NSF awards $2M to ChE’s Nagy team to improve pharmaceutical supply chains
Zoltan Nagy, professor in the Davidson School of Chemical Engineering, has been awarded a $2M grant from the National Science Foundation (NSF).
Nagy’s project will produce an integrated framework for creating a resilient, distributed pharmaceutical manufacturing ecosystem that will optimally meet individualized patient needs. The team developed the idea in response to disruptions in the supply of essential medicines caused by the COVID-19 pandemic.
“Global pharmaceutical supply chains based on production in a few centralized manufacturing sites, using traditional large-batch manufacturing methods that produce one-size-fits-all dosages, are inherently unreliable and inefficient,” Nagy, the principal investigator, wrote in his abstract.
His team on the project includes co-principal investigators: Gintaras “Rex” Reklaitis, Purdue’s Burton and Kathryn Gedge Distinguished Professor of Chemical Engineering; David Thompson, Purdue professor of organic chemistry; and Venkat Venkatasubramanian and Garud Iyengar, both of Columbia University.
With the grant funds, the team plans to address supply chain deficiencies by bringing production of medicines closer to the point of demand - the patient - employing advanced manufacturing methods, including continuous processing, digital design and high levels of automation and advanced control to assure product quality and to produce dosages that are personalized for the patient.
“Specifically, we will develop the technology necessary to achieve these capabilities and demonstrate them using two representative generic drugs, one for the treatment of cancer and another for treating high blood pressure,” according to the abstract.
Nagy’s research efforts have focused on understanding, designing and controlling complex chemical and pharmaceutical systems. His work is characterized by the integration of modeling and control approaches with experimental investigations, with the goal of developing theoretically founded, practical methodologies with quantifiable system performance improvements that can be supported in an industrial environment.