Recently we have demonstrated batch suspension culture of mammalian cells in microwell plates. Here we describe a method for fed-batch culture of an industrially relevant GS-CHO (Glutamine Synthetase-Chinese Hamster Ovary) cell line in shaken 24-standard round well (24-SRW) plates. Use of a commercially available 'sandwich lid' and appropriate dilution of the bolus feeds counteracted liquid evaporation from the wells resulting in similar cell growth and antibody formation kinetics in both 24-SRW plates (800 mul) and shaken flasks (50 ml). Peak viable cell densities obtained were 8 +/- 0.5 x 10(6) and 9 +/- 1.3 x 10(6) ml(-1), respectively, while comparable final titres of a whole IgG of approximately 1.5 g l(-1) were recorded. Use of microwells provides at least a 50-fold reduction in medium requirements compared to shake-flask and other culture devices currently used in early stage cell culture process development. The ability to run multiple wells in parallel and to automate culture operation also offers considerable enhancements in experimental throughput.

Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody–peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high‐throughput (HT) micro‐bioreactor system (AmbrTM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on‐line and off‐line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale‐up. Biotechnol. Bioeng. 2017;114: 2222–2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.