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Updated: Sep 26, 2025

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
Published on: November 8, 2019
Application of Online NIR Spectroscopy to Enhance Process Understanding and Enable In-process Control Testing of
Craig Ikeda1, George Zhou1, Yung-Chi Lee1
1Merck & Co., Inc., Kenilworth, NJ, USA.
Near infrared spectroscopy (NIRS) effectively monitors spray-dried intermediates
Area of Science:
- Pharmaceutical Manufacturing
- Process Analytical Technology (PAT)
- Spectroscopy
Background:
- Spray drying is a critical process for producing pharmaceutical intermediates.
- Secondary drying requires precise endpoint determination to ensure product quality.
- Traditional off-line testing for residual solvents and assay is time-consuming and labor-intensive.
Purpose of the Study:
- To implement Near Infrared Spectroscopy (NIRS) for real-time monitoring of the secondary drying process.
- To develop NIRS methods for quantifying residual solvents (acetone, water) and API assay in spray-dried intermediates.
- To validate and transfer these NIRS methods to a commercial scale.
Main Methods:
- Utilized Near Infrared Spectroscopy (NIRS) for in-line process monitoring.
- Developed calibration models using Partial Least Squares (PLS) regression.
- Validated NIRS methods for residual solvents and API assay with low Standard Errors of Prediction (SEP).
- Transferred and updated NIRS methods to commercial-scale equipment at a different site.
Main Results:
- Achieved accurate quantification of residual acetone (SEP: 0.1 wt. %), water (SEP: 0.2 wt. %), and API potency (SEP: 3.0 mg API/g SDI).
- Successfully transferred NIRS methods to commercial scale, demonstrating robustness across different instrumentation and sites.
- Enabled real-time, in-process release and improved data consistency by minimizing sample handling.
Conclusions:
- NIRS is a viable technology for real-time monitoring and control of secondary drying in spray-dried intermediates.
- NIRS methods reduce reliance on off-line testing, improving efficiency and data quality.
- These NIRS methods offer potential for optimizing drying cycle times and understanding process parameter impacts.
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