Genedata Bioprocess™ provides an integrated framework to process, analyze, visualize, and interpret bioreactor cell-culture data. The system is particularly useful for the analysis of online and offline data produced by mini-bioreactor systems (e.g., ambr®, DasGip). The increasing use of mini-bioreactors, which emulate large-scale manufacturing bioreactors at a fraction of the cost, has resulted in a significant increase in experiments. This in turn has led to huge volumes of complex bioreactor time series data that need to be analyzed.
Genedata Bioprocess enables an integrated, parallel assessment of large panels of clones - based on multi-parameter decision criteria - in order to identify the best cell lines to move forward. Cell culture growth characteristics, such as product titer, specific productivity (Qp), viable cell density (VCD), lactate and other metabolite data, are automatically calculated and analyzed, providing a comprehensive view on clone behavior under simulated manufacturing conditions. Dedicated tools facilitate the in-depth evaluation of multiple clones in parallel to identify the best producers.
Built-in tools enable a systematic analysis of all factors needed to guide process development and optimization; this includes tools for the identification of critical parameters and their impact on clone productivity and product quality (e.g., dependency of N-glycan patterns on feeding strategy, and lactate-VCD correlations). Typical applications are optimization of media and feeding strategies, extrapolation to lager bioreactor scales to guide upscaling campaigns, and other key process development activities. The platform helps to extrapolate from scale-down bioreactors to real-life fermentation manufacturing conditions and supports the incremental upscaling of bioreactor volumes to full manufacturing scale.