Presented at ESACT, Lausanne, Switzerland
With increased number of experiments performed in bioprocess development, the capturing, processing, aggregation, visualization, and statistical analysis of generated data has become a major bottleneck. Association of the data with the experimental context (e.g., fermentation protocols, media recipes, bioreactor control parameters) is also challenging in high throughput. New and highly performant data capture, rocessing, and analysis systems need to be integrated to enable processing of analytics data. We have developed a new platform for bioprocess development, which enables the automatic capture and visualization of all online and offline data (e.g., pH, O2), auto-calculations and aggregations (e.g., IVCD, Qp), and multi-parametric assessment of any type of time-series bioreactor data in the context of experimental protocol data (e.g., process parameters). We present concrete use cases showing the selection of the best producer clones, the identification of optimized media feeding strategies, and the comparison of clone performance across fermentation scales. A special focus is on the analysis of data from micro-bioreactors (e.g., ambr®15) operated in parallel (n x 12 reactors) and of cross-reactor scale comparisons (e.g., ambr15 vs. DasGip®). Finally, we show how the platform enables correlation of process parameters (e.g., fermentation protocols, bioreactor control parameters), with key performance indicators of the processes (e.g., Titer, Qp) and the product quality attributes (e.g., aggregation, glycosylation profiles).