Positioning for a sustainable future—Role of chemical engineers in transforming pharmaceutical process development

Bordawekar, Shailendra; Diwan, Moiz; Nere, Nandkishor K.

doi:10.1002/aic.17364

Cited by 3 publications

(1 citation statement)

References 52 publications

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“…25 Reduced downtime leads to higher productivity, as well as reduced unit capital cost, and may also help in achieving more sustainable processing. [26][27][28][29] Likewise, steady-state operation makes model building and thereby control far easier. This is an important argument to assist in the implementation of process analytical technology (PAT), as encouraged by the FDA.…”

Section: Continuous Flow Processingmentioning

confidence: 99%

Biocatalysis in microfluidic systems: an experimental basis for data science

Woodley

2024

React. Chem. Eng.

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Section: Continuous Flow Processingmentioning

confidence: 99%

Biocatalysis in microfluidic systems: an experimental basis for data science

Woodley

2024

React. Chem. Eng.

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Current state of implementation of in silico tools in the biopharmaceutical industry—Proceedings of the 5th modeling workshop

Wittkopp,

Welsh,

Todd

et al. 2024

Biotech & Bioengineering

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The fifth modeling workshop (5MW) was held in June 2023 at Favrholm, Denmark and sponsored by Recovery of Biological Products Conference Series. The goal of the workshop was to assemble modeling practitioners to review and discuss the current state, progress since the last fourth mini modeling workshop (4MMW), gaps and opportunities for development, deployment and maintenance of models in bioprocess applications. Areas of focus were four categories: biophysics and molecular modeling, mechanistic modeling, computational fluid dynamics (CFD) and plant modeling. Highlights of the workshop included significant advancements in biophysical/molecular modeling to novel protein constructs, mechanistic models for filtration and initial forays into modeling of multiphase systems using CFD for a bioreactor and mapped strategically to cell line selection/facility fit. A significant impediment to more fully quantitative and calibrated models for biophysics is the lack of large, anonymized datasets. A potential solution would be the use of specific descriptors in a database that would allow for detailed analyzes without sharing proprietary information. Another gap identified was the lack of a consistent framework for use of models that are included or support a regulatory filing beyond the high‐level guidance in ICH Q8–Q11. One perspective is that modeling can be viewed as a component or precursor of machine learning (ML) and artificial intelligence (AI). Another outcome was alignment on a key definition for “mechanistic modeling.” Feedback from participants was that there was progression in all of the fields of modeling within scope of the conference. Some areas (e.g., biophysics and molecular modeling) have opportunities for significant research investment to realize full impact. However, the need for ongoing research and development for all model types does not preclude the application to support process development, manufacturing and use in regulatory filings. Analogous to ML and AI, given the current state of the four modeling types, a prospective investment in educating inter‐disciplinary subject matter experts (e.g., data science, chromatography) is essential to advancing the modeling community.

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Special issue on women in chemical engineering

Singh

Azevedo²

2022

Chemical Engineering Research and Design

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Positioning for a sustainable future—Role of chemical engineers in transforming pharmaceutical process development

Cited by 3 publications

References 52 publications

Biocatalysis in microfluidic systems: an experimental basis for data science

Biocatalysis in microfluidic systems: an experimental basis for data science

Current state of implementation of in silico tools in the biopharmaceutical industry—Proceedings of the 5th modeling workshop

Special issue on women in chemical engineering

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