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The Analytical Scientist / Issues / 2025 / October / Raman on the Line for mAbs
Spectroscopy Pharma and Biopharma

Raman on the Line for mAbs 

Inline Raman spectroscopy has been demonstrated as a real-time tool for monitoring buffer exchange in monoclonal antibody formulation

10/14/2025 2 min read

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Credit: Monoclonal antibodies (2) by Linda Bartlett (Photographer), Public domain, via Wikimedia Commons

What?

Buffer exchange is a critical step in monoclonal antibody (mAb) manufacturing, ensuring proteins are transferred into stabilizing solutions that preserve structure and efficacy. Traditionally, this step has been tracked using offline assays such as HPLC and amino acid analysis – accurate, but slow and sample-intensive.

The new study shows that inline Raman spectroscopy can directly quantify excipients, including sucrose, histidine, mannitol, and hydroxypropyl-β-cyclodextrin (HPβCD), during adalimumab buffer exchange. By building Partial Least Squares (PLS) calibration models, the team achieved high predictive accuracy (R² values above 0.91) under real processing conditions.

 

Why?

Process control in biomanufacturing hinges on timely feedback. Delays in assessing buffer composition can increase the risk of protein aggregation, denaturation, or loss of therapeutic function. Raman spectroscopy – a non-destructive vibrational technique – provides a path to continuous, inline monitoring that aligns with Process Analytical Technology (PAT) and Quality by Design (QbD) principles.

By moving analysis in line, manufacturers could reduce turnaround times, minimize material waste, and improve overall robustness of therapeutic protein formulation.

How?

The researchers integrated a Raman probe (785 nm laser, stainless-steel flow cell) into a tangential flow filtration system for buffer exchange. They compared two calibration strategies:

  • Offline models built using prepared reference solutions

  • Placebo models built using inline data from protein-free runs
     

Both sets were validated during monoclonal antibody processing. Offline models showed the strongest calibration metrics, while placebo models proved more robust in real process conditions, especially for sugars such as sucrose and mannitol. Inline monitoring confirmed that concentration changes could be tracked in real time, with root mean square prediction errors kept low.

Who?

The work was carried out by Dorottya Vaskó and colleagues at the University of Pannonia, Hungary, and collaborators, with contributions from Edit Hirsch and Zsombor K. Nagy on supervision and conceptualization. The study appears in the International Journal of Pharmaceutics.

 

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