Statistical Analysis of a Method to Predict Drug-Polymer Miscibility

Matthias Manne Knopp, Niels Erik Olesen, Yanbin Huang, René Holm, Thomas Rades

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

    Resumé

    In this study, a method proposed to predict drugepolymer miscibility from differential scanning calorimetry measurements was subjected to statistical analysis. The method is relatively fast and inexpensive and has gained popularity as a result of the increasing interest in the formulation of drugs as amorphous solid dispersions. However, it does not include a standard statistical assessment of the experimental uncertainty by means of a confidence interval. In addition, it applies a routine mathematical operation known as “transformation to linearity,” which previously has been shown to be subject to a substantial bias. The statistical analysis performed in this present study revealed that the mathematical procedure associated with the method is not only biased, but also too uncertain to predict drugepolymer miscibility at room temperature. Consequently, the statistical inference based on the mathematical procedure is problematic and may foster uncritical and misguiding interpretations. From a statistical perspective, the drugepolymer miscibility prediction should instead be examined by deriving an objective function, which results in the unbiased, minimum variance properties of the least-square estimator as provided in this study.
    OriginalsprogEngelsk
    TidsskriftJournal of Pharmaceutical Sciences
    Vol/bind105
    Udgave nummer1
    Sider (fra-til)362-367
    ISSN0022-3549
    DOI
    StatusUdgivet - 2016

    Citer dette

    Knopp, M. M., Olesen, N. E., Huang, Y., Holm, R., & Rades, T. (2016). Statistical Analysis of a Method to Predict Drug-Polymer Miscibility. Journal of Pharmaceutical Sciences, 105(1), 362-367. https://doi.org/10.1002/jps.24704
    Knopp, Matthias Manne ; Olesen, Niels Erik ; Huang, Yanbin ; Holm, René ; Rades, Thomas. / Statistical Analysis of a Method to Predict Drug-Polymer Miscibility. I: Journal of Pharmaceutical Sciences. 2016 ; Bind 105, Nr. 1. s. 362-367.
    @article{d686fc02d677413794019a94b907651a,
    title = "Statistical Analysis of a Method to Predict Drug-Polymer Miscibility",
    abstract = "In this study, a method proposed to predict drugepolymer miscibility from differential scanning calorimetry measurements was subjected to statistical analysis. The method is relatively fast and inexpensive and has gained popularity as a result of the increasing interest in the formulation of drugs as amorphous solid dispersions. However, it does not include a standard statistical assessment of the experimental uncertainty by means of a confidence interval. In addition, it applies a routine mathematical operation known as “transformation to linearity,” which previously has been shown to be subject to a substantial bias. The statistical analysis performed in this present study revealed that the mathematical procedure associated with the method is not only biased, but also too uncertain to predict drugepolymer miscibility at room temperature. Consequently, the statistical inference based on the mathematical procedure is problematic and may foster uncritical and misguiding interpretations. From a statistical perspective, the drugepolymer miscibility prediction should instead be examined by deriving an objective function, which results in the unbiased, minimum variance properties of the least-square estimator as provided in this study.",
    author = "Knopp, {Matthias Manne} and Olesen, {Niels Erik} and Yanbin Huang and Ren{\'e} Holm and Thomas Rades",
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    Knopp, MM, Olesen, NE, Huang, Y, Holm, R & Rades, T 2016, 'Statistical Analysis of a Method to Predict Drug-Polymer Miscibility', Journal of Pharmaceutical Sciences, bind 105, nr. 1, s. 362-367. https://doi.org/10.1002/jps.24704

    Statistical Analysis of a Method to Predict Drug-Polymer Miscibility. / Knopp, Matthias Manne; Olesen, Niels Erik; Huang, Yanbin; Holm, René; Rades, Thomas.

    I: Journal of Pharmaceutical Sciences, Bind 105, Nr. 1, 2016, s. 362-367.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

    TY - JOUR

    T1 - Statistical Analysis of a Method to Predict Drug-Polymer Miscibility

    AU - Knopp, Matthias Manne

    AU - Olesen, Niels Erik

    AU - Huang, Yanbin

    AU - Holm, René

    AU - Rades, Thomas

    PY - 2016

    Y1 - 2016

    N2 - In this study, a method proposed to predict drugepolymer miscibility from differential scanning calorimetry measurements was subjected to statistical analysis. The method is relatively fast and inexpensive and has gained popularity as a result of the increasing interest in the formulation of drugs as amorphous solid dispersions. However, it does not include a standard statistical assessment of the experimental uncertainty by means of a confidence interval. In addition, it applies a routine mathematical operation known as “transformation to linearity,” which previously has been shown to be subject to a substantial bias. The statistical analysis performed in this present study revealed that the mathematical procedure associated with the method is not only biased, but also too uncertain to predict drugepolymer miscibility at room temperature. Consequently, the statistical inference based on the mathematical procedure is problematic and may foster uncritical and misguiding interpretations. From a statistical perspective, the drugepolymer miscibility prediction should instead be examined by deriving an objective function, which results in the unbiased, minimum variance properties of the least-square estimator as provided in this study.

    AB - In this study, a method proposed to predict drugepolymer miscibility from differential scanning calorimetry measurements was subjected to statistical analysis. The method is relatively fast and inexpensive and has gained popularity as a result of the increasing interest in the formulation of drugs as amorphous solid dispersions. However, it does not include a standard statistical assessment of the experimental uncertainty by means of a confidence interval. In addition, it applies a routine mathematical operation known as “transformation to linearity,” which previously has been shown to be subject to a substantial bias. The statistical analysis performed in this present study revealed that the mathematical procedure associated with the method is not only biased, but also too uncertain to predict drugepolymer miscibility at room temperature. Consequently, the statistical inference based on the mathematical procedure is problematic and may foster uncritical and misguiding interpretations. From a statistical perspective, the drugepolymer miscibility prediction should instead be examined by deriving an objective function, which results in the unbiased, minimum variance properties of the least-square estimator as provided in this study.

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    JO - Journal of Pharmaceutical Sciences

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