자료유형  

 학위논문

Control Number  

0016932678

International Standard Book Number  

9798379833947

Dewey Decimal Classification Number  

690

Main Entry-Personal Name  

Eren, Ayse.

Publication, Distribution, etc. (Imprint  

[S.l.] : Purdue University., 2021

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2021

Physical Description  

1 online resource(270 p.)

General Note  

Source: Dissertations Abstracts International, Volume: 85-01, Section: B.

General Note  

Advisor: Nagy, Zoltan.

Dissertation Note  

Thesis (Ph.D.)--Purdue University, 2021.

Restrictions on Access Note  

This item must not be sold to any third party vendors.

Summary, Etc.  

요약Developments in the technology are followed by the methods and frameworks in industry to intensify the production of information, tools, goods, and services. This trend has been followed by the pharmaceutical industry which is highly regulated by administrations to meet the quality requirements of the drugs and produce more for cheaper in a shorter time. As the knowledge and understanding of crystallization systems have been increasing with the development of process analytical technology (PAT) tools, it is inevitable to use the experience and data coming with it to develop data-driven, better processes. In the light of these developments, Industry 4.0 has started becoming the new paradigm in pharmaceutical industry pushing the data-driven design of pharmaceutical processes. This thesis demonstrates the development and usage of a framework for data-driven, model-based design of pharmaceutical processes that fall in line with this latest paradigm shift. The proposed framework can be summarized in four levels showing the benefits of the collected data and model development. These levels are data collection from specially designed experiments, model writing, using the data collected from the first step to train the model, validation of the model to call it 'Digital Twin' of the process, using the digital twin for process design via in-silico design of experiments (DoE) or process optimization. The chapters in this thesis are different case studies that follow these steps for model-based process design. The systems studied are batch cooling crystallization with temperature cycling to produce a drug compound, batch cooling crystallization with integrated milling and temperature cycling for the shape optimization of the same drug compound from previous step, and hot melt extrusion for amorphization of another drug compound. In addition to demonstrating the development of the whole framework and its possible benefits in each chapter, Chapter 4 is the solely experimental proof of concept of a previous, more general model-based design of a mill integrated crystallization work.

Subject Added Entry-Topical Term  

Cooling.

Subject Added Entry-Topical Term  

Spectrum analysis.

Subject Added Entry-Topical Term  

Parameter identification.

Subject Added Entry-Topical Term  

Digital twins.

Subject Added Entry-Topical Term  

Grain boundaries.

Subject Added Entry-Topical Term  

Crystallization.

Subject Added Entry-Topical Term  

Kinetics.

Subject Added Entry-Topical Term  

Particle size.

Subject Added Entry-Topical Term  

Crystals.

Subject Added Entry-Topical Term  

Scanning electron microscopy.

Subject Added Entry-Topical Term  

Parameter estimation.

Subject Added Entry-Topical Term  

Analytical chemistry.

Subject Added Entry-Topical Term  

Chemistry.

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Computer engineering.

Subject Added Entry-Topical Term  

Optics.

Subject Added Entry-Topical Term  

Pharmaceutical sciences.

Added Entry-Corporate Name  

Purdue University.

Host Item Entry  

Dissertations Abstracts International. 85-01B.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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Control Number  

joongbu:641515