Analytics and modeling tools can help deliver more effective and safer therapies to patients says Emerson, fresh from its acquisition of Bioproduction Group (Bio-G).
Terms of the acquisition have not been divulged, but technology and engineering company Emerson extends its life sciences technology portfolio through the addition of Bio-G.
“Many of biopharma’s biggest companies use Bio-G’s modeling and scheduling software for de-bottlenecking and optimization, and many of these same companies trust Emerson expertise and software to control their production and manage the release of quality therapies,” Tom Snead, president of Life Sciences and Alliances at Emerson, told Bioprocess Insider.
“At its core, Bio-G’s modeling software takes complex manufacturing performance data and makes it simple. While it’s currently utilized for optimizing production, either prior to or during manufacturing, the modeling capabilities could be deployed to simplify other areas of biopharma manufacturing.”
He added that combining these technologies will help place Emerson at the forefront of biomanufacturing.
“From a technology standpoint, much of the data and inputs necessary for Bio-G’s scheduling software come from control and manufacturing execution systems. Closer integration with our Syncade manufacturing execution system and DeltaV control system should only improve the efficiency and accuracy of models used to build production schedules and optimize production capacity.
“The combination of Bio-G with Emerson’s DeltaV system, Syncade software, and field devices will continue to place Emerson at the forefront of manufacturing patient impact therapies for diseases such as diabetes, Alzheimer’s, Immuno-Oncology (IO) and many others.”
Analytics and modeling tools
According to Snead, the most important driver for analytics and modeling tools is its ability to help quickly deliver more effective and safer therapies to patients.
“The reality is, with so many variables in today’s biopharma manufacturing, it’s almost inconceivable—yet necessary—to anticipate exactly what will be the impact of process changes and day-to-day manufacturing upsets and changes on production and quality,” he told us.
“For example, coordinating and scheduling production at biopharma facilities today is a heavily manual process dependent on variables and inputs from control, manufacturing execution, maintenance, and corporate enterprise systems.
“Balancing the impacts and constraints of those variables on production is necessary when organizations have millions of dollars tied up in manufacturing equipment and inventory and patients are depending on timely delivery of quality therapies.”