Computational modeling and optimization of biopharmaceutical downstream processes

Research output: ThesisDissertation (TU Delft)

2 Downloads (Pure)

Abstract

Vaccination is a strong and effective way to prevent spreading of infectious diseases and promotes global health. In the future, the importance of vaccines is expected only to increase, driven by factors such as increased international traveling, higher healthcare expenditures, and a growing population. To meet the growing demands, it is necessary to shorten process development timelines for the production of new vaccines without compromising on safety, efficacy, consistency, and stability of the product. Therefore, it is necessary to advance process development approaches of vaccines to respond quickly and in event of an emerging infectious disease. The work in this thesis employed mathematical modeling and simulation techniques to accelerate this process development. The developed methods are particularly valuable for early phase process development, aiming to enhance process knowledge and minimize the consumption of valuable resources and material. While the project has a focus on vaccine production processes, the modeling tools and methods developed are also applicable to other (bio)pharmaceutical processes. In Chapter 2, we discussed the present and future process development approaches in (bio)pharmaceutical purification with an emphasis on vaccines. The primary needs are to establish standardized processes and to improve understanding of both production processes and host cell impurities. Modeling, when combined with high throughput experimentation, can play a crucial role in achieving these goals...
Original languageEnglish
QualificationDoctor of Philosophy
Supervisors/Advisors
  • Ottens, M., Supervisor
  • Pabst, Martin, Advisor
Award date22 May 2024
DOIs
Publication statusPublished - 2024

Keywords

  • Chromatography
  • Downstream processing (DSP)
  • mechanistic modeling
  • Artificial neural network (ANN)

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