Dataset Information

Advanced monitoring and control of pharmaceutical production processes with Pichia pastoris by using Raman spectroscopy and multivariate calibration methods.

ABSTRACT: This contribution includes an investigation of the applicability of Raman spectroscopy as a PAT analyzer in cyclic production processes of a potential Malaria vaccine with Pichia pastoris. In a feasibility study, Partial Least Squares Regression (PLSR) models were created off-line for cell density and concentrations of glycerol, methanol, ammonia and total secreted protein. Relative cross validation errors RMSEcvrel range from 2.87% (glycerol) to 11.0% (ammonia). In the following, on-line bioprocess monitoring was tested for cell density and glycerol concentration. By using the nonlinear Support Vector Regression (SVR) method instead of PLSR, the error RMSEPrel for cell density was reduced from 5.01 to 2.94%. The high potential of Raman spectroscopy in combination with multivariate calibration methods was demonstrated by the implementation of a closed loop control for glycerol concentration using PLSR. The strong nonlinear behavior of exponentially increasing control disturbances was met with a feed-forward control and adaptive correction of control parameters. In general the control procedure works very well for low cell densities. Unfortunately, PLSR models for glycerol concentration are strongly influenced by a correlation with the cell density. This leads to a failure in substrate prediction, which in turn prevents substrate control at cell densities above 16 g/L.

SUBMITTER: Voss JP

PROVIDER: S-EPMC6999294 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Advanced monitoring and control of pharmaceutical production processes with Pichia pastoris by using Raman spectroscopy and multivariate calibration methods.

Voss Jan-Patrick JP Mittelheuser Nina E NE Lemke Roman R Luttmann Reiner R

Engineering in life sciences 20170925 12

This contribution includes an investigation of the applicability of Raman spectroscopy as a PAT analyzer in cyclic production processes of a potential Malaria vaccine with Pichia pastoris. In a feasibility study, Partial Least Squares Regression (PLSR) models were created off-line for cell density and concentrations of glycerol, methanol, ammonia and total secreted protein. Relative cross validation errors RMSEcvrel range from 2.87% (glycerol) to 11.0% (ammonia). In the followi ...[more]

PMID: 32624755

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Project description:Over the past three decades, due to the universal application of Pichia yeast in the fermentation industry as well as the establishment of Pichia pastoris fermentation process for more than 30 years, the technology of the whole process has become very mature and has now reached a stagnated period of growth. However, studies and research conducted on the genomics of the classic fermentation process and the uncovering of the biological phenomena in the fermentation process from the point of view of high-throughput gene or protein is still in its early stages, and there is still insufficient data within this field. First, in collaboration with Agilent Company, we designed and prepared an expression microarray that could be used for the detection of Pichia pastoris transcriptomics. The transcriptomic changes in the five key technology steps (time points), during the fermentation process of Pichia pastoris would then be detected with the aid of an expression microarray. The five key steps of technology described above formed two important biological processes, namely, the limiting carbon source replacement and secondly, the fermentative production of exogenous proteins. The biological phenomena involved in these two processes were displayed and analyzed at the transcriptional level. In addition to this, with regard to the most important function in the fermentation process of Pichia pastoris, oxid-reduction, the metabolic drift process was analyzed and the important genes that might dominate the changes in the metabolic flux were discovered creatively by using the function tree method in this paper. This study was undertaken from the point of view of the transcriptome and the biological phenomena in the fermemntation process of Pichia pastoris. Both of which, were thoroughly explained during this study. The hope is for many more researchers to optimize the strain fermentation process, to produce proteins at the genetic level, as well as providing and obtaining new perspectives and detailed scientific data for the continued development within this field.

Dataset Information

Advanced monitoring and control of pharmaceutical production processes with Pichia pastoris by using Raman spectroscopy and multivariate calibration methods.

Publications

Advanced monitoring and control of pharmaceutical production processes with <i>Pichia pastoris</i> by using Raman spectroscopy and multivariate calibration methods.

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