Sequential Multivariate Cell Culture Modeling at Multiple Scales Supports Systematic Shaping of a Monoclonal Antibody Toward a Quality Target

Abstract

The development of cell culture processes is highly complex and requires a large number of experiments on various scales to define the design space of the final process and fulfil the regulatory requirements. This work follows an almost complete process development cycle for a biosimilar monoclonal antibody, from high throughput screening and optimization to scale-up and process validation. The key goal of this analysis is to apply tailored multivariate tools to support decision-making at every stage of process development. A toolset mainly based on Principal Component Analysis, Decision Trees, and Partial Least Square Regression combined with a Genetic Algorithm is presented. It enables to visualize the sequential improvement of the high-dimensional quality profile towards the target, provides a solid basis for the selection of effective process variables and allows to dynamically predict the complete set of product quality attributes. Additionally, this work shows the deep level of process knowledge which can be deduced from small scale experiments through such multivariate tools. The presented methodologies are generally applicable across various processes and substantially reduce the complexity, experimental effort as well as the costs and time of process development.

Protein Glycoengineering: An Approach for Improving Protein Properties

“…A possible combination strategy is as follows: organic and/or enzymatic synthesis is used to deeply understand the structure-property relationships of representative model glycoproteins that have relatively small sizes and simple structures. Theoretical predictions derived from the high-level understanding of protein glycosylation can then be used to guide protein glycoengineering efforts (Umana and Bailey, 1997 ; Grainger and James, 2013 ; Spahn et al, 2016 , 2017 ; Krambeck et al, 2017 ; Sokolov et al, 2018 ; Liang et al, 2020 ). Finally, cell-based methods can be used to more quickly obtain designed glycoforms in large-scale.…”

“…Researchers from many different disciplines have undertaken considerable efforts to develop and optimize methods and tools for the control and analysis of the heterogeneity of recombinant glycoproteins and have achieved encouraging success. For example, by developing computation models of protein glycosylation, researchers are now able to provide guidance on the design of optimal strategies to obtain a target glycosylation profile with desired properties (Umana and Bailey, 1997 ; Grainger and James, 2013 ; Spahn et al, 2016 , 2017 ; Krambeck et al, 2017 ; Sokolov et al, 2018 ; Liang et al, 2020 ). By improving chromatographic separation and analytical tools such as capillary electrophoresis, high performance liquid chromatography and mass spectrometry, researchers have made significant advances in the determination of the identity and quantity of differently glycosylated protein forms (glycoforms) (Domann et al, 2007 ; Zaia, 2008 ; Artemenko et al, 2012 ; Campbell et al, 2014 ; Zhang et al, 2016 ).…”

Cell culture process metabolomics together with multivariate data analysis tools opens new routes for bioprocess development and glycosylation prediction

“…21 This procedure can then be used to sequentially define the design space of the key features fulfilling a certain product quality goal. 22 However, such approaches have seldom been expanded to the extensive number of metabolic compounds present in extracellular and intracellular domains. The goal of this work is to apply such quantitative tools to process measurements while capturing the dynamics of several hundred extracellular and intracellular metabolites.…”

“…PLS2 models are capable of connecting the process to the product within a single model, while feature selection techniques 18,19 enable to center variable importance interpretation on key features, such as operating parameters, 20 medium composition, 21 and clone candidates 21 . This procedure can then be used to sequentially define the design space of the key features fulfilling a certain product quality goal 22 . However, such approaches have seldom been expanded to the extensive number of metabolic compounds present in extracellular and intracellular domains.…”

Accelerated Bioprocess Development of Endopolygalacturonase-Production with Saccharomyces cerevisiae Using Multivariate Prediction in a 48 Mini-Bioreactor Automated Platform

“…By these methods experiments not resulting in knowledge gain are avoided, thereby minimizing the time and resources needed for process development. Finally, this work is a step further to close the gap between data-driven statistical models and knowledge-driven deterministic models by combining them in so-called “hybrid models”, which can be flexibly defined given the available process knowledge and data [37,38,39].…”