Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

The Uncertainty Principle04:08

The Uncertainty Principle

32.0K
Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...
32.0K
Embryonic Stem Cells00:58

Embryonic Stem Cells

32.5K
Embryonic stem (ES) cells are undifferentiated pluripotent cells, meaning they can produce any cell type in the body. This gives them tremendous potential in science and medicine since they can generate specific cell types for use in research or to replace body cells lost due to damage or disease.
32.5K
Embryonic Stem Cells00:57

Embryonic Stem Cells

5.1K
Embryonic stem (ES) cells were first discovered in mice in 1981 by Martin Evans. In 1998, James Thomson identified a method to isolate embryonic stem cells from humans. Human embryonic stem cells (hESCs) are obtained from 3-5 day old embryos that remain unused after an in vitro fertilization procedure.
ES cells are grown in a culture medium where they can divide indefinitely, creating ES cell lines. Under certain conditions, ES cells can differentiate, either spontaneously into a variety of...
5.1K
Adult Stem Cells01:33

Adult Stem Cells

33.9K
Stem cells are undifferentiated cells that divide and produce more stem cells or progenitor cells that differentiate into mature, specialized cell types. All the cells in the body are generated from stem cells in the early embryo, but small populations of stem cells are also present in many adult tissues including the bone marrow, brain, skin, and gut. These adult stem cells typically produce the various cell types found in that tissue—to replace cells that are damaged or to continuously...
33.9K
Induced Pluripotent Stem Cells01:13

Induced Pluripotent Stem Cells

28.1K
Stem cells are undifferentiated cells that divide and produce different types of cells. Ordinarily, cells that have differentiated into a specific cell type are post-mitotic—that is, they no longer divide. However, scientists have found a way to reprogram these mature cells so that they “de-differentiate” and return to an unspecialized, proliferative state. These cells are also pluripotent like embryonic stem cells—able to produce all cell types—and are therefore...
28.1K
Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

52.9K
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
52.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Curative-intent tri-modality treatment of de novo bone-only oligometastatic breast cancer: single-center patient outcomes.

BMC cancer·2026
Same author

Assessing the feasibility of a pre-triage photo and questionnaire protocol in GP triage: a quality improvement study.

Primary health care research & development·2026
Same author

A bactericidal tuberculosis drug regimen driven by inhibition of the terminal oxidases by pretomanid.

EMBO molecular medicine·2026
Same author

A Series of Pyrazolo-Quinazoline Amines Inhibits the Cytochrome <i>bd</i> Oxidase in <i>Mycobacterium tuberculosis</i>.

Journal of medicinal chemistry·2026
Same author

Haemodynamic impact of implant materials and anastomotic angle in femoro-popliteal artery grafts.

Biomechanics and modeling in mechanobiology·2026
Same author

The promise of human bone marrow organoids for drug discovery and testing in myeloid and lymphoid cancers.

Expert opinion on drug discovery·2025

Related Experiment Video

Updated: Feb 5, 2026

Measuring Deformability and Red Cell Heterogeneity in Blood by Ektacytometry
09:12

Measuring Deformability and Red Cell Heterogeneity in Blood by Ektacytometry

Published on: January 12, 2018

15.5K

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

Ruth Misener1, Mark C Allenby2, María Fuentes-Garí2

  • 1Dept. of Computing Imperial College London South Kensington London SW7 2AZ U.K.

Aiche Journal. American Institute of Chemical Engineers
|September 1, 2018
PubMed
Summary

This study presents a computational framework for optimizing stem cell biomanufacturing processes, reducing costs by 4x. The robust optimization approach ensures reliable cellular therapy production despite process uncertainties.

Keywords:
bioprocess optimization under uncertaintybioreactor design under uncertaintyred blood cell productionrobust optimizationstem cell biomanufacturing

More Related Videos

Studying Pancreatic Cancer Stem Cell Characteristics for Developing New Treatment Strategies
07:29

Studying Pancreatic Cancer Stem Cell Characteristics for Developing New Treatment Strategies

Published on: June 20, 2015

20.2K
Prediction of Red Blood Cell Antibody Significance Using the Monocyte-Macrophage Assay
11:27

Prediction of Red Blood Cell Antibody Significance Using the Monocyte-Macrophage Assay

Published on: February 7, 2025

1.1K

Related Experiment Videos

Last Updated: Feb 5, 2026

Measuring Deformability and Red Cell Heterogeneity in Blood by Ektacytometry
09:12

Measuring Deformability and Red Cell Heterogeneity in Blood by Ektacytometry

Published on: January 12, 2018

15.5K
Studying Pancreatic Cancer Stem Cell Characteristics for Developing New Treatment Strategies
07:29

Studying Pancreatic Cancer Stem Cell Characteristics for Developing New Treatment Strategies

Published on: June 20, 2015

20.2K
Prediction of Red Blood Cell Antibody Significance Using the Monocyte-Macrophage Assay
11:27

Prediction of Red Blood Cell Antibody Significance Using the Monocyte-Macrophage Assay

Published on: February 7, 2025

1.1K

Area of Science:

  • Biotechnology and Bioprocessing
  • Regenerative Medicine
  • Computational Biology

Background:

  • Translating cellular therapy discoveries into commercial applications necessitates efficient stem cell biomanufacturing.
  • Optimizing bioprocess design and operation is crucial for reliable and scalable production.
  • Existing methods may not adequately address uncertainties inherent in biomanufacturing.

Purpose of the Study:

  • To propose a rigorous computational framework for stem cell biomanufacturing under uncertainty.
  • To demonstrate the advantages of this framework using a case study of red blood cell production.
  • To quantitatively evaluate the commercial impact of optimized cellular therapies.

Main Methods:

  • Development of a mathematical toolkit incorporating high-fidelity modeling.
  • Application of single and multivariate sensitivity analysis.
  • Utilizing global topological superstructure optimization and robust optimization techniques.

Main Results:

  • The proposed framework was quantitatively demonstrated using a dual hollow fiber bioreactor for red blood cell production.
  • The optimization phase achieved a cost reduction of fourfold.
  • The cost of insuring process performance against uncertainty was approximately 15% above the nominal optimum.

Conclusions:

  • Mathematical modeling and optimization provide a robust approach to guide decision-making in stem cell biomanufacturing.
  • The framework enables the reliable commercialization of cellular therapies.
  • This disruptive technology paradigm has significant potential commercial impact.