Digital Butterworth filter as preprocessing method for implementing Raman spectroscopy as an analytical method in...

Area of Science:

• Analytical Chemistry
• Biopharmaceutical Analysis
• Spectroscopy

Background:

• Raman spectroscopy faces challenges in biopharmaceutical downstream processing due to spectral variations.
• Accurate molecular information extraction is hindered by spectrometer, setup, and fluorescence interferences.

Purpose of the Study:

• To explore the Butterworth filter for baseline correction and noise reduction in Raman spectra.
• To optimize Butterworth filter parameters for enhanced biopharmaceutical analysis.
• To develop chemometric models for predicting Critical Quality Attributes (CQAs).

Main Methods:

• Investigated Butterworth highpass and bandpass filters for spectral preprocessing.
• Optimized cutoff frequencies (ωc) to minimize baseline variations and maximize linear correlation (r²) with protein concentrations.
• Developed and validated chemometric models using preprocessed Raman data.

Main Results:

• Optimal Butterworth highpass filter (ωc: 0.004-0.008 cm) achieved r² ≥ 0.85, outperforming Savitzky-Golay filter (r²=0.68).
• Butterworth bandpass filter showed 11.6-15% improvement in r² over the highpass design.
• Validated chemometric models predicted IgG (R²=0.99) and Transferrin (R²=0.95) concentrations accurately in Cation Exchange Chromatography.

Conclusions:

• The Butterworth filter is a robust preprocessing tool for Raman spectroscopy in biopharmaceutical analysis.
• Optimized cutoff frequency selection is crucial for bandpass filter application.
• The developed method enables reliable in-line prediction of CQAs for biopharmaceuticals.