Currently, a problem with transmission Raman spectroscopy is that it can be compromised by the way light behaves inside a sample. Specifically, how near-infrared (NIR) photons scatter and are absorbed during their travel through the tablet matrix (1). The researchers sought to explore this problem at length in their study.
What did the researchers investigate in their study?
According to the researchers, differences in tablet thickness, porosity, and compaction force alter the optical paths of Raman photons. These changes introduce attenuation effects across the Raman spectrum, resulting in signal distortions that are not easily corrected using conventional normalization techniques like min-max scaling or standard normal variate (SNV) normalization (1).
In their experiments, the team studied single- and multi-component pharmaceutical tablets, systematically varying compaction forces and thicknesses to observe the resulting impact on TRS signal quality. They found that residual NIR absorption and photon scattering, which were both influenced by sample physical properties, were responsible for the observed spectral profile distortions (1). These effects varied across the Raman spectrum, meaning different regions of the signal were attenuated to different extents (1).
Significantly, the researchers demonstrated that the same physical dependence holds even at shorter TRS wavelengths (800–1000 nm), a spectral range frequently used in commercial TRS applications (1). This insight pointed to a generalizable underlying mechanism that affects TRS reliability across most operating conditions.
How did the researchers address this issue?
In their study, the researchers developed a basic spectral standardization method aimed at correcting for these distortions. When applied, the correction yielded measurable improvements in model performance. For instance, the root mean square error (RMSE) for the calibration set improved from 2.5% to 2.0%, while the residual bias between low and high compaction force test sets was virtually eliminated, dropping from 8.40% to nearly 0% (1). In the most extreme test case, the correction reduced the RMSE to just 23.87% of its original value (1).
What are the implications of this study?
The researchers note in their study that a current trend in the pharmaceutical industry is the pursuit of more efficient, real-time analytical methods under the Quality by Design (QbD) framework (1). As a result, ensuring the robustness of predictive models across varying manufacturing conditions becomes critical.
References
- Ryckaert, A.; Corujo, M. P.; Andrews, D.; et al. Impact and Mitigation of Near Infrared Absorption in Quantitative Transmission Raman Spectroscopy. J. Pharm. Biomed. Anal. 2025, 265, 117043. DOI: 10.1016/j.jpba.2025.117043
- Agilent Technologies, Transmission Raman Spectroscopy. Agilent. Available at: https://www.agilent.com/en/product/molecular-spectroscopy/raman-spectroscopy/transmission-raman-spectroscopy (accessed 2025-07-22).
