Impact and mitigation of near infrared absorption in quantitative Transmission Raman Spectroscopy

Area of Science:

• Analytical Chemistry
• Pharmaceutical Sciences
• Spectroscopy

Background:

• Transmission Raman Spectroscopy (TRS) is used for pharmaceutical content uniformity analysis.
• Physical-chemical stressors like compaction force and thickness variations can distort spectral profiles.
• These distortions introduce systematic errors in quantitative models.

Purpose of the Study:

• To investigate the impact of thickness, porosity, and compaction force variations on quantitative model predictions.
• To propose a spectral standardization technique to mitigate these effects.

Main Methods:

• Utilized Transmission Raman Spectroscopy for sample analysis.
• Varied sample thickness, porosity, and compaction force.
• Developed and applied a spectral standardization technique.
• Evaluated model performance using statistical metrics like RMSE and bias.

Main Results:

• Observed significant improvements in quantitative model performance.
• Reduced Root Mean Square Error (RMSE) from 2.5% to 2.0% for the overall model.
• Nearly eliminated bias related to compaction force variations (from 8.40% to ~0%).
• Significantly reduced residuals (RMSE from 8.63% to 2.06%).

Conclusions:

• Spectral standardization effectively corrects for physical-chemical stressors in pharmaceutical samples analyzed by TRS.
• The proposed technique enhances the predictive capability and reliability of quantitative models.
• This method improves the accuracy of active pharmaceutical ingredient and excipient quantification.