MK
M.E. Klijn
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Vaccination plays a pivotal role in modern preventive healthcare and contributes to a global decline in infectious diseases. Efficient production of vaccines is essential to meet the growing demand which results from factors like a growing global population and increased international travel. Protein subunit vaccines are a vaccine modality that contains parts of the infectious pathogen as the active ingredients. These subunits are recognized by the immune system, which is trained to respond more effectively and reduce symptoms upon actual infection. Production of these vaccines is divided into upstream processing (USP), which involves fermentation using expression hosts, downstream processing (DSP) where the protein subunit is purified, and finally formulation where the vaccines are prepared for distribution. During the DSP, multiple chromatography modes are often used to reach the required purity. Selection of the optimal chromatographic resin types, as well as operating conditions can be expensive and time consuming. Model-based process development has the potential to speed up this selection by using computational methods to predict protein behavior. Especially in early phase development, models allow in silico screening of resins and conditions in tandem to classical experiments, reducing required material. These computational models can be divided into knowledge-driven, datadriven, or a combination thereof.
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Vaccination plays a pivotal role in modern preventive healthcare and contributes to a global decline in infectious diseases. Efficient production of vaccines is essential to meet the growing demand which results from factors like a growing global population and increased international travel. Protein subunit vaccines are a vaccine modality that contains parts of the infectious pathogen as the active ingredients. These subunits are recognized by the immune system, which is trained to respond more effectively and reduce symptoms upon actual infection. Production of these vaccines is divided into upstream processing (USP), which involves fermentation using expression hosts, downstream processing (DSP) where the protein subunit is purified, and finally formulation where the vaccines are prepared for distribution. During the DSP, multiple chromatography modes are often used to reach the required purity. Selection of the optimal chromatographic resin types, as well as operating conditions can be expensive and time consuming. Model-based process development has the potential to speed up this selection by using computational methods to predict protein behavior. Especially in early phase development, models allow in silico screening of resins and conditions in tandem to classical experiments, reducing required material. These computational models can be divided into knowledge-driven, datadriven, or a combination thereof.
Bioprocess engineering involves the controlled cultivation of cells for the production of specialized products. These cells function as living factories, and their environment must be carefully controlled to optimize metabolic activity and productivity. Cell cultures are operated in bioreactor systems which aim to maintain optimal environmental conditions and provide optimal mass transfer. Monitoring bioreactor conditions such as nutrient levels or cell growth is typically dependent on manual sampling. This involves an operator extracting a small sample and analysing it on an external device, which provides a delayed and partial view of the process. To overcome the challenges of manual sampling, the bioprocessing industry is adopting Process Analytical Technology (PAT) tools like Raman spectroscopy, which can monitor the molecular composition of the system in real-time. However, accurate monitoring by Raman spectroscopy is dependent on chemometric models that typically require extensive calibration with process data, leading to processspecific models which do not transfer to related processes. This often necessitates repeating the extensive collection of process data for each new process that must be monitored. Therefore, this thesis focuses on investigating alternative approaches to calibration data collection and chemometric model calibration, while studying how varying measurement conditions affect spectral integrity...
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Bioprocess engineering involves the controlled cultivation of cells for the production of specialized products. These cells function as living factories, and their environment must be carefully controlled to optimize metabolic activity and productivity. Cell cultures are operated in bioreactor systems which aim to maintain optimal environmental conditions and provide optimal mass transfer. Monitoring bioreactor conditions such as nutrient levels or cell growth is typically dependent on manual sampling. This involves an operator extracting a small sample and analysing it on an external device, which provides a delayed and partial view of the process. To overcome the challenges of manual sampling, the bioprocessing industry is adopting Process Analytical Technology (PAT) tools like Raman spectroscopy, which can monitor the molecular composition of the system in real-time. However, accurate monitoring by Raman spectroscopy is dependent on chemometric models that typically require extensive calibration with process data, leading to processspecific models which do not transfer to related processes. This often necessitates repeating the extensive collection of process data for each new process that must be monitored. Therefore, this thesis focuses on investigating alternative approaches to calibration data collection and chemometric model calibration, while studying how varying measurement conditions affect spectral integrity...
Towards Holistic Science
Cultivating a mindset suiting inter- and transdisciplinarity
In the ever-changing landscape of the 21st century, complex issues like climate change demand holistic solutions. However, traditional scientific approaches often fall short by employing reductionism, breaking problems into isolated parts. This executive summary introduces a thesis that calls for a shift towards a more holistic and interdisciplinary perspective in the field of biotechnology. It outlines a three-phase research approach, seeking to cultivate a 'holistic' mindset within this academic discipline.
Phase 1 explores contextual influences on inter- and transdisciplinary mindsets in biotechnology. By introducing unusual triggers, such as artworks, researchers induce shifts in participants' perspectives. Emotions and cognitive dissonance emerge as key drivers of change, emphasizing the role of context in shaping mindsets.
Phase 2 delves into defining factors that continuously nurture a 'holistic' mindset. It highlights the importance of preserving individuality while fostering connections, utilizing boundary objects for effective communication, and leveraging emotions as triggers for reflective conversations.
Phase 3 involves the design of the "Out of Context!" tool, aimed at supporting interdisciplinary practices and the development of a 'holistic' mindset among biotechnology professionals. The tool is designed with criteria that ensure contextual relevance, creative discussions, integration of personal beliefs, support for minor interactions, and the establishment of a common ground.
This research offers a novel approach to fostering interdisciplinary thinking in biotechnology and could inform the development of a 'holistic' mindset within the field. It emphasizes the need for practitioners and researchers to share their experiences, ultimately advancing interdisciplinary practices in biotechnology. The effective implementation and evaluation of the "Out of Context!" tool are crucial, as it has the potential to transform discussions within the field, furthering the practice of inter- and transdisciplinarity in biotechnology. ...
Phase 1 explores contextual influences on inter- and transdisciplinary mindsets in biotechnology. By introducing unusual triggers, such as artworks, researchers induce shifts in participants' perspectives. Emotions and cognitive dissonance emerge as key drivers of change, emphasizing the role of context in shaping mindsets.
Phase 2 delves into defining factors that continuously nurture a 'holistic' mindset. It highlights the importance of preserving individuality while fostering connections, utilizing boundary objects for effective communication, and leveraging emotions as triggers for reflective conversations.
Phase 3 involves the design of the "Out of Context!" tool, aimed at supporting interdisciplinary practices and the development of a 'holistic' mindset among biotechnology professionals. The tool is designed with criteria that ensure contextual relevance, creative discussions, integration of personal beliefs, support for minor interactions, and the establishment of a common ground.
This research offers a novel approach to fostering interdisciplinary thinking in biotechnology and could inform the development of a 'holistic' mindset within the field. It emphasizes the need for practitioners and researchers to share their experiences, ultimately advancing interdisciplinary practices in biotechnology. The effective implementation and evaluation of the "Out of Context!" tool are crucial, as it has the potential to transform discussions within the field, furthering the practice of inter- and transdisciplinarity in biotechnology. ...
In the ever-changing landscape of the 21st century, complex issues like climate change demand holistic solutions. However, traditional scientific approaches often fall short by employing reductionism, breaking problems into isolated parts. This executive summary introduces a thesis that calls for a shift towards a more holistic and interdisciplinary perspective in the field of biotechnology. It outlines a three-phase research approach, seeking to cultivate a 'holistic' mindset within this academic discipline.
Phase 1 explores contextual influences on inter- and transdisciplinary mindsets in biotechnology. By introducing unusual triggers, such as artworks, researchers induce shifts in participants' perspectives. Emotions and cognitive dissonance emerge as key drivers of change, emphasizing the role of context in shaping mindsets.
Phase 2 delves into defining factors that continuously nurture a 'holistic' mindset. It highlights the importance of preserving individuality while fostering connections, utilizing boundary objects for effective communication, and leveraging emotions as triggers for reflective conversations.
Phase 3 involves the design of the "Out of Context!" tool, aimed at supporting interdisciplinary practices and the development of a 'holistic' mindset among biotechnology professionals. The tool is designed with criteria that ensure contextual relevance, creative discussions, integration of personal beliefs, support for minor interactions, and the establishment of a common ground.
This research offers a novel approach to fostering interdisciplinary thinking in biotechnology and could inform the development of a 'holistic' mindset within the field. It emphasizes the need for practitioners and researchers to share their experiences, ultimately advancing interdisciplinary practices in biotechnology. The effective implementation and evaluation of the "Out of Context!" tool are crucial, as it has the potential to transform discussions within the field, furthering the practice of inter- and transdisciplinarity in biotechnology.
Phase 1 explores contextual influences on inter- and transdisciplinary mindsets in biotechnology. By introducing unusual triggers, such as artworks, researchers induce shifts in participants' perspectives. Emotions and cognitive dissonance emerge as key drivers of change, emphasizing the role of context in shaping mindsets.
Phase 2 delves into defining factors that continuously nurture a 'holistic' mindset. It highlights the importance of preserving individuality while fostering connections, utilizing boundary objects for effective communication, and leveraging emotions as triggers for reflective conversations.
Phase 3 involves the design of the "Out of Context!" tool, aimed at supporting interdisciplinary practices and the development of a 'holistic' mindset among biotechnology professionals. The tool is designed with criteria that ensure contextual relevance, creative discussions, integration of personal beliefs, support for minor interactions, and the establishment of a common ground.
This research offers a novel approach to fostering interdisciplinary thinking in biotechnology and could inform the development of a 'holistic' mindset within the field. It emphasizes the need for practitioners and researchers to share their experiences, ultimately advancing interdisciplinary practices in biotechnology. The effective implementation and evaluation of the "Out of Context!" tool are crucial, as it has the potential to transform discussions within the field, furthering the practice of inter- and transdisciplinarity in biotechnology.