Discretized multi-level elution trajectory: A proof-of-concept demonstration

Sellberg, Anton; Holmqvist, Anders; Magnusson, Fredrik; Andersson, Christian; Nilsson, Bernt

doi:10.1016/j.chroma.2016.12.038

Cited by 15 publications

(5 citation statements)

References 30 publications

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“…In addition to pooling, there are not a lot of opportunities to control batch chromatography. An interesting approach is to control the gradient shape in batch chromatography to optimize resolution and binding capacity (Sellberg et al, 2017). The authors named it salt trajectory.…”

Section: Toward Real‐time Monitoring Control and Rtrtmentioning

confidence: 99%

Sensors and chemometrics in downstream processing

Dürauer

Jungbauer

Scharl

2023

Biotech & Bioengineering

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The biopharmaceutical industry is still running in batch mode, mostly because it is highly regulated. In the past, sensors were not readily available and in‐process control was mainly executed offline. The most important product parameters are quantity, purity, and potency, in addition to adventitious agents and bioburden. New concepts using disposable single‐use technologies and integrated bioprocessing for manufacturing will dominate the future of bioprocessing. To ensure the quality of pharmaceuticals, initiatives such as Process Analytical Technologies, Quality by Design, and Continuous Integrated Manufacturing have been established. The aim is that these initiatives, together with technology development, will pave the way for process automation and autonomous bioprocessing without any human intervention. Then, real‐time release would be realized, leading to a highly predictive and robust biomanufacturing system. The steps toward such automated and autonomous bioprocessing are reviewed in the context of monitoring and control. It is possible to integrate real‐time monitoring gradually, and it should be considered from a soft sensor perspective. This concept has already been successfully implemented in other industries and requires relatively simple model training and the use of established statistical tools, such as multivariate statistics or neural networks. This review describes a scenario for integrating soft sensors and predictive chemometrics into modern process control. This is exemplified by selective downstream processing steps, such as chromatography and membrane filtration, the most common unit operations for separation of biopharmaceuticals.

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Section: Toward Real‐time Monitoring Control and Rtrtmentioning

confidence: 99%

Sensors and chemometrics in downstream processing

Dürauer

Jungbauer

Scharl

2023

Biotech & Bioengineering

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show abstract

“…Besides pooling there are not a lot of opportunities to control batch chromatography. An interesting approach is to control the gradient shape in batch chromatography to optimize resolution and binding capacity (Sellberg et al, 2017). The authors named it salt trajectory.…”

Section: Impact Of Different Sensorsmentioning

confidence: 99%

Monitoring Product Quantity, Purity and Potency of Biopharmaceuticals in Real-time by Predictive Chemometrics and Soft sensors

Dürauer¹,

Jungbauer²,

Scharl

2023

Preprint

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The biopharmaceutical industry is still running in batch mode, mostly because it is a highly regulated industry sector. In the past, sensors were not readily available and in-process control was mainly executed off-line. The most important product parameters are quantity, purity and potency besides adventitious agents and bioburden. There is increasing economic pressure on time-to-market and also on the environmental sustainability of biopharmaceutical manufacturing. New concepts for manufacturing using disposable single-use technologies and integrated bioprocessing will dominate the future of bioprocessing. In order to ensure the quality of pharmaceuticals initiatives such as Process Analytical Technologies, Quality by Design and Continuous Integrated Manufacturing have been established. The vision must be that these initiatives together with technology development pave the way for process automation and autonomous bioprocessing without any human intervention. Then a real-time release would be realized leading to a highly predictive and robust biomanufacturing system. The steps toward such automated and autonomous bioprocessing are reviewed in context of monitoring and control. Starting from statistical treatment of single and multiple sensors, establishing soft sensors with predictive chemometrics and hybrid models. A scenario is described how to integrate soft sensors and predictive chemometrics into modern process control. This will be exemplified by selective downstream processing steps such as chromatography and membrane filtration, the most common unit operations for separation of biopharmaceuticals.

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“…This is especially computationally beneficial when considering large-scale dynamic optimization used e.g. to obtain discretized multi-level elution trajectories for high productivity and high yield batch chromatographic processes (Holmqvist and Magnusson (2016); Sellberg et al (2017)) or for global downstream optimization (Huuk et al (2014); Baumann et al (2015); Pirrung et al (2017)). It is also computationally advantageous when considering closed loop non-linear model predictive control (MPC) applications including state-estimation.…”

Section: Paper Objectivesmentioning

confidence: 99%

A stabilized nodal spectral solver for liquid chromatography models

Meyer

Huusom

Abildskov

2019

Computers & Chemical Engineering

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show abstract

Discretized multi-level elution trajectory: A proof-of-concept demonstration

Cited by 15 publications

References 30 publications

Sensors and chemometrics in downstream processing

Sensors and chemometrics in downstream processing

Monitoring Product Quantity, Purity and Potency of Biopharmaceuticals in Real-time by Predictive Chemometrics and Soft sensors

A stabilized nodal spectral solver for liquid chromatography models

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