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

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.