Statistical Analysis of a Method to Predict Drug-Polymer Miscibility
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Statistical Analysis of a Method to Predict Drug-Polymer Miscibility. / Knopp, Matthias Manne; Olesen, Niels Erik; Huang, Yanbin; Holm, René; Rades, Thomas.
In: Journal of Pharmaceutical Sciences, Vol. 105, No. 1, 05.01.2016, p. 362–367.Research output: Contribution to journal › Journal article › Research › peer-review
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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
N1 - © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.
PY - 2016/1/5
Y1 - 2016/1/5
N2 - In this study, a method proposed to predict drug-polymer 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 drug-polymer 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 drug-polymer 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. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci.
AB - In this study, a method proposed to predict drug-polymer 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 drug-polymer 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 drug-polymer 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. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci.
U2 - 10.1002/jps.24704
DO - 10.1002/jps.24704
M3 - Journal article
C2 - 26539792
VL - 105
SP - 362
EP - 367
JO - Journal of Pharmaceutical Sciences
JF - Journal of Pharmaceutical Sciences
SN - 0022-3549
IS - 1
ER -
ID: 161588172