Bioreactor Fill Process Control Using Inline Concentration Measurement
Name
891583459-MIT.pdf
Description
Full printable version
Size
8.91 MB
Format
Adobe PDF
Checksum (MD5)
a24f61a76caf473c8931f58b5d27a49f
Author(s)
Dumouchel, Matthew P. (Matthew Paul)
Advisor(s)
Donald Rosenfield and Bernhardt Trout.
Date Issued
2014
Publisher
Massachusetts Institute of Technology
Abstract
Some biopharmaceutical companies have responded to evolution of the competitive landscape by placing additional emphasis on reducing their costs of manufacturing as a means of maintaining competitiveness. The prototypical current generation biopharmaceutical drug substance manufacturing facility requires a large upfront capital investment. Improving efficiency of use of existing facilities, such as by improving production throughput through the adoption of technology, represents one way in which a company may reduce its costs of manufacturing and/or avoid or delay investments in additional capacity needed to meet future demand. Reducing the variability in the performance of a liquid filling operation taking place during the protein production step is desirable, because it: (1) enables process optimization, including potential throughput expansion, (2) demonstrates control over the process, and (3) improves step yield reproducibility. The technical and economic bases for the implementation of an alternative process control strategy intended to reduce this variability are presented. This strategy involves controlling the fill operation using an inline concentration measurement of the parameter of interest. An engineering-probabilistic approach, consisting of a transient concentration profile model built into a Monte Carlo framework, is applied to predict the variability of the performance of a concentration-based control strategy for filling an agitated, gassed bioreactor. An optimization methodology for selecting an appropriate post-fill target concentration and for quantifying the economic benefit of reducing variability is proposed.
Description
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT.
Thesis: S.M., Massachusetts Institute of Technology, Department of Chemical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 75-77).
Subjects
Sloan School of Management.
Chemical Engineering.
Leaders for Global Operations Program.
MIT Department
Leaders for Global Operations Program at MIT
Massachusetts Institute of Technology. Department of Chemical Engineering
Sloan School of Management
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