Simultaneous automated image analysis and Raman spectroscopy of powders at an individual particle level

Sekulovic A, Verrijk R, Rades T, Grabarek A, Jiskoot W, Hawe A and Rantanen J.


  • We report the combination of image analysis and Raman spectroscopy for exploring the solid form diversity of powder samples
  • This approach is based on the measurement at an individual particle level of high number of particles
  • The efficient data analysis based on multivariate methods enables visualization of the classification of a high number of particles
  • Method with potential for exploring low amounts of solid form impurities in fine chemicals, especially with particulate pharmaceuticals


Solid form diversity of raw materials can be critical for the performance of the final drug product. In this study, Raman spectroscopy, image analysis and combined Raman and image analysis were utilized to characterize the solid form composition of a particulate raw material. Raman spectroscopy provides chemical information and is complementary to the physical information provided by image analysis. To demonstrate this approach, binary mixtures of two solid forms of carbamazepine with a distinct shape, an anhydrate (prism shaped) and a dihydrate (needle shaped), were characterized at an individual particle level. Partial least squares discriminant analysis classification models were developed and tested with known, gravimetrically mixed test samples, followed by analysis of unknown, commercially supplied carbamazepine raw material samples. Classification of several thousands of particles was performed, and it was observed that with the known binary mixtures, the minimum number of particles needed for the combined Raman spectroscopy – image analysis classification model was approximately 100 particles per solid form. The carbamazepine anhydrate and dihydrate particles were detected and classified with a classification error of 1 % using the combined model. Further, this approach allowed the identification of raw material solid form impurity in unknown raw material samples. Simultaneous automated image analysis and Raman spectroscopy of powders at an individual particle level has its potential in accurate detection of low amounts of unwanted solid forms in particulate raw material samples.

Journal of Pharmaceutical and Biomedical Analysis 2020 Nov