ArticleAIChE journal. American Institute of Chemical Engineers2018
Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production.
Article in AIChE journal. American Institute of Chemical Engineers, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Bioprocess Economic Modeling: Decision Support Tools for the Development of Stem Cell Therapy Products.Bioengineering (Basel, Switzerland) · 2022Review
- Membrane Applications in Autologous Cell Therapy.Membranes · 2022Review
- Biomaterials for stem cell engineering and biomanufacturing.Bioactive materials · 2019Review
- Ceramic Hollow Fibre Constructs for Continuous Perfusion and Cell Harvest from 3D Hematopoietic Organoids.Stem cells international · 2018Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
As breakthrough cellular therapy discoveries are translated into reliable, commercializable applications, effective stem cell biomanufacturing requires systematically developing and optimizing bioprocess design and operation. This article proposes a rigorous computational framework for stem cell biomanufacturing under uncertainty. Our mathematical tool kit incorporates: high-fidelity modeling, single variate and multivariate sensitivity analysis, global topological superstructure optimization, and robust optimization. The advantages of the proposed bioprocess optimization framework using, as a case study, a dual hollow fiber bioreactor producing red blood cells from progenitor cells were quantitatively demonstrated. The optimization phase reduces the cost by a factor of 4, and the price of insuring process performance against uncertainty is approximately 15% over the nominal optimal solution. Mathematical modeling and optimization can guide decision making; the possible commercial impact of this cellular therapy using the disruptive technology paradigm was quantitatively evaluated.
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Registered trials
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