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Continuous background correction of refractive index signal to improve monoclonal antibody concentration monitoring during UF/DF and SPTFF operations. Bioprocess Biosyst Eng 2022; 45:647-657. [PMID: 34989873 DOI: 10.1007/s00449-021-02683-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 12/12/2021] [Indexed: 11/02/2022]
Abstract
Inline refractive index (RI) has the potential for monitoring protein concentration during final bulk concentration. While useful for monitoring and controlling product concentration, RI is sensitive to the respective background buffer being used for processing. This raises concerns around variations in buffer preparations, and during diafiltration where the buffer background is a mixture of different buffers during exchange. This study evaluated whether the use of a RI probe in the permeate line could facilitate continuous background subtraction (dual RI) and improve concentration monitoring during ultrafiltration/diafiltration and single pass TFF concentration for IgG1 and IgG4 antibodies. The proposed dual RI strategy yielded reductions in % error compared to the use of a single refractive index estimate from the retentate line (6.18% vs 8.63% for IgG4 and 2.65% vs 8.85% for IgG1) during traditional ultrafiltration/diafiltration. The improvement in IgG estimates were best during diafiltration where the continuous background subtraction of the permeate RI-enabled continuous monitoring of antibody material without knowledge of what the background buffer was compared to the use of a single RI estimate (6.47% vs 10.79% for IgG4 and 3.29% vs 19.59% for IgG1). In contrast minimal improvement to accuracy was obtained when using SPTFF as a concentration step. The ability to monitor product concentration changes via the proposed dual RI approach removes the need for complex calibrations, minimal worry about changing buffer backgrounds during diafiltration, and could enable better process control during product concentration in the cGMP manufacture of biologics.
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Harris SA, Patel BA, Gospodarek A, Desai J, de Janon Gutiérrez A, Botonjic-Sehic E, Brower M, Pinto NDS. Determination of protein concentration in downstream biomanufacturing processes by in-line index of refraction. Biotechnol Prog 2021; 37:e3187. [PMID: 34164947 DOI: 10.1002/btpr.3187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 06/04/2021] [Accepted: 06/18/2021] [Indexed: 11/07/2022]
Abstract
Protein concentration determination is a necessary in-process control for the downstream operations within biomanufacturing. As production transitions from batch mode to an integrated continuous bioprocess paradigm, there is a growing need to move protein concentration quantitation from off-line to in-line analysis. One solution to fulfill this process analytical technology need is an in-line index of refraction (IoR) sensor to measure protein concentration in real time. Here the performance of an IoR sensor is evaluated through a series of experiments to assess linear response, buffer matrix effects, dynamic range, sensor-to-sensor variability, and the limits of detection and quantitation. The performance of the sensor was also tested in two bioprocessing scenarios, ultrafiltration and capture chromatography. The implementation of this in-line IoR sensor for real-time protein concentration analysis and monitoring has the potential to improve continuous bioprocess manufacturing.
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Affiliation(s)
- Steven A Harris
- Analytics Group, Digital Innovation Program, Central Technology Organization, Pall Corporation, Westborough, Massachusetts, USA
| | - Bhumit A Patel
- Analytical Research and Development, Merck & Co., Inc., Kenilworth, New Jersey, USA
| | - Adrian Gospodarek
- Biologics Process Research and Development, Merck & Co., Inc., Kenilworth, New Jersey, USA
| | - Jayesh Desai
- Analytical Research and Development, Merck & Co., Inc., Kenilworth, New Jersey, USA
| | | | - Edita Botonjic-Sehic
- Analytics Group, Digital Innovation Program, Central Technology Organization, Pall Corporation, Westborough, Massachusetts, USA
| | - Mark Brower
- Biologics Process Research and Development, Merck & Co., Inc., Kenilworth, New Jersey, USA
| | - Nuno D S Pinto
- Biologics Process Research and Development, Merck & Co., Inc., Kenilworth, New Jersey, USA
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