Study of Preprocessing Methods for the Determination of Crystalline Phases in Binary Mixtures of Drug Substances by X-ray Powder Diffraction and Multivariate Calibration

Abstract

In this paper, various preprocessing methods were tested on data generated by X-ray powder diffraction (XRPD) in order to enhance the partial least-squares (PLS) regression modeling performance. The preprocessing methods examined were 22 different discrete wavelet transforms, Fourier transform, Savitzky–Golay, orthogonal signal correction (OSC), and combinations of wavelet transform and OSC, and Fourier transform and OSC. Root mean square error of prediction (RMSEP) of an independent test set was used to measure the performance of the various preprocessing methods. The best PLS model was obtained with a wavelet transform (Symmlet 8), which at the same time compressed the data set by a factor of 9.5. With the use of wavelet and X-ray powder diffraction, concentrations of less than 10% of one crystal from could be detected in a binary mixture. The linear range was found to be in the range 10–70% of the crystalline form of phenacetin, although semiquantitative work could be carried out down to a level of approximately 2%. Furthermore, the wavelet-pretreated models were able to handle admixtures and deliberately added noise.

Quantitative Determination of Hydrate Content of Theophylline Powder by Chemometric X-ray Powder Diffraction Analysis

“…If the problems of imperfection of the standard sample homogeneity and the crystal orientation are solved, the XRPD will become more robust method for evaluation of crystal content in online pharmaceutical manufacturing processes as one of PAT tools. For this reason, the chemometric XRPD method was investigated as a quantitative method for the prediction of polymorphic content in a previous study (5,7). The results confirmed the importance of standard sample quality and the usefulness of the chemometrics method for accuracy of quantitative XRPD analysis.…”

“…However, the XRPD method has relatively large errors, around ±5%. This limitation of accuracy is caused by imperfect homogeneity in the crystalline standard samples and crystal orientation when the sample powder is loaded on the glass plate (5). Imperfect homogeneity of the standard sample can be improved by avoiding destruction of the crystalline form during the mixing process (6,7) While crystal orientation is caused by aeolotropic crystal habit of polymorphic forms.…”

Smoothing of X-ray diffraction data andKα2elimination using penalized likelihood and the composite link model

“…Very popular in analytical chemistry is the Savitzky-Golay filter (Savitzky & Golay, 1964), which tunes smoothness by varying the order of the local polynomial and the number of basis functions. Other methods use wavelets or Fourier transforms, which are both reviewed by Artursson et al (2000). Chen et al (2005) used smooth principal components to exploit the shared variation in a set of different patterns.…”

Multivariate calibration of analytical signals by WILMA (wavelet interface to linear modelling analysis)

“…The discrete wavelet transform (DWT) has been applied as a preprocessing tool in multivariate calibration of near-IR spectra [14][15][16][17], mid-IR spectra [18], Raman spectra [19], fluorescence data [20], X-ray powder diffraction spectra [21], process variables [22] and electroanalytical signals [23].…”

“…Where DWT is used for feature selection, two approaches are most often proposed: (1) the wavelet coefficients are thresholded by using criteria based on the evaluation of PLS weights [18] or of PLS regression coefficients [15]; (2) the wavelet coefficients are previously ranked by their variance [16,20,21] or by their squared correlation coefficient with the response variable [17]; then the subset giving the most stable or the best performing regression model is selected.…”