QRM News

12
Sep

Aldevron, Center for Quick Response Manufacturing Win Applied Research Challenge for Innovations in Protein Manufacturing

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A collaboration between biotechnology company Aldevron and the University of Wisconsin-Madison College of Engineering to develop decision support tools for biomanufacturing has been awarded first place in the 2016 Applied Research Challenge organized by the Production and Operations Management Society (POMS).

This competition was established by POMS as a way to encourage its members to conduct rigorous applied research that is innovative and relevant to production and operations management.

The team included Industrial and Systems Engineering Associate Professor Ananth Krishnamurthy and Tugce Martagan, researchers from the Center for Quick Response Manufacturing at UW-Madison; Peter A. Leland, senior manager of protein services at Aldevron; and Christos T. Maravelias, Vilas Distinguished Achievement Professor of chemical and biological engineering at UW-Madison.

The team’s project, titled “Optimal Purification Decisions for Engineered Proteins,” developed a decision model that provides managerial insight to optimize protein purification operations. The work provides practical guidelines and predictive software tools to quantify financial risks and optimize decisions based on specific client requirements.

A collaboration between biotechnology company Aldevron and the University of Wisconsin-Madison College of Engineering to develop decision support tools for biomanufacturing has been awarded first place in the 2016 Applied Research Challenge organized by the Production and Operations Management Society (POMS).

This competition was established by POMS as a way to encourage its members to conduct rigorous applied research that is innovative and relevant to production and operations management.

The team included Industrial and Systems Engineering Associate Professor Ananth Krishnamurthy and Tugce Martagan, researchers from the Center for Quick Response Manufacturing at UW-Madison; Peter A. Leland, senior manager of protein services at Aldevron; and Christos T. Maravelias, Vilas Distinguished Achievement Professor of chemical and biological engineering at UW-Madison.

The team’s project, titled “Optimal Purification Decisions for Engineered Proteins,” developed a decision model that provides managerial insight to optimize protein purification operations. The work provides practical guidelines and predictive software tools to quantify financial risks and optimize decisions based on specific client requirements.

“Our clients have unique and rigorous requirements for their protein production projects,” Leland says. “The challenge biomanufacturers face is optimizing many parameters, including yield, purity and activity while producing proteins in living cells that have inherent variability. Using mathematical models, we hypothesized that we could reduce the effort and duration required to establish purification processes, resulting in reduced lead times and improved service to our clients”.

“This collaboration has resulted in an innovative application of the theory of stochastic optimization to biomanufacturing,” says Krishnamurthy, director of the Center for Quick Response Manufacturing. “Using models for sequential decision making under uncertainty, we are able to develop tools that would allow Aldevron to meet client targets related to yield and purity requirements with shorter lead times and lower costs.”

Aldevron is currently implementing the results of this work in its development processes to deliver increased value to its clients. The work has also been submitted for publication in the journal Operations Research.

“Our clients have unique and rigorous requirements for their protein production projects,” Leland says. “The challenge biomanufacturers face is optimizing many parameters, including yield, purity and activity while producing proteins in living cells that have inherent variability. Using mathematical models, we hypothesized that we could reduce the effort and duration required to establish purification processes, resulting in reduced lead times and improved service to our clients”.

“This collaboration has resulted in an innovative application of the theory of stochastic optimization to biomanufacturing,” says Krishnamurthy, director of the Center for Quick Response Manufacturing. “Using models for sequential decision making under uncertainty, we are able to develop tools that would allow Aldevron to meet client targets related to yield and purity requirements with shorter lead times and lower costs.”

Aldevron is currently implementing the results of this work in its development processes to deliver increased value to its clients. The work has also been submitted for publication in the journal Operations Research.

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