Raman Observation of Crystalline Polymorphs in a Medicinal Substance
Raman image(left) and optical microscopic image(right) of crystalline polymorphs of mefenamic acids
Only 20 minutes shows the imaging of distribution in crystalline polymorphs
The image above shows the distribution of the mixture of two mefenamic acids with different crystal forms obtained by high speed and high resolution Raman imaging. The distribution of crystal form I and crystal form II are shown in red and green respectively. The Raman image of 0.5mm square field of view is measured in about 20 minutes with the spatial resolution of about 700nm.
About the sample used for measurement
In this measurement, the crystalline polymorphs of the mefenamic acids, which have anti-inflammation, relieving pain and antipyretic effect, are analyzed by Raman spectroscopy. Because the medicinal effect varied with the difference of crystal form of chemical components, the control of crystal form is a key problem in medicine manufacture process. As an analysis technique for identifying crystal form, there’re X-ray diffraction and Raman spectroscopy. Raman spectroscopy has been used for screening usage because of the handiness with an unnecessary preparation for the vacuum.
Molecular structure of mefenamic acid
The Raman spectrum analysis of crystalline polymorphs of mefenamic acids
The right hand side figure shows the Raman spectra of crystalline polymorphs of mefenamic acids. In general, the difference of crystal forms can be identified from the difference of Raman spectra. For mefenamic acid, though the position of each Raman peak is almost the same and hard to identify each crystal pattern by this, identification and distribution analyses on each crystal form become possible by using the principal component analysis that is one of the multivariate analysis techniques.
(Reference)About Raman spectrum analysis
One of the multivariate analysis techniques-the principal component analysis is a technique for separating two or more component spectra included in the imaging data by using the spectra as multidimensional data of intensity and wavenumber, and modeling it. In that case, it is also possible to remove the noise by using the difference between the degree factor of spectrum signal and the noise’, and restructuring the data with the factors of few noises.
Overwhelming power of RAMAN-11 is demonstrated to detect the medicine crystal polymorphs deposited by micro order, by combining the spatial resolution of 350 nm, the super-high-speed imaging function with the line illumination and the principal component analysis.
