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Greg: Scott Broadley, president of Broadley-James Corp., broke wide open what our view of what a lab control systems can and should do for commercialization of biopharmaceuticals. I met Scott as a result of a shared interest in pH measurement and bioreactor modeling and control. Scott supported the exploration of a virtual plant as described in the BioProcess International Journal article "PAT Tools for Accelerated Process Development" March 2008 Supplement Series. Scott also provided a 100-liter bioreactor for testing wireless pH measurement and control. In the bioreactor tests we found that the wireless pH measurement had a resolution or threshold sensitivity of 0.001 pH and ignored spikes from electromagnetic interference (EMI) seen in wired measurements. The enhanced PID could achieve setpoint changes with an overshoot of less than a 0.002 pH. The long term accuracy including junction effects was 0.01 pH. These phenomenal results compared to what we are accustomed to in chemical process pH measurement and control were described in the Control May 2009 article "Is Wireless Process Control Ready for Prime Time."
Stan: Scott, how did you get into providing bioreactor systems for research and development?
Scott: I always had a fascination with biotechnology. After our development of the steam sterilizible gel filled pH electrode in the 1980s, I started a dialog with biopharmaceutical companies. I always answered the phone, gave first hand info, and got involved with what the customer needed. We gave seminars on the "Top Ten Practices for DO and pH Measurement." This led us to the idea of a better solution to the process development (PD) lab. The original concept was to start with a DCS scaled down to bench top applications with sophisticated control capability to deal with complex processes.
Greg: What was the biggest surprise?
Scott: We didn't anticipate the networking implications in Process Development. The PD Lab vessels acquire large amounts of data in historians including PID outputs that create the ability to adjust the PID based on batch phases using gain scheduling, steps, and ramps. The DCS system also has advanced control tools, such as adaptive control, model predictive control, and data analytics. We brought the best of automation technology developed over decades in commercial processes to the PD lab. These BioNet lab optimized DCS systems are little powerhouses of data which is what a PD lab is all about.
Stan: Why is the demand for data so great?
Scott: Besides the design of experiments (DOE) to determine optimums and operating condition limits in the definition of the process for the Food and Drug Administration (FDA), statistical analysis requires a large number of vessel runs. Each vessel run takes 2 weeks and with project time always being critical, many more bioreactor runs are required to run in parallel for the same experiment. In our most recent installation we had a total of 64 one liter bioreactors at two different sites for a particularly visionary and astute biopharmaceutical PD lab. The data was networked revealing essentially the same results independent of site and operator. Furthermore, the automation of the labs at both facilities enabled twice as many runs to be completed with half as many operators. The data obtained had minimal variance, was reproducible, and was explainable within the design space. The data variance was actually cut in half. With all biopharmaceutical budgets being squeezed this 4x improvement in productivity is drawing a lot of attention.
Stan: The 1 liter bench top bioreactor requires incredibly precise dosing and extremely small samples for at-line analyzers. Why so small?
Lab may do 50 to 200 small vessel runs in their development of scale-up data. A 500-liter pilot plant scale run costs $100K to $200K whereas the 1-liter run costs $1K to $K. However, precise control is not lost at this small vessel size. The lab system uses mass flow controllers (MFC) instead of solenoid valves for dosing. The MFC has a thermal flow meter, PID, and an internal flow element that gets a remote setpoint from either pH or DO controllers in the DCS. The cascade loop provides tight control and a flow measurement that provides considerable knowledge for data analytics and first principle modeling and diagnostics.
Greg: The job of the process controller is to transfer variability from the process variable (PV) to the manipulated variables (MV), inputs to the process, which in this case is air, oxygen, and carbon dioxide flows. If the process controller does a great job, changes in the process are not seen in the PV but are seen in the MV. When a process controller output goes directly to a final control element (no cascade control and no flow measurement), the relationship between the MV and the PV has too much nonlinearity and uncertainty principally due to pressure changes to be used for statistical or first principle modeling. The story is in the controller output but the picture is much clearer if there is a flow measurement.