News|Videos|July 13, 2026

Rapid Rosuvastatin Quality Testing Using Raman Spectroscopy

Researchers at the University of Agriculture Faisalabad showed that Raman spectroscopy combined with chemometric modeling (PCA and PLSR) can accurately and non-destructively quantify rosuvastatin content in pharmaceutical tablets.

Recently, a research team at the University of Agriculture Faisalabad in Pakistan demonstrated the benefits of using Raman spectroscopy with chemometric modeling to characterize and quantify active pharmaceutical ingredients (APIs) in pharmaceuticals. In their study, the results of which were published in the journal Plasmonics, the research team used rosuvastatin as their example, highlighting how their method offers drug manufacturers a faster alternative to conventional testing methods.1

Has Raman spectroscopy been used in analyze active pharmaceutical ingredients often?

Raman spectroscopy has been used in several studies to analyze and quantify active pharmaceutical ingredients (APIs). Using this technique has only become more popular as drug analysis continues to change quickly. For example, multi-component drug formulations are becoming more ubiquitous.2,3 As a result, Raman spectroscopy is being routinely combined with chemometric modeling to adapt to these changes.

What did the researchers do in their study?

The researchers’ main objective was to address a practical need in the pharmaceutical industry: verifying that tablets containing rosuvastatin, which is a widely prescribed cholesterol-lowering drug used to manage dyslipidemia, contain the correct active ingredient concentration relative to their excipient content.1,4

Using Raman spectroscopy, the researchers collected spectral data from multiple rosuvastatin formulations containing varying ratios of active pharmaceutical ingredient (API) to excipients. They then applied two statistical techniques, principal component analysis (PCA) and partial least squares regression (PLSR), to distinguish genuine spectral variations tied to drug concentration from background noise introduced by the excipient matrix.1

Which model (PLSR or PCA) performed better?

The researchers found that PLSR was the better statistical technique. Their PLSR model performed with high accuracy, with a root mean square error of calibration of 0.95 milligrams and a root mean square error of prediction of 1.71 milligrams, alongside a goodness-of-fit value of 0.99.1 The model was subsequently used to estimate rosuvastatin concentrations in samples of unknown composition, correctly predicting drug content without requiring the sample destruction or extensive solvent use associated with standard techniques such as high-performance liquid chromatography (HPLC).1

What are the key takeaways from this article?

There are a couple key takeaways, both of which highlight the utility of Raman spectroscopy in pharmaceutical quality-control operations. First, because Raman spectroscopy is nondestructive and can deliver results quickly, the technique offers benefits such as a reduction of testing time and material waste during batch verification.1 The technique also avoids the need for extensive sample preparation, which is a common bottleneck in traditional assays.1

The authors conclude that Raman spectroscopy paired with PCA and PLSR modeling constitutes a reliable, reproducible approach for assessing rosuvastatin content across varied formulations.1

References
  1. Razaq, R.; Zulfiqar, A.; Majeed, M. I.; et al. Raman Spectroscopy and Chemometric Tools for the Qualitative and Quantitative Analysis of Pharmaceutical Formulations of Rosuvastatin. Plasmonics 2026, 21, 691–700. DOI: 10.1007/s11468-025-03050-z
  2. Wetzel, W. New Correction Technique Enhances Accuracy of Transmission Raman Spectroscopy in Pharmaceutical Quality Testing. Spectroscopy Online, 2026. https://www.spectroscopyonline.com/view/new-correction-technique-enhances-accuracy-of-transmission-raman-spectroscopy-in-pharmaceutical-quality-testing (accessed July 6, 2026).
  3. Wetzel, W. New Raman Spectroscopy Method Boosts Drug Component Detection Accuracy and Speed. Spectroscopy Online, 2026. https://www.spectroscopyonline.com/view/new-raman-spectroscopy-method-boosts-drug-component-detection-accuracy-and-speed (accessed July 6, 2026).
  4. Mayo Clinic, Rosuvastatin. Spectroscopy Online, 2026. https://www.mayoclinic.org/drugs-supplements/rosuvastatin-oral-route/description/drg-20065889 (accessed July 6, 2026).