Applications of bio-capacitance to cell culture manufacturing

Bergin, Adam; Carvell, John; Butler, Michael

doi:10.1016/j.biotechadv.2022.108048

Cited by 15 publications

(7 citation statements)

References 95 publications

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“…In contrast, in line with the process analytical technology (PAT) initiative, 21,22 In‐Situ monitoring tools like near‐infrared, Raman, and capacitance probes are favored for their nondestructive and timely monitoring capabilities. Their applications have been widely reported in various pharmaceutical unit operations 23–28 . Among them, capacitance spectroscopy measures cells directly through the intact plasma membrane 26 .…”

Section: Introductionmentioning

confidence: 99%

“…Their applications have been widely reported in various pharmaceutical unit operations. [23][24][25][26][27][28] Among them, capacitance spectroscopy measures cells directly through the intact plasma membrane. 26 Proportional to the total membrane area within the electric field, the capacitance signal reflected the viable biomass and was reported to control feeding, inoculation, and perfusion.…”

mentioning

confidence: 99%

“…[23][24][25][26][27][28] Among them, capacitance spectroscopy measures cells directly through the intact plasma membrane. 26 Proportional to the total membrane area within the electric field, the capacitance signal reflected the viable biomass and was reported to control feeding, inoculation, and perfusion. [29][30][31] However, the correlation between the capacitance signal and biomass is disrupted when the viability declines.…”

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confidence: 99%

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Adaptive modeling optimized by the data fusion strategy: Real‐time dying cell percentage prediction using capacitance spectroscopy

Wu,

Ketcham,

Corredor

et al. 2024

Biotechnology Progress

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The previous research showcased a partial least squares (PLS) regression model accurately predicting cell death percentages using in‐line capacitance spectra. The current study advances the model accuracy through adaptive modeling employing a data fusion approach. This strategy enhances prediction performance by incorporating variables from the Cole–Cole model, conductivity and its derivatives over time, and Mahalanobis distance into the predictor matrix (X‐matrix). Firstly, the Cole–Cole model, a mechanistic model with parameters linked to early cell death onset, was integrated to enhance prediction performance. Secondly, the inclusion of conductivity and its derivatives over time in the X‐matrix mitigated prediction fluctuations resulting from abrupt conductivity changes during process operations. Thirdly, Mahalanobis distance, depicting spectral changes relative to a reference spectrum from a previous time point, improved model adaptability to independent test sets, thereby enhancing performance. The final data fusion model substantially decreased root‐mean squared error of prediction (RMSEP) by around 50%, which is a significant boost in prediction accuracy compared to the prior PLS model. Robustness against reference spectrum selection was confirmed by consistent performance across various time points. In conclusion, this study illustrates that the data fusion strategy substantially enhances the model accuracy compared to the previous model relying solely on capacitance spectra.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Adaptive modeling optimized by the data fusion strategy: Real‐time dying cell percentage prediction using capacitance spectroscopy

Wu,

Ketcham,

Corredor

et al. 2024

Biotechnology Progress

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“…For instance, biocapacitance probes, such as those offered by Aber and Hamilton, can be inserted into the sampling ports of large-scale stirred bioreactors (>250 mL). [14][15][16][17][18] These larger probes are not well-suited for use in small reactors. For some smaller bioreactors, electric cell-substrate impedance (ECIS) technology, such as the real time cell analyzer (xCELLigence) can be used to measure adhesion, transendothelial electrical resistance, and growth progression of adherent monolayers.…”

Section: Introductionmentioning

confidence: 99%

Single-use, Metabolite Absorbing, Resonant Transducer (SMART) culture vessels for label-free, continuous cell culture progression monitoring

Chan,

Dileep,

Rothstein

et al. 2024

Preprint

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Secreted metabolites are an important class of bio-process analytical technology (PAT) targets that can correlate to cell condition. However, current strategies for measuring metabolites are limited to discrete measurements, resulting in limited understanding and ability for feedback control strategies. Herein, we demonstrated a continuous metabolite monitoring strategy using a single-use metabolite absorbing resonant transducer (SMART) to correlate with cell growth. Polyacrylate was shown to absorb secreted metabolites from living cells containing hydroxyl and alkenyl groups such as terpenoids, that act as a plasticizer. Upon softening, the polyacrylate irreversibly conformed into engineered voids above a resonant sensor, changing the local permittivity which is interrogated, contact-free, with a vector network analyzer. Compared to sensing using the intrinsic permittivity of cells, the SMART approach yields a 20-fold improvement in sensitivity. Tracking growth of many cell types such as Chinese hamster ovary, HEK293, K562, HeLa, and E. coli cells as well as perturbations in cell proliferation during drug screening assays were demonstrated. The sensor was benchmarked to show continuous measurement over six days, ability to track different growth conditions, selectivity to transducing active cell growth metabolites against other components found in the media, and feasibility to scale out for high throughput campaigns.

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“…To overcome the lack of inline and real-time sensors, spectroscopicbased technologies with process probe interfaces are being evaluated to monitor cell growth. They have the advantage of being non-invasive, non-destructive, offer rapid, and frequent analysis, and are based on dielectric, [9][10][11] near infrared, [12] or Raman spectroscopies. [13,14] To date, these technologies are typically used for online monitoring of viable cell concentration (VCC) or compounds in the culture media.…”

Section: Introductionmentioning

confidence: 99%

Influence of cell specific parameters in a dielectric spectroscopy conversion model used to monitor viable cell density in bioreactors

Schini,

De Canditiis,

Sanchez

et al. 2023

Biotechnology Journal

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In the biopharmaceutical industry, the use of mammalian cells to produce therapeutic proteins is becoming increasingly widespread. Monitoring of these cultures via different analysis techniques is essential to ensure a good quality product while respecting good manufacturing practice (GMP) regulations. PAT (Process Analytical Technologies) tools provide real‐time measurements of the physiological state of the culture and enable process automation. Dielectric spectroscopy is a PAT that can be used to monitor the viable cell concentration of living cells (VCC) after processing raw permittivity data. Several modeling approaches exist and estimate biomass with different accuracy. The accuracy of the Cole‐Cole and Maxwell Wagner's equations are studied here in the determination of the VCC and cell radius in Chinese hamster ovary (CHO) culture. A sensitivity analysis performed on the parameters entering the equations highlighted the importance of the cell specific parameters such as internal conductivity (σi) and membrane capacitance (Cm) in the accuracy of the estimation of VCC and cell radius. The most accurate optimization method found to improve the accuracy involves in‐process adjustments of Cm and σi in the model equations with samplings from the bioreactor. This combination of offline and in situ data improved the estimation precision of the viable cell concentration by 69% compared to a purely mechanistic model without offline adjustments.This article is protected by copyright. All rights reserved

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Applications of bio-capacitance to cell culture manufacturing

Cited by 15 publications

References 95 publications

Adaptive modeling optimized by the data fusion strategy: Real‐time dying cell percentage prediction using capacitance spectroscopy

Adaptive modeling optimized by the data fusion strategy: Real‐time dying cell percentage prediction using capacitance spectroscopy

Single-use, Metabolite Absorbing, Resonant Transducer (SMART) culture vessels for label-free, continuous cell culture progression monitoring

Influence of cell specific parameters in a dielectric spectroscopy conversion model used to monitor viable cell density in bioreactors

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