Cargando…

Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production

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 bio...

Descripción completa

Detalles Bibliográficos
Autores principales: Misener, Ruth, Allenby, Mark C., Fuentes‐Garí, María, Gupta, Karan, Wiggins, Thomas, Panoskaltsis, Nicki, Pistikopoulos, Efstratios N., Mantalaris, Athanasios
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6108044/
https://www.ncbi.nlm.nih.gov/pubmed/30166646
http://dx.doi.org/10.1002/aic.16042
_version_ 1783350077176152064
author Misener, Ruth
Allenby, Mark C.
Fuentes‐Garí, María
Gupta, Karan
Wiggins, Thomas
Panoskaltsis, Nicki
Pistikopoulos, Efstratios N.
Mantalaris, Athanasios
author_facet Misener, Ruth
Allenby, Mark C.
Fuentes‐Garí, María
Gupta, Karan
Wiggins, Thomas
Panoskaltsis, Nicki
Pistikopoulos, Efstratios N.
Mantalaris, Athanasios
author_sort Misener, Ruth
collection PubMed
description 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. © 2017 American Institute of Chemical Engineers AIChE J, 64: 3011–3022, 2018
format Online
Article
Text
id pubmed-6108044
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-61080442018-08-28 Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production Misener, Ruth Allenby, Mark C. Fuentes‐Garí, María Gupta, Karan Wiggins, Thomas Panoskaltsis, Nicki Pistikopoulos, Efstratios N. Mantalaris, Athanasios AIChE J Futures Issue: Process Systems Engineering 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. © 2017 American Institute of Chemical Engineers AIChE J, 64: 3011–3022, 2018 John Wiley and Sons Inc. 2017-12-07 2018-08 /pmc/articles/PMC6108044/ /pubmed/30166646 http://dx.doi.org/10.1002/aic.16042 Text en © 2017 American Institute of Chemical Engineers This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Futures Issue: Process Systems Engineering
Misener, Ruth
Allenby, Mark C.
Fuentes‐Garí, María
Gupta, Karan
Wiggins, Thomas
Panoskaltsis, Nicki
Pistikopoulos, Efstratios N.
Mantalaris, Athanasios
Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production
title Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production
title_full Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production
title_fullStr Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production
title_full_unstemmed Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production
title_short Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production
title_sort stem cell biomanufacturing under uncertainty: a case study in optimizing red blood cell production
topic Futures Issue: Process Systems Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6108044/
https://www.ncbi.nlm.nih.gov/pubmed/30166646
http://dx.doi.org/10.1002/aic.16042
work_keys_str_mv AT misenerruth stemcellbiomanufacturingunderuncertaintyacasestudyinoptimizingredbloodcellproduction
AT allenbymarkc stemcellbiomanufacturingunderuncertaintyacasestudyinoptimizingredbloodcellproduction
AT fuentesgarimaria stemcellbiomanufacturingunderuncertaintyacasestudyinoptimizingredbloodcellproduction
AT guptakaran stemcellbiomanufacturingunderuncertaintyacasestudyinoptimizingredbloodcellproduction
AT wigginsthomas stemcellbiomanufacturingunderuncertaintyacasestudyinoptimizingredbloodcellproduction
AT panoskaltsisnicki stemcellbiomanufacturingunderuncertaintyacasestudyinoptimizingredbloodcellproduction
AT pistikopoulosefstratiosn stemcellbiomanufacturingunderuncertaintyacasestudyinoptimizingredbloodcellproduction
AT mantalarisathanasios stemcellbiomanufacturingunderuncertaintyacasestudyinoptimizingredbloodcellproduction