An Accurate Quantitative Analysis of Polymorphic Content by Chemometric X-ray Powder Diffraction

Abstract

Data from X-ray powder diffraction (XRD) were subjected to a partial least-squares regression analysis (PLS) to build a calibration model for predicting the polymorphic content of carbamazepine (CBZ). The effectiveness of the PLS method in the construction of calibration models was analyzed by a scientific approach based on a regulation vector. CBZ forms I and III were characterized by differential scanning calorimetry (DSC) and XRD. Powder mixtures of forms I and III at various ratios (0 -100% w/w; form III) were subjected to XRD. Five diffraction peaks were used for the peak-area method to compare with PLS. The results obtained by PLS had a better predictive accuracy compared to those of the peak-area method. The XRD-PLS method was established as a non-destructive, non-contact way to avoid the particle orientation effect based on statistical theory.

Chemometric Methods for the Quantification of Crystalline Tacrolimus in Solid Dispersion by Powder X‐Ray Diffractrometry

“…The pretreatment of the data with various mathematical methods did not improve the data as the primary source of data variation in XRPD is preferred crystal orientation and sample heterogeneity. The preferential crystal orientation could be prevented by reducing the crystal size and pressing the powder sample in the sample holder before measurement …”

Application of Partial Least-Squares (PLS) modeling in quantifying drug crystallinity in amorphous solid dispersions

“…Different experimental methods have been utilized to quantify the degree of crystallinity in pure API systems, or for quantification of the different crystalline phases present in polymorphic mixtures. Such methods include differential scanning calorimetry (DSC), infrared and Raman spectroscopy, and powder X-ray diffractometry (PXRD) (Clas et al, 1995;Taylor and Zografi, 1998;Pan et al, 2006;Shah et al, 2006;Seyer and Luner, 2001;Lehto et al, 2006;Bertacche et al, 2006;Bai et al, 2004;Yoshioka et al, 1994Yoshioka et al, , 1995Suda et al, 2008;Chieng et al, 2009). In addition, quantitative determination of crystalline API in the presence of other components has also been reported (Suryanarayanan and Herman, 1991;Moore et al, 2008Moore et al, , 2009).…”

Characterization of a Nonribosomal Peptide Antibiotic Solid Dispersion Formulation by Process Analytical Technologies Sensors

“…The source of this variation in NIR data is baseline shift and multiplicative scattering . Similarly, factors responsible for data variation in PXRD are nonhomogeneity of crystalline sample and preferential orientation of crystal in a sample holder …”