Driving Bioprocess Optimization Through Connected Laboratory Environments And Advanced Analytics

Digital integration and predictive control are transforming bioprocess development by improving efficiency and sustainability. We present two studies leveraging a connected laboratory environment and advanced analytics to accelerate process optimization.

Study 1:

A fully connected lab integrating real-time data acquisition and advanced process control was implemented to enhance instrument performance. Predictive modeling improved pH and dissolved oxygen (DO) regulation, delivering smoother control, reduced spiking, lower variability, and decreased gas consumption—demonstrating the potential of connectivity-driven strategies for robust bioprocess control.

Study 2:

Twelve small-scale bioreactors were operated in a connected environment to generate comprehensive cell culture datasets, including viable cell density (VCD) and metabolite profiles. Advanced analytics identified optimized conditions that increased VCD and product titer, achieving an 8% yield improvement. Data-driven predictions reduced experimental effort by up to 80%, enabling direct scale-up without incremental steps. This approach accelerates development timelines, reduces costs, and underscores the value of connectivity and predictive analytics in modern bioprocessing.