huong le

Artifacts, Tools, and Classrooms

Mind, Culture, and Activity, 2005

... | Ayuda. Artifacts, Tools, and Classrooms. Autores: Valerie Podmore, Huong Le, Geraldine McDo... more

Advancing biopharmaceutical process science through transcriptome analysis

Current Opinion in Biotechnology, 2014

Global survey of transcriptome dynamics can provide molecular insights into cell physiology. In t... more Global survey of transcriptome dynamics can provide molecular insights into cell physiology. In the past few years, DNA microarray for transcriptome analysis has been augmented by high-throughput sequencing methods; extending the reach of transcriptome analysis to the rodent species of biotechnological importance, for which the development of genomic tools has been lagging. The rapid accumulation of sequencing data for these species highlighted the need for more evidence-based annotation. Recent findings in the epigenetic regulation in human and mouse will inspire similar research in CHO and BHK cells. Transcriptome studies in these recombinant cells will likely lay the foundation for a systems-based genome engineering which can be used to develop superior producing cell lines. Herein, we summarized the recent findings and advances in transcriptome studies of cell culture bioprocesses. The potential impact of transcriptomics on biopharmaceutical process technology is also discussed.

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Transcriptome Data Analysis for Cell Culture Processes

Genomics and Systems Biology of Mammalian Cell Culture, 2011

In the past decade, DNA microarrays have fundamentally changed the way we study complex biologica... more In the past decade, DNA microarrays have fundamentally changed the way we study complex biological systems. By measuring the expression levels of thousands of transcripts, the paradigm of studying organisms has shifted from focusing on the local phenomena of a few genes to surveying the whole genome. DNA microarrays are used in a variety of ways, from simple comparisons between two samples to more intricate time-series studies. With the large number of genes being studied, the dimensionality of the problem is inevitably high. The analysis of microarray data thus requires specific approaches. In the case of time-series microarray studies, data analysis is further complicated by the correlation between successive time points in a series.In this review, we survey the methodologies used in the analysis of static and time-series microarray data, covering data pre-processing, identification of differentially expressed genes, profile pattern recognition, pathway analysis, and network reconstruction. When available, examples of their use in mammalian cell cultures are presented.

Multivariate analysis of cell culture bioprocess data—Lactate consumption as process indicator

Journal of Biotechnology, 2012

Multivariate analysis of cell culture bioprocess data has the potential of unveiling hidden proce... more Multivariate analysis of cell culture bioprocess data has the potential of unveiling hidden process characteristics and providing new insights into factors affecting process performance. This study investigated the time-series data of 134 process parameters acquired throughout the inoculum train and the production bioreactors of 243 runs at the Genentech's Vacaville manufacturing facility. Two multivariate methods, kernel-based support vector regression (SVR) and partial least square regression (PLSR), were used to predict the final antibody concentration and the final lactate concentration. Both product titer and the final lactate level were shown to be predicted accurately when data from the early stages of the production scale were employed. Using only process data from the inoculum train, the prediction accuracy of the final process outcome was lower; the results nevertheless suggested that the history of the culture may exert significant influence on the final process outcome. The parameters contributing most significantly to the prediction accuracy were related to lactate metabolism and cell viability in both the production scale and the inoculum train. Lactate consumption, which occurred rather independently of the residual glucose and lactate concentrations, was shown to be a prominent factor in determining the final outcome of production-scale cultures. The results suggest possible opportunities to intervene in metabolism, steering it towards the type with a strong propensity towards high productivity. Such intervention could occur in the inoculum stage or in the early stage of the production-scale reactors. Overall, this study presents pattern recognition as an important process analytical technology (PAT). Furthermore, the high correlation between lactate consumption and high productivity can provide a guide to apply quality by design (QbD) principles to enhance process robustness.

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Mining manufacturing data for discovery of high productivity process characteristics

Journal of Biotechnology, 2010

Modern manufacturing facilities for bioproducts are highly automated with advanced process monito... more Modern manufacturing facilities for bioproducts are highly automated with advanced process monitoring and data archiving systems. The time dynamics of hundreds of process parameters and outcome variables over a large number of production runs are archived in the data warehouse. This vast amount of data is a vital resource to comprehend the complex characteristics of bioprocesses and enhance production robustness. Cell culture process data from 108 ‘trains’ comprising production as well as inoculum bioreactors from Genentech's manufacturing facility were investigated. Each run constitutes over one-hundred on-line and off-line temporal parameters. A kernel-based approach combined with a maximum margin-based support vector regression algorithm was used to integrate all the process parameters and develop predictive models for a key cell culture performance parameter. The model was also used to identify and rank process parameters according to their relevance in predicting process outcome. Evaluation of cell culture stage-specific models indicates that production performance can be reliably predicted days prior to harvest. Strong associations between several temporal parameters at various manufacturing stages and final process outcome were uncovered. This model-based data mining represents an important step forward in establishing a process data-driven knowledge discovery in bioprocesses. Implementation of this methodology on the manufacturing floor can facilitate a real-time decision making process and thereby improve the robustness of large scale bioprocesses.

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Transcriptome dynamics of transgene amplification in Chinese hamster ovary cells

Biotechnology and Bioengineering, 2014

Dihydrofolate reductase (DHFR) system is used to amplify the product gene to multiple copies in C... more Dihydrofolate reductase (DHFR) system is used to amplify the product gene to multiple copies in Chinese Hamster Ovary (CHO) cells for generating cell lines which produce the recombinant protein at high levels. The physiological changes accompanying the transformation of the non-protein secreting host cells to a high producing cell line is not well characterized. We performed transcriptome analysis on CHO cells undergoing the selection and amplification processes. A host CHO cell line was transfected with a vector containing genes encoding the mouse DHFR (mDHFR) and a recombinant human IgG (hIgG). Clones were isolated following selection and subcloned following amplification. Control cells were transfected with a control plasmid which did not have the hIgG genes. Although methotrexate (MTX) amplification increased the transcript level of the mDHFR gene significantly, its effect on both hIgG heavy and light chain genes was more modest. The subclones appeared to retain the transcriptome signatures of their parental clones, however, their productivity varied among those derived from the same clone. The transcript levels of hIgG transgenes of all subclones fall in a narrower range than the product titer, alluding to the role of many functional attributes, other than transgene transcript, on productivity. We cross examined functional class enrichment during selection and amplification as well as between high and low producers and discerned common features among them. We hypothesize that the role of amplification is not merely increasing transcript levels, but also enriching survivors which have developed the cellular machinery for secreting proteins, leading to an increased frequency of isolating highproducing clones. We put forward the possibility of assembling a hyper-productivity gene set through comparative transcriptome analysis of a wide range of samples.

Download

Advancing biopharmaceutical process science through transcriptome analysis

Current Opinion in Biotechnology, 2014

Global survey of transcriptome dynamics can provide molecular insights into cell physiology. In t... more Global survey of transcriptome dynamics can provide molecular insights into cell physiology. In the past few years, DNA microarray for transcriptome analysis has been augmented by high-throughput sequencing methods; extending the reach of transcriptome analysis to the rodent species of biotechnological importance, for which the development of genomic tools has been lagging. The rapid accumulation of sequencing data for these species highlighted the need for more evidence-based annotation. Recent findings in the epigenetic regulation in human and mouse will inspire similar research in CHO and BHK cells. Transcriptome studies in these recombinant cells will likely lay the foundation for a systems-based genome engineering which can be used to develop superior producing cell lines. Herein, we summarized the recent findings and advances in transcriptome studies of cell culture bioprocesses. The potential impact of transcriptomics on biopharmaceutical process technology is also discussed.

Download

Transcriptome Data Analysis for Cell Culture Processes

Genomics and Systems Biology of Mammalian Cell Culture, 2011

In the past decade, DNA microarrays have fundamentally changed the way we study complex biologica... more In the past decade, DNA microarrays have fundamentally changed the way we study complex biological systems. By measuring the expression levels of thousands of transcripts, the paradigm of studying organisms has shifted from focusing on the local phenomena of a few genes to surveying the whole genome. DNA microarrays are used in a variety of ways, from simple comparisons between two samples to more intricate time-series studies. With the large number of genes being studied, the dimensionality of the problem is inevitably high. The analysis of microarray data thus requires specific approaches. In the case of time-series microarray studies, data analysis is further complicated by the correlation between successive time points in a series.In this review, we survey the methodologies used in the analysis of static and time-series microarray data, covering data pre-processing, identification of differentially expressed genes, profile pattern recognition, pathway analysis, and network reconstruction. When available, examples of their use in mammalian cell cultures are presented.

Multivariate analysis of cell culture bioprocess data—Lactate consumption as process indicator

Journal of Biotechnology, 2012

Multivariate analysis of cell culture bioprocess data has the potential of unveiling hidden proce... more Multivariate analysis of cell culture bioprocess data has the potential of unveiling hidden process characteristics and providing new insights into factors affecting process performance. This study investigated the time-series data of 134 process parameters acquired throughout the inoculum train and the production bioreactors of 243 runs at the Genentech's Vacaville manufacturing facility. Two multivariate methods, kernel-based support vector regression (SVR) and partial least square regression (PLSR), were used to predict the final antibody concentration and the final lactate concentration. Both product titer and the final lactate level were shown to be predicted accurately when data from the early stages of the production scale were employed. Using only process data from the inoculum train, the prediction accuracy of the final process outcome was lower; the results nevertheless suggested that the history of the culture may exert significant influence on the final process outcome. The parameters contributing most significantly to the prediction accuracy were related to lactate metabolism and cell viability in both the production scale and the inoculum train. Lactate consumption, which occurred rather independently of the residual glucose and lactate concentrations, was shown to be a prominent factor in determining the final outcome of production-scale cultures. The results suggest possible opportunities to intervene in metabolism, steering it towards the type with a strong propensity towards high productivity. Such intervention could occur in the inoculum stage or in the early stage of the production-scale reactors. Overall, this study presents pattern recognition as an important process analytical technology (PAT). Furthermore, the high correlation between lactate consumption and high productivity can provide a guide to apply quality by design (QbD) principles to enhance process robustness.

Download

Mining manufacturing data for discovery of high productivity process characteristics

Journal of Biotechnology, 2010

Modern manufacturing facilities for bioproducts are highly automated with advanced process monito... more Modern manufacturing facilities for bioproducts are highly automated with advanced process monitoring and data archiving systems. The time dynamics of hundreds of process parameters and outcome variables over a large number of production runs are archived in the data warehouse. This vast amount of data is a vital resource to comprehend the complex characteristics of bioprocesses and enhance production robustness. Cell culture process data from 108 ‘trains’ comprising production as well as inoculum bioreactors from Genentech's manufacturing facility were investigated. Each run constitutes over one-hundred on-line and off-line temporal parameters. A kernel-based approach combined with a maximum margin-based support vector regression algorithm was used to integrate all the process parameters and develop predictive models for a key cell culture performance parameter. The model was also used to identify and rank process parameters according to their relevance in predicting process outcome. Evaluation of cell culture stage-specific models indicates that production performance can be reliably predicted days prior to harvest. Strong associations between several temporal parameters at various manufacturing stages and final process outcome were uncovered. This model-based data mining represents an important step forward in establishing a process data-driven knowledge discovery in bioprocesses. Implementation of this methodology on the manufacturing floor can facilitate a real-time decision making process and thereby improve the robustness of large scale bioprocesses.

Download

Transcriptome dynamics of transgene amplification in Chinese hamster ovary cells

Biotechnology and Bioengineering, 2014

Dihydrofolate reductase (DHFR) system is used to amplify the product gene to multiple copies in C... more Dihydrofolate reductase (DHFR) system is used to amplify the product gene to multiple copies in Chinese Hamster Ovary (CHO) cells for generating cell lines which produce the recombinant protein at high levels. The physiological changes accompanying the transformation of the non-protein secreting host cells to a high producing cell line is not well characterized. We performed transcriptome analysis on CHO cells undergoing the selection and amplification processes. A host CHO cell line was transfected with a vector containing genes encoding the mouse DHFR (mDHFR) and a recombinant human IgG (hIgG). Clones were isolated following selection and subcloned following amplification. Control cells were transfected with a control plasmid which did not have the hIgG genes. Although methotrexate (MTX) amplification increased the transcript level of the mDHFR gene significantly, its effect on both hIgG heavy and light chain genes was more modest. The subclones appeared to retain the transcriptome signatures of their parental clones, however, their productivity varied among those derived from the same clone. The transcript levels of hIgG transgenes of all subclones fall in a narrower range than the product titer, alluding to the role of many functional attributes, other than transgene transcript, on productivity. We cross examined functional class enrichment during selection and amplification as well as between high and low producers and discerned common features among them. We hypothesize that the role of amplification is not merely increasing transcript levels, but also enriching survivors which have developed the cellular machinery for secreting proteins, leading to an increased frequency of isolating highproducing clones. We put forward the possibility of assembling a hyper-productivity gene set through comparative transcriptome analysis of a wide range of samples.

Download

Slide Handout 3 - Trade Theory & Policy

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