Margret Thorsteinsdottir (Presenter)
University of Iceland
Bio: I am an associate professor in pharmaceutical analytical chemistry at the faculty of Pharmaceutical Sciences at the University of Iceland and the R&D director of a spin-off company from deCode Genetics, ArcticMass, Ltd. which offers bioanalytical services utilizing mass spectrometers. For the past 10 years I worked as director of a Bioanalytical Laboratory at deCode Genetics. I managed and participated in building up a laboratory which developed methods for supporting the entire compound development process from drug discovery through post-marketing trials. I was a member of four product development teams which managed deCode Genetics drug development projects and was responsible for conducting PK calculations for all of the drug discovery projects. My major area of research interest includes the development analytical assays for metabolite profiling and quantification of biomarkers in different biofluids utilizing chemometric approaches. This includes studies of lipid metabolism as well as development of quantification methods of biomarkers in different cell lines, plasma, urine and tissues, mainly using ultra performance liquid chromatography coupled to soft ionization mass spectrometer (UPLC-MS/MS). Currently I have been focusing on developing and implementing a mass spectrometry based assays to clinic laboratories for support of diagnostics and therapeutic drug monitoring (in collaboration with ArcticMass and the Faculty of Medicine). I am a scientific advisor in the Rare Kidney Stone Consortium (RKSC), responsible for implementing a UPLC-MS/MS assay for routine diagnostics to a clinical laboratory. I am a principal investigator of a Marie Curie program, BluePharmTrain and I am currently supervising two Ph.D. students (Finnur Freyr Eiríksson and Ana Margarida Costa) as well as I have supervised several M.Sc. students. I have given lectures at major analytical and pharmaceutical based conferences.
Authorship: Margret Thorsteinsdottir (1) and Finnur Freyr Eiriksson (1, 2)
(1) University of Iceland, Reykjavik, Iceland, (2) ArcticMass, Reykjavik, Iceland
| Short Abstract Tandem mass spectrometry coupled to liquid chromatography (LC-MS/MS) is an excellent analytical platform for quantification of biomarkers in biological matrices. Method development consists of several integrated steps involving many experimental factors which need to be simultaneously optimized to obtain maximum selectivity and sensitivity at minimum retention time. This work will illustrate that method optimization can become much more efficient by utilizing design of experiments (DoE). Examples will be given to illustrate how DoE works for optimization of LC-MS/MS clinical diagnostic methods using only a fraction of experiments that would be required by changing one-factor-at-time (OFAT) approach. |
Long Abstract
Tandem mass spectrometry coupled to liquid chromatography (LC-MS/MS) is an excellent analytical platform with ultimate selectivity and sensitivity needed for quantification of biomarkers in complex biological matrices. 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. The method development consists of several integrated steps from sample preparation, chromatographic separation, mass spectrometry detection and to data analysis. These processes involve many experimental factors which need to be simultaneously optimized to obtain maximum selectivity and sensitivity at a minimum retention time. Method development and optimization of quantitative LC-MS/MS clinical diagnostic methods can become much more efficient by implementation of a chemometric based technique such as design of experiments (DoE). Optimization of experimental conditions for LC-MS/MS methods is usually performed by changing one-factor-at-time (OFAT) experiments. However this procedure can be very ineffective and possible interactions between experimental factors studied are not taken into account. A much more effective optimization strategy for discovering important experimental factors and to optimize the responses is to utilize DoE. Such systematic strategy includes several advantages, including performing experiments in accordance to predefined plan, modelling by empirical functions and graphical visualization. This work illustrates that method development and optimization of quantitative LC-MS/MS methods is much more efficient by utilizing DoE. Examples will be presented from selected assays for evaluation of biomarkers for clinical diagnostic purposes and therapeutic drug monitoring, utilizing this chemometric strategy for optimization of these assays.
High-performance liquid chromatography (HPLC) and ultra-performance liquid chromatography (UPLC) coupled to an electrospray tandem mass spectrometry (MS/MS) were used for simultaneous quantification of biomarkers in various biological matrices. A chemometric approach was implemented for optimization of these assays. A fractional factorial design was used for experimental screening to reveal the most influential experimental factors. When multi-levels qualitative factors were included in the screening experiments D-optimal design was applied. Significant factors were studied via central composite design and related to sensitivity, resolution and retention time utilizing partial least square (PLS)-regression.
This work shows that the chemometric approach, design of experiments (DoE) can be used to ensure that selected experiments contain maximum information and that optimization of these LC-MS/MS clinical diagnosis methods is achieved. A sensitive, specific and reliable UPLC-MS/MS assay for simultaneous quantification of urinary 2,8-dihydroxyadenine (DHA) and adenine was optimized efficiently with a chemometric approach. This assay has been implemented for clinical diagnosis and therapeutic drug monitoring of patients with adenine phosphoribosyltransferase (APRT) deficiency, which is an inborn error of purine metabolism.
In another study DoE was used for optimization of a HPLC-MS/MS and a UPLC-MS/MS quantification methods for simultaneous quantification of cortisol, cortisone and glycyrrhetinic acid in urine and plasma. Results showed that many interaction factors were significant and therefore 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 evaluation of 11 β-hydroxysteroid dehydrogenase type 2 (11βHSD2) enzyme activity.
These selected studies show that design of experiments (DoE) can be used to optimize the LC-MS/MS quantification methods efficiently with only fraction of the experiments that would be required by changing one-factor-at-time (OFAT) experiments.
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