Department Seminar Series - Dr. Syed Kaschif Ahmed

Title

Abstract

The most common feed control strategies employed in the bio-pharmaceutical industry use offline and fixed recipes for controls of nutrients. An alternative approach is to apply Advanced Process Control (APC), using statistical models that rely upon discrete data and make assumptions about process variation. The use of Raman allows for more observability in the process which allows more data for use in model building. We first built a digital twin of a large-scale monoclonal antibody bioreactor with the following modeling spaces: the metabolism, the feedback controls, and the media. Then to test different in-process APC strategies, APC software was interfaced with the digital twin to allow us to investigate APC performance virtually. We also investigate the costliest step in production, the protein-A chromatography step. We model the kinetics of the step with regards to fouling. The product that is formed undergoes a number of post translation modification. Product quality is modeled with respect to process parameters. With these tools, one can start to optimize the production process and further develop the digital twin at the equipment and product quality level. 

Biography

Dr. Kaschif Ahmed has a Ph.D. in Chemical Engineering specializing in Advanced Process Modeling, Simulation, Optimization, and Control from the Illinois Institute of Technology. Kaschif has experience in modeling, optimizing, and controlling different systems such as fuel cell cars, coal gasifier, hybrid electric cars, bioreactors, and protein chromatography. Kaschif is currently an Senior APC engineer in the Advanced Data Analytics group in Biogen developing models and advanced controls for biologics upstream and downstream. 

Virtual Seminar via WEBEX