optimization of LC-MS/MS methods for evaluation of biomarkers for clinical diagnostic and therapeutic drug monitoring.
A chemometric approach was implemented for optimization of simultaneous quantification of biomarkers in various biological matrices with high-performance liquid chromatography (HPLC) and ultra-performance liquid chromatography (UPLC) coupled to an electrospray tandem mass spectrometer (MS/MS). The chemometric software MODDE 11 (MKS Data Analytical Solutions) was used to set up the design of experiments. Experimental screening of significant variables was performed by fractional factorial design to reveal the most influential experimental factors. When multi-levels qualitative factors were included in the screening experiments D-optimal design was applied. Optimization of significant factors were studied via central composite design and related to sensitivity, resolution and retention time utilizing partial least square (PLS)-regression.
Design of experiments (DoE) was utilized for optimization of a HPLC-MS/MS and UPLC-MS/MS quantification method for cortisol, cortisone and glycyrrhetinic acid in plasma. Results showed that many interaction factors were significant so these variables could not be independently controlled to obtain optimal conditions. Baseline separation was achieved between the biomarkers and the method was implemented for analyses of human plasma samples from individuals with and without liquorices consumption for support of clinical diagnosis of liquorice induced hypertension and for evaluation of 11 β-hydroxysteroid dehydrogenase type 2 (11βHSD2) enzyme activity in patients.
This selected study shows that design of experiments (DoE) can be used to ensure that selected experiments contain maximum information and optimization of this LC-MS/MS clinical assay was achieved efficiently with only fraction of the experiments that would be required by changing one-factor-at-time (COST) experiments.
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