Nanoscale integration of single cell biologics discovery processes using optofluidic manipulation and monitoring Article Swipe
YOU?
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· 2019
· Open Access
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· DOI: https://doi.org/10.1002/bit.27024
The new and rapid advancement in the complexity of biologics drug discovery has been driven by a deeper understanding of biological systems combined with innovative new therapeutic modalities, paving the way to breakthrough therapies for previously intractable diseases. These exciting times in biomedical innovation require the development of novel technologies to facilitate the sophisticated, multifaceted, high‐paced workflows necessary to support modern large molecule drug discovery. A high‐level aspiration is a true integration of “lab‐on‐a‐chip” methods that vastly miniaturize cellulmical experiments could transform the speed, cost, and success of multiple workstreams in biologics development. Several microscale bioprocess technologies have been established that incrementally address these needs, yet each is inflexibly designed for a very specific process thus limiting an integrated holistic application. A more fully integrated nanoscale approach that incorporates manipulation, culture, analytics, and traceable digital record keeping of thousands of single cells in a relevant nanoenvironment would be a transformative technology capable of keeping pace with today's rapid and complex drug discovery demands. The recent advent of optical manipulation of cells using light‐induced electrokinetics with micro‐ and nanoscale cell culture is poised to revolutionize both fundamental and applied biological research. In this review, we summarize the current state of the art for optical manipulation techniques and discuss emerging biological applications of this technology. In particular, we focus on promising prospects for drug discovery workflows, including antibody discovery, bioassay development, antibody engineering, and cell line development, which are enabled by the automation and industrialization of an integrated optoelectronic single‐cell manipulation and culture platform. Continued development of such platforms will be well positioned to overcome many of the challenges currently associated with fragmented, low‐throughput bioprocess workflows in biopharma and life science research.
Related Topics
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.1002/bit.27024
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/bit.27024
- OA Status
- hybrid
- Cited By
- 33
- References
- 113
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2946009643
Raw OpenAlex JSON
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https://openalex.org/W2946009643Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1002/bit.27024Digital Object Identifier
- Title
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Nanoscale integration of single cell biologics discovery processes using optofluidic manipulation and monitoringWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
- Publication date
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2019-05-21Full publication date if available
- Authors
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Marsela Jorgolli, Tanner Nevill, Aaron Winters, Irwin Chen, Su Kong Chong, Fen‐Fen Lin, Marissa Mock, Ching Chen, Kim Le, Christopher Tan, Philip Jess, Xu Han, Agi Hamburger, Jennitte Stevens, Trent P. Munro, Ming C. Wu, Philip Tagari, Les P. MirandaList of authors in order
- Landing page
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https://doi.org/10.1002/bit.27024Publisher landing page
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/bit.27024Direct link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/bit.27024Direct OA link when available
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Nanotechnology, Workflow, Drug discovery, Computer science, Process (computing), Data science, Biochemical engineering, Engineering, Bioinformatics, Materials science, Biology, Database, Operating systemTop concepts (fields/topics) attached by OpenAlex
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33Total citation count in OpenAlex
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2025: 3, 2024: 7, 2023: 5, 2022: 7, 2021: 3Per-year citation counts (last 5 years)
- References (count)
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113Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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