Process Analytical Technology Application for Protein PEGylation Using near Infrared Spectroscopy: G‐CSF as a Case Study
Abstract
Conjugation of protein therapeutics with polymers like polyethylene glycol (PEG) has been shown to increase their therapeutic efficiency. However, manufacturing of PEGylated drugs requires an additional, carefully controlled reaction step after purifying the protein, followed by further purification of over- and under-PEGylated variants. In this work, we have used a combined spectroscopic and statistical approach for monitoring and control of the PEGylation reaction for G-CSF using near infrared spectroscopy (NIRS). An online NIRS probe deployed in the reaction vessel has been used to track conversion of G-CSF into monoPEGylated and multiPEGylated forms using calibrated partial least squares regression models on the NIRS spectra which are collected in real time every 3 s. A pH probe integrated with a peristaltic pump facilitates automated quenching of the reaction at the targeted time. The NIRS spectra have also been used to build a batch evolution model for the reaction from end-to-end, including the addition of the reactants to the reaction vessel, the progress of the reaction for 70 min, and the final quenching with Tris base. Online spectra are compared against the statistical process control charts of the batch evolution model in real time to detect deviations as soon as they occur. The system was demonstrated for four common deviations in the PEGylation process, namely: delayed quenching time, wrong concentration of reducing agent added, wrong PEG to G-CSF ratio, and wr…
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NIR has been employed in an on-line setup to monitor PEGylation of proteins, with spectra collected in real time every 3 s followed by model building for information extraction and process control.
“NIRs have been employed in an on‐line setup to monitor the PEGylation of proteins, which is an important quality attribute to monitor during the downstream processing of conjugated proteins. NIRS spectra were collected in real time for every 3 s, which was then followed by model building for information extraction and process control [62].”
From Current PAT Landscape in the Downstream Processing of Biopharmaceuticals (2025) · cites this paper as [62]
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Current PAT Landscape in the Downstream Processing of Biopharmaceuticals
Sathiyapriyan, P., Mukherjee, S., Vogel, T., Essen, L., Boerema, D., Vey, M., & Kalina, U. (2025) · Analytical Science Advances · doi:10.1002/ansa.70013 · Cited by 45 · see citing works
- Authors
- Hebbi, V., Thakur, G., & Rathore, A. S.
- ORCID
- Rathore, Anurag S.
- Venue
- Journal of Biotechnology
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 325
- Pages
- 303-311
- ISSN
- 0168-1656
- Cited by
- 9
- References
- 1
- Language
- en
- Funders
- Department of Science and Technology, Ministry of Science and Technology, India
- Council of Scientific and Industrial Research, India
- Department of Biotechnology, Ministry of Science and Technology, India
- Tata Consultancy Services
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