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New Directions in Bioprocess Modeling and Control: Maximizing Process Analytical Technology Benefits

Michael A. Boudreau, Gregory K. McMillan
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Product ISBN/ID:
978-1-55617-905-1

Stock Status: In Stock

About

Models offer benefits even before they are put on line. Based on years of experience, the authors reveal in New Directions in Bioprocess Modeling and Control that significant improvements can result from the process knowledge and insight that are gained when building experimental and first-principle models for process monitoring and control. Doing modeling in the process development and early commercialization phases is advantageous because it increases process efficiency and provides ongoing opportunities for improving process control. This technology is important for maximizing benefits from analyzers and control tool investments.

If you are a process design, quality control, information systems, or automation engineer in the biopharmaceutical, brewing, or bio-fuel industry, this handy resource will help you define, develop, and apply a virtual plant, model predictive control, first-principle models, neural networks, and multivariate statistical process control. The synergistic knowledge discovery on bench top or pilot plant scale can be ported to industrial scale processes. This learning process is consistent with the intent in the Process Analyzer and Process Control Tools sections of the FDA’s Guidance for Industry PAT – A Framework for Innovative Pharmaceutical Development, Manufacturing and Quality Assurance.

It states in the Process Analyzer section of the FDA’s guidance: “For certain applications, sensor-based measurements can provide a useful process signature that may be related to the underlying process steps or transformations. Based on the level of process understanding these signatures may also be useful for the process monitoring, control, and end point determination when these patterns or signatures relate to product and process quality.”

Check out Mr. McMillan's Deminar Series for additional educational resources.

Format: Softbound Book
Length: 340 pages
 Shipping Weight: 1.38 lb(s)
Copyright: 2007
Publisher: ISA

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Spotlight Reviews

Beyond Brewing - Apr 24, 2008
Reviewer: Nicholas Sands
The area of bioprocesses, as opposed to traditional chemical processes, has being growing. Pharmaceuticals and bio-fuels have made it a hot topic in schools and industry. Finally there is a book that addresses bioprocess control, New Directions in Bioprocess Modeling and Control, by Michael Bourdreau and Gregory McMillan. McMillan is an ISA fellow, a former "Control Engineer of the Year", one of the first inductees into the "Process Control Hall of Fame", an affiliate professor at Washington University in St. Louis, and, because he shares his 30+ years of experience at Monsanto and Solutia, one of ISA's most prolific authors. This is neither the first nor the last review of one of McMillan's books. Michael Boudreau, P.E., is a control systems engineer for Emerson Process Management and has worked on control systems at Amgen, Bayer, and Genentech.

The introductory chapter explains that many bioprocesses have not optimized control because the pharmaceutical industry must, by regulation, validate the control system after each change. This has stifled the usual continuous improvement. The Process Analytical Technology (PAT) initiative is aimed at demonstrating control of the process and allowing improvements if the process remains within control limits. The control techniques in this book can help accomplish the PAT objectives.

Boudreau and McMillan next explain the basics of dynamics for both self-regulating and integrating processes, and describe the general characteristics for bioprocess variables such as pH, DO, and various concentrations. The loop deadtime limits the controller performance. The authors explain the structure and operation of various PID controllers and which is appropriate for different process variables such as temperature and pressure. They recommend the lambda tuning method.

Beyond basic control, model predictive control (MPC) is a powerful tool for optimization. MPC is particularly well suited for processes with dynamic interactions and complex dynamics, like inverse response. MPC can also control against a trajectory. Because of the limited opportunity to test operating conditions, dynamic simulations, or virtual plants, can provide an opportunity to explore new process conditions and control strategies. The rest of the book details modeling techniques for bio processes that can be used to develop virtual plants.

First principle models begin with mass and energy balances. The heat and kinetics for reactions and the vapor-liquid equilibrium further enhance the model. Virtual plants can be constructed using reusable modules that can be embedded within the control system. In the final chapters, the models are extended to artificial neural networks (ANNs) that use operating data to build multivariable nonlinear correlations of complex processes. Another set of technologies for complex processes, particularly suited to biological processes, are principle component analysis (PCA) and multivariable statistical process control. In PCA, many variables are mapped to fewer orthogonal dimensions to simplify analysis.

Boudreau and McMillan have assembled a single book that introduces the readers to the basics of control and the basics of bioprocesses, the dynamics of these processes, and then much more. For those in the bio-industry, this insight is truly valuable. That makes New Directions in Bioprocess Modeling and Control well worth buying for those in the bio industry and well worth reading, or borrowing, for those that work in other industries.