Development of a scale down cell culture model using multivariate analysis as a qualification tool

In characterizing a cell culture process to support regulatory activities such as process validation and Quality by Design, developing a representative scale down model for design space definition is of great importance. The manufacturing bioreactor should ideally reproduce bench scale performance with respect to all measurable parameters. However, due to intrinsic geometric differences between scales, process performance at manufacturing scale often varies from bench scale performance, typically exhibiting differences in parameters such as cell growth, protein productivity, and/or dissolved carbon dioxide concentration. Here, we describe a case study in which a bench scale cell culture process model is developed to mimic historical manufacturing scale performance for a late stage CHO‐based monoclonal antibody program. Using multivariate analysis (MVA) as primary data analysis tool in addition to traditional univariate analysis techniques to identify gaps between scales, process adjustments were implemented at bench scale resulting in an improved scale down cell culture process model. Finally we propose an approach for small scale model qualification including three main aspects: MVA, comparison of key physiological rates, and comparison of product quality attributes. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 30:152–160, 2014     

Fermentanomics: Relating quality attributes of a monoclonal antibody to cell culture process variables and raw materials using multivariate data analysis

Fermentanomics is an emerging field of research and involves understanding the underlying controlled process variables and their effect on process yield and product quality. Although major advancements have occurred in process analytics over the past two decades, accurate real‐time measurement of significant quality attributes for a biotech product during production culture is still not feasible. Researchers have used an amalgam of process models and analytical measurements for monitoring and process control during production. This article focuses on using multivariate data analysis as a tool for monitoring the internal bioreactor dynamics, the metabolic state of the cell, and interactions among them during culture. Quality attributes of the monoclonal antibody product that were monitored include glycosylation profile of the final product along with process attributes, such as viable cell density and level of antibody expression. These were related to process variables, raw materials components of the chemically defined hybridoma media, concentration of metabolites formed during the course of the culture, aeration‐related parameters, and supplemented raw materials such as glucose, methionine, threonine, tryptophan, and tyrosine. This article demonstrates the utility of multivariate data analysis for correlating the product quality attributes (especially glycosylation) to process variables and raw materials (especially amino acid supplements in cell culture media). The proposed approach can be applied for process optimization to increase product expression, improve consistency of product quality, and target the desired quality attribute profile. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1586–1599, 2015     

The potential of ISSR-PCR primer-pair combinations for genetic linkage analysis using the seasonal flowering locus in Fragaria as a model

ISSR-PCR has been widely used for genetic distance analysis and DNA fingerprinting but has been less well utilised for mapping purposes. A key limitation lies in the small number of primer designs available to generate useful polymorphisms. In this study, the potential of paired combinations of ISSR primers is evaluated using a test cross mapping population of 168 BC₁ individuals between Fragaria vesca f. vesca and a closely related line F. vesca f. semperflorens. Ten ISSR primers and all possible pairwise combinations between them were used to generate markers potentially linked to the locus controlling seasonal flowering in F. vesca. Band profiles of individual primers were found to be highly reproducible for band position and intensity, and only minor variation was noted in band intensity (but not in position) between different constituent mixes of primer-pair combinations. Overall, ISSR primers used in isolation produced 85 markers of which only five were specific to F. vesca. None of these markers were linked to the seasonal flowering locus. In contrast, the primer-pair combina-tions yielded 493 markers, including 14 specific to F. vesca. These markers included two located within 2.2 cM of the seasonality locus. The strengths and limitations of using pairs of ISSR primers in combination for mapping and other genetic analyses are briefly explored. Received: 12 October 2000 / Accepted: 19 January 2001