Driving Bioprocess Optimization Through Connected Laboratory Environments And Advanced Analytics

Bioprocess optimization often requires extensive experimentation, incremental scale-up, and careful management of process variability. A connected laboratory environment offers a more efficient path by combining real-time instrument data with predictive modeling and advanced analytics. Improved control of pH and dissolved oxygen reduced spiking, variability, and gas consumption, while analysis of cell culture data identified conditions that increased viable cell density and product titer. The resulting process delivered an 8% yield improvement and reduced experimental effort by up to 80%. These outcomes demonstrate how data-driven development can accelerate decision-making, lower costs, conserve resources, and enable direct scale-up.

Learn how laboratory connectivity can help translate process data into stronger performance and more efficient development strategies.