Predicting T‐cell quality during manufacturing through an artificial intelligence‐based integrative multiomics analytical platform-Reference-Cited by-同舟云学术

Predicting T‐cell quality during manufacturing through an artificial intelligence‐based integrative multiomics analytical platform

Published:2022-01-04 Issue: Volume: Page:
ISSN:2380-6761
Container-title:Bioengineering & Translational Medicine
language:en
Short-container-title:Bioengineering & Transla Med

Author:

Odeh‐Couvertier Valerie Y.¹,Dwarshuis Nathan J.²,Colonna Maxwell B.³,Levine Bruce L.⁴,Edison Arthur S.³,Kotanchek Theresa⁵,Roy Krishnendu²,Torres‐Garcia Wandaliz¹^ORCID

Affiliation:

1. Department of Industrial Engineering University of Puerto Rico Mayagüez Mayagüez Puerto Rico USA

2. The Wallace H. Coulter Department of Biomedical Engineering Georgia Institute of Technology Atlanta Georgia USA

3. Departments of Genetics and Biochemistry & Molecular Biology, Complex Carbohydrate Research Center University of Georgia Athens Georgia USA

4. Center for Cellular Immunotherapies, Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USA

5. Evolved Analytics LLC Rancho Santa Fe California USA

Funder

Division of Engineering Education and Centers

Georgia Tech Foundation

Publisher

Wiley

Subject

Pharmaceutical Science,Biomedical Engineering,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/btm2.10282

Reference50 articles.

1. Engineered T cells: the promise and challenges of cancer immunotherapy

2. Adoptive cell transfer as personalized immunotherapy for human cancer

3. Cells as advanced therapeutics: State-of-the-art, challenges, and opportunities in large scale biomanufacturing of high-quality cells for adoptive immunotherapies

4. Manufacturing chimeric antigen receptor T cells: issues and challenges

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