A design space exploration for control of Critical Quality Attributes of mAb

Bhatia, Hemlata; Read, Erik K.; Agarabi, Cyrus; Brorson, Kurt; Lute, Scott; Yoon, Seongkyu

doi:10.1016/j.ijpharm.2016.08.046

Cited by 24 publications

(13 citation statements)

References 23 publications

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“…In summary the results of this study show that the combination of Raman spectroscopy with chemometrics models is a suitable method for real‐time measurement of amino acids in cell culture processes. The presented PAT platform can be seen as a step towards the real‐time monitoring and control of product quality attributes by regulating the amino acid feed in cell culture media . The developed models can be further optimized to reduce the errors.…”

Section: Discussionmentioning

confidence: 99%

In‐line monitoring of amino acids in mammalian cell cultures using raman spectroscopy and multivariate chemometrics models

Bhatia

Mehdizadeh

Drapeau

et al. 2017

Engineering in Life Sciences

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In-line monitoring of amino acids in mammalian cell cultures using raman spectroscopy and multivariate chemometrics modelsThe application of PAT for in-line monitoring of biopharmaceutical manufacturing operations has a central role in developing more robust and consistent processes. Various spectroscopic techniques have been applied for collecting real-time data from cell culture processes. Among these, Raman spectroscopy has been shown to have advantages over other spectroscopic techniques, especially in aqueous culture solutions. Measurements of several process parameters such as glucose, lactate, glutamine, glutamate, ammonium, osmolality and VCD using Ramanbased chemometrics models have been reported in literature. The application of Raman spectroscopy, coupled with calibration models for amino acid measurement in cell cultures, has been assessed. The developed models cover four amino acids important for cell growth and production: tyrosine, tryptophan, phenylalanine and methionine. The chemometrics models based on Raman spectroscopy data demonstrate the significant potential for the quantification of tyrosine, tryptophan and phenylalanine. The model for methionine would have to be further refined to improve quantification.

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Section: Discussionmentioning

confidence: 99%

In‐line monitoring of amino acids in mammalian cell cultures using raman spectroscopy and multivariate chemometrics models

Bhatia

Mehdizadeh

Drapeau

et al. 2017

Engineering in Life Sciences

Self Cite

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“…The initial CQA assessment will leverage literature, prior knowledge, and the target product profile to develop a preliminary set of CQAs and critical process parameters. During product development, as more knowledge is gathered for all quality attributes including the CQAs, the critical process parameters should be defined [183][184][185] and controlled to deliver a product that satisfies the intended target product profile.…”

Section: Discussionmentioning

confidence: 99%

Stress Factors in mAb Drug Substance Production Processes: Critical Assessment of Impact on Product Quality and Control Strategy

Das

Narhi

Sreedhara³

et al. 2020

Journal of Pharmaceutical Sciences

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The success of biotherapeutic development heavily relies on establishing robust production platforms. During the manufacturing process, the protein is exposed to multiple stress conditions that can result in physical and chemical modifications. The modified proteins may raise safety and quality concerns depending on the nature of the modification. Therefore, the protein modifications potentially resulting from various process steps need to be characterized and controlled. This commentary brings together expertise and knowledge from biopharmaceutical scientists and discusses the various manufacturing process steps that could adversely impact the quality of drug substance (DS). The major process steps discussed here are commonly used in mAb production using mammalian cells. These include production cell culture, harvest, antibody capture by protein A, virus inactivation, polishing by ion-exchange chromatography, virus filtration, ultrafiltration-diafiltration, compounding followed by release testing, transportation and storage of final DS. Several of these process steps are relevant to protein DS production in general. The authors attempt to critically assess the level of risk in each of the DS processing steps, discuss strategies to control or mitigate protein modification in these steps, and recommend mitigation approaches including guidance on development studies that mimic the stress induced by the unit operations.

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“…Ren et al (2019) have demonstrated the use of the K‐means clustering method to identify the similarities of historical pharmaceutical batches. Data‐driven advanced analytics for process modeling (Kornecki & Strube, 2019), process design space analysis (Bhatia et al, 2016), and the connection between CPPs and CQAs have been covered elsewhere (Sokolov et al, 2016; Sokolov et al, 2017).…”

Section: Data Automation Visualization and Smart Data Utilitymentioning

confidence: 99%

Technology outlook for real‐time quality attribute and process parameter monitoring in biopharmaceutical development—A review

Wasalathanthri

Rehmann

Song

et al. 2020

Biotech & Bioengineering

106

101

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Real‐time monitoring of bioprocesses by the integration of analytics at critical unit operations is one of the paramount necessities for quality by design manufacturing and real‐time release (RTR) of biopharmaceuticals. A well‐defined process analytical technology (PAT) roadmap enables the monitoring of critical process parameters and quality attributes at appropriate unit operations to develop an analytical paradigm that is capable of providing real‐time data. We believe a comprehensive PAT roadmap should entail not only integration of analytical tools into the bioprocess but also should address automated‐data piping, analysis, aggregation, visualization, and smart utility of data for advanced‐data analytics such as machine and deep learning for holistic process understanding. In this review, we discuss a broad spectrum of PAT technologies spanning from vibrational spectroscopy, multivariate data analysis, multiattribute chromatography, mass spectrometry, sensors, and automated‐sampling technologies. We also provide insights, based on our experience in clinical and commercial manufacturing, into data automation, data visualization, and smart utility of data for advanced‐analytics in PAT. This review is catered for a broad audience, including those new to the field to those well versed in applying these technologies. The article is also intended to give some insight into the strategies we have undertaken to implement PAT tools in biologics process development with the vision of realizing RTR testing in biomanufacturing and to meet regulatory expectations.

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A design space exploration for control of Critical Quality Attributes of mAb

Cited by 24 publications

References 23 publications

In‐line monitoring of amino acids in mammalian cell cultures using raman spectroscopy and multivariate chemometrics models

In‐line monitoring of amino acids in mammalian cell cultures using raman spectroscopy and multivariate chemometrics models

Stress Factors in mAb Drug Substance Production Processes: Critical Assessment of Impact on Product Quality and Control Strategy

Technology outlook for real‐time quality attribute and process parameter monitoring in biopharmaceutical development—A review

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