An NIR‐based PAT approach for real‐time control of loading in Protein A chromatography in continuous manufacturing of monoclonal antibodies

Abstract

Control of column loading in Protein A chromatography is a crucial part of development of robust and flexible process platforms for continuous production of monoclonal antibody (mAb) products. In this paper, we propose a control system that uses near infrared spectroscopy (NIRS) flow cells to accomplish the above. Two applications have been demonstrated using a periodic counter-current continuous chromatography setup. The first application involves use of single NIR flow cell before the inlet of the loading column to measure the concentration of mAb in the harvested broth. Measurement was in real-time (every 3 s) and within ±0.05 mg/ml, significantly better than making UV-based concentration estimations. The second application involved use of an additional NIR flow cell at the outlet of the loading column to measure column breakthrough in real time. The concentration data was transferred to a Python-based monitoring and control algorithm layered over a Cadence BioSMB system. The program could successfully run a three-column periodic counter current method on the BioSMB whereas controlling loading to ensure optimal resin utilization in each loading cycle phase based on precharacterized dynamic binding capacity models, whereas maintaining periodic elutions. The system was tested with multiple perturbations in harvest concentration, modeled after deviations that could arise downstream of a perfusion cell culture system. The resultsshow that the proposed control is a spectroscopy-based process analytical technology tool that facilitates real time monitoring and control of loading in process chromatography. It is adaptable to any continuous chromatography equipment and is very well suited for implementation in a continuous mAb production train.

A multisensor approach for improved protein A load phase monitoring by conductivity‐based background subtraction of UV spectra

“…In this study, a multisensor approach for real-time monitoring of the load phase in a protein A capture step was presented and compared to other We conclude that UV-based methods, especially with background subtraction, yield better prediction accuracies than NIR-or Raman-based methods judged by the RMSEPs published in other publications (Feidl, Garbellini, Luna, et al, 2019;Thakur et al, 2019). The application of the background subtraction to product concentration determination with only one absorption wavelength shows great potential for the application to production processes as the required sensors are already implemented in most processes.…”

“…To set the results of this study into perspective to recent publications, the results are compared to the obtained results by (Thakur et al, 2019) for the usage of NIR spectroscopy to monitor the breakthrough and to the results by (Feidl, Garbellini, Vogg, et al, 2019) for the usage of Raman spectroscopy. As these studies were carried out on different data set and different steps for model optimization were undertaken, a final conclusion cannot be drawn by solely comparison of the results.…”

“…Thakur et al (2019) published an RMSEP for the breakthrough experiments in their publication of 0.1540 g for NIR spectroscopy in combination with PLS models. This error is almost 10‐fold higher than the RMSEP of 0.0186 g for the model with background subtraction from this article.…”

High-Throughput Raman Spectroscopy Combined with Innovate Data Analysis Workflow to Enhance Biopharmaceutical Process Development

“…Other spectroscopic methods have been described in relation to DSP, such as mid (MIR) and near (NIR) infrared spectroscopy. NIR was used to determine mAb concentration in real-time, enabling the dynamic loading of protein A chromatography [37]. Capito et al used MIR to monitor product concentration, aggregate, and HCP content, although this was developed as an at-line method, as the samples were processed (dried) prior to measurements [38], limiting the use of the tool for on-line monitoring.…”

Evaluation of temperature compensation methods for a near‐infrared calibration to predict the viscosity of micellar liquids

“…Near‐infrared (NIR) spectroscopy has proven to be a successful analytical tool in measuring chemical and physical properties in‐line due to its non‐destructive nature, speed of analysis and ease of implementation in manufacturing environments 1–9 . Though NIR spectroscopy has low selectivity, it can be combined with multivariate modelling techniques such as principal component analysis (PCA) or partial least squares (PLS) to extract the relevant information and develop predictive models.…”