The increasing array of challenges faced by the pharmaceutical industry during drug development has led to a push for more efficient manufacturing techniques. With the implementation of continuous manufacturing, the importance of process modeling and control has become evident, being subject of multiple studies. Dynamic models with fast execution speeds are needed for the development of control strategies. Additionally, as robust as a control system can be, it is still not possible to ensure that the entirety of a production run is within quality specifications. For this reason, strategies for material diversion in real time need to be implemented.
The first part of this work focuses on the modeling of the tablet compaction operation. The experimental residence time distribution (RTD) of the tablet compaction process is determined through tracer experiments, and the resulting data is used to generate and validate an RTD model based on two different approaches. A framework for the development of control relevant dynamic models is then introduced. To exemplify the presented framework, a validated dynamic model for the tablet compaction operation is created. An in silico study using this model is conducted to evaluate different control algorithms and strategies for tablet compaction. One of the evaluated control strategies is selected and successfully implemented in a direct compaction pilot plant to demonstrate the applicability of the validated model for control strategy development.
In the second part of this thesis, a framework for the implementation of a material diversion system based on RTD is presented. A tablet diversion system is created according to the introduced framework, and the proposed diversion system is implemented in a commercial control platform, where its functionality is demonstrated using the developed RTD model and a simulated input.
Subject (authority = RUETD)
Topic
Chemical and Biochemical Engineering
Subject (authority = LCSH)
Topic
Pharmaceutical chemistry
Subject (authority = LCSH)
Topic
Drug factories
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_9264
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (ix, 124 pages : illustrations)
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
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