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  • 1.
    Fredriksson, Mattias
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.
    Efficient algorithms for highly automated evaluation of liquid chromatography - mass spectrometry data2010Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Liquid chromatography coupled to mass spectrometry (LC‐MS) has due to its superiorresolving capabilities become one of the most common analytical instruments fordetermining the constituents in an unknown sample. Each type of sample requires a specificset‐up of the instrument parameters, a procedure referred to as method development.During the requisite experiments, a huge amount of data is acquired which often need to bescrutinised in several different ways. This thesis elucidates data processing methods forhandling this type of data in an automated fashion.The properties of different commonly used digital filters were compared for LC‐MS datade‐noising, of which one was later selected as an essential data processing step during adeveloped peak detection step. Reconstructed data was further discriminated into clusterswith equal retention times into components by an adopted method. This enabled anunsupervised and accurate comparison and matching routine by which components fromthe same sample could be tracked during different chromatographic conditions.The results show that the characteristics of the noise have an impact on the performanceof the tested digital filters. Peak detection with the proposed method was robust to thetested noise and baseline variations but functioned optimally when the analytical peaks hada frequency band different from the uninformative parts of the signal. The algorithm couldeasily be tuned to handle adjacent peaks with lower resolution. It was possible to assignpeaks into components without typical rotational and intensity ambiguities associated tocommon curve resolution methods, which are an alternative approach. The underlyingfunctions for matching components between different experiments yielded satisfactoryresults. The methods have been tested on various experimental data with a high successrate.

  • 2.
    Fredriksson, Mattias
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences.
    Forsberg, Sven
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences.
    Wood Fibre Composites with High Fibre Content2005Report (Other academic)
  • 3.
    Fredriksson, Mattias
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.
    Petersson, Patrik
    AstraZeneca.
    Axelsson, Bengt-Olof
    AstraZeneca.
    Bylund, Dan
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.
    A component tracking algorithm for accelerated and improved liquid chromatography-mass spectrometry method development2010In: Journal of Chromatography A, ISSN 0021-9673, E-ISSN 1873-3778, Vol. 1217, no 52, p. 8195-8204Article in journal (Refereed)
    Abstract [en]

    A method for tracking of sample components during liquid chromatography–mass spectrometry (LC–MS) method development has been proposed. The method manages to, fully automatically and without user intervention, find the chromatographic peaks in the data sets, discriminate them to sample components and track them when the separation conditions have been changed. The algorithm utilises the resolution obtained from all considered data sets and has the ability to discriminate the non informative parts. The technique has a great sensitivity even in cases where a majority of the tracked components cannot easily be spotted by means of traditional total ion chromatogram (TIC) or base peak chromatogram (BPC) representations. The method was tested on an experimental sample using six different columns and an average of 79% of the suggested sample components could be successfully tracked at a minimum area of 0.05% of the main component in the sample. 66 components with 79–92% of the total suggested component area were able to be tracked between all data sets. The method could be used to rapidly investigate selectivity during different types of separation conditions.

  • 4.
    Fredriksson, Mattias
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.
    Petersson, Patrik
    Axelsson, Bengt-Olof
    Bylund, Dan
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.
    An automatic peak finding method for LC-MS data using Gaussian second derivative filtering2009In: Journal of Separation Science, ISSN 1615-9306, E-ISSN 1615-9314, Vol. 32, no 22, p. 3906-3918Article in journal (Refereed)
    Abstract [en]

    A highly automated procedure for localising and characterising peaks in the chromatographic time domain of LC-MS data has been developed. The work was initiated by an identified need to facilitate the detection and tracking of chromatographic peaks during method development for the analysis of impurities in pharmaceutical products. The algorithm is mainly based on a digital filter for which the settings are automatically adapted to the data set under study. The procedure was evaluated for synthetic data sets with various S/N levels, peak widths and baseline properties. It was found that even for the worst case tested with S/N=10 and a high variability in the baseline, 94% of the simulated analytical peaks could be detected without producing any false-positive identifications. Furthermore, the number of correctly estimated peak heights and peak widths falling within a 10% error of the true values were 94 and 91%, respectively. For experimental data sets, peak height, and width estimations were more difficult, but the processed reconstructions showed an excellent agreement with the analytical signals of the raw data, and also a clearly improved visualisation in total ion- and base-peak chromatograms.

  • 5.
    Fredriksson, Mattias
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.
    Petersson, Patrik
    Astra Zeneca R and D Lund, SE-221 87 Lund, Sweden.
    Axelsson, Bengt-Olof
    Astra Zeneca R and D Lund, SE-221 87 Lund, Sweden.
    Bylund, Dan
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.
    Combined use of algorithms for peak picking, peak tracking and retention modelling to optimize the chromatographic conditions for liquid chromatography-mass spectrometry analysis of fluocinolone acetonide and its degradation products2011In: Analytica Chimica Acta, ISSN 0003-2670, E-ISSN 1873-4324, Vol. 704, no 1-2, p. 180-188Article in journal (Refereed)
    Abstract [en]

    A strategy for rapid optimization of liquid chromatography column temperature and gradient shape is presented. The optimization as such is based on the well established retention and peak width models implemented in software like e.g. DryLab and LC simulator. The novel part of the strategy is a highly automated processing algorithm for detection and tracking of chromatographic peaks in noisy liquid chromatography-mass spectrometry (LC-MS) data. The strategy is presented and visualized by the optimization of the separation of two degradants present in ultraviolet (UV) exposed fluocinolone acetonide. It should be stressed, however, that it can be utilized for LC-MS analysis of any sample and application where several runs are conducted on the same sample. In the application presented, 30 components that were difficult or impossible to detect in the UV data could be automatically detected and tracked in the MS data by using the proposed strategy. The number of correctly tracked components was above 95%. Using the parameters from the reconstructed data sets to the model gave good agreement between predicted and observed retention times at optimal conditions. The area of the smallest tracked component was estimated to 0.08% compared to the main component, a level relevant for the characterization of impurities in the pharmaceutical industry.

  • 6.
    Fredriksson, Mattias
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences.
    Petersson, Patrik
    Jörntén-Karlsson, Magnus
    Axelsson, Bengt-Olof
    Bylund, Dan
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences.
    An objective comparison of pre-processing methods for enhancement of liquid chromatography-mass spectrometry data2007In: Journal of Chromatography A, ISSN 0021-9673, E-ISSN 1873-3778, Vol. 1172, no 2, p. 135-150Article in journal (Refereed)
    Abstract [en]

    Four data pre-processing methods have been applied with different settings to data sets obtained from the analysis of a pharmaceutical drug and its degradation products by liquid chromatography�mass spectrometry (LC�MS). The methods compared were the frequently used component detection algorithm (CODA) and three kinds of digital filters�matched filtration (MF), Gaussian second derivative (GSD) and Savitzky�Golay. The aim was to evaluate the performance and robustness of these methods for extracted ion chromatogram (XIC), total ion chromatogram (TIC) and base peak chromatogram (BPC) in the presence of different types of noise. In accordance with theory, the best improvements in signal-to-noise ratio (S/N) of the XICs were obtained with MF under the ideal case with random white noise. However, when highly coloured noise was present, it was found that no improvements in XIC S/N could be obtained with any of the pre-processing methods studied. GSD and CODA did, however, improve the S/N for both TIC and BPC. GSD and CODA also significantly reduced the background in the spectral domain, thereby facilitating the interpretation of the mass spectra. Another advantage associated with CODA and to some extent also with GSD is their data reduction ability.

1 - 6 of 6
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