Quality Control of High Throughput Screening

  • Hervé C. Zilliox

    Student thesis: Master's ThesisMaster of Science (by Research)


    [Master of Science by Research thesis]. High Throughput Screening (HTS) is an efficient way of assessing the biological activity of a large number of compounds in order to determine the few compounds that could lead to the development of a pharmaceutical product of commercial value. The process consists of screening a large number of mixtures using the standard 96-well plate featuring amongst others six specific control wells whose expected value is known. Because the measurement technique is subject to variation and because of the large number of plates involved, the quality assessment of the data is difficult and therefore automation appears to be a necessity. We propose a three-step procedure for the quality control of the data. It first consists of a study based on control wells, where a Gaussian mixture, trained with the EM algorithm, models the distribution of the control values to determine general variations on a whole screen together with any errors that would affect the control wells. The second step relies on normal wells and is based on a plate to plate comparison and an intra-plate variation detection that aims at spotting general effects such as handling mistakes or blocked jets. The Kolmogorov-Smirnov procedure was chosen to perform inter-plate comparisons whereas Siegel-Tukey and Wilcoxon tests investigate differences in spread and location in the data within a plate. The Analysis of Variance techniques complete the quality control of the screening process by focusing on the detection of systematic edge and corner effects.
    Date of AwardSept 1998
    Original languageEnglish


    • Gaussian Mixture Model
    • EM algorithm
    • Statistical tests
    • Analysis of Variance
    • High Throughput Screening
    • Machine Learning
    • Applied Mathematics
    • Neural Networks

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