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Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging
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Automated image analysis with the potential for process quality control applications in stem cell maintenance and
David Smith1, Katie Glen1, Robert Thomas1
1Centre for Biological Engineering, Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University, Loughborough, LE11 3TU, U.K.
Biotechnology Progress
|November 13, 2015
Summary
Image analysis offers a powerful solution for cell-based therapy manufacturing by providing efficient, informative process control. This method uses live cell imaging to monitor cell morphology, enabling accurate assessment of cell state and number.
Area of Science:
- Biotechnology
- Cell Therapy Manufacturing
- Quantitative Imaging
Background:
- Scaling laboratory cell-based therapies to manufacturing presents significant challenges.
- A lack of informative and efficient analytical methods hinders effective process control.
Purpose of the Study:
- To explore the potential of quantitative image analysis for in-process control in cell therapy manufacturing.
- To utilize pluripotent stem cells as a model to develop and validate image analysis techniques.
Main Methods:
- Live cell imaging (Cell-IQ platform) to create morphological attribute libraries (colony edge, core periphery, core cells).
- Correlation of morphological attributes with conventional biomarkers (Oct3/4, Nanog, Sox-2) using immunostaining and flow cytometry.
- Quantitative monitoring of morphological changes in response to process variations (media exchange, BMP4 addition).
- Determination of imaging sample size versus precision for morphological attributes.
- Correlation of single colony morphology with differentiation outcomes and cell number assessment.
Main Results:
- Morphological attributes were linked to specific cell states and biomarkers.
- Quantitative monitoring demonstrated rapid sensitivity to process changes.
- Optimal imaging sample sizes were defined for reliable sensitivity.
- Single colony morphology predicted differentiation outcomes (smaller colonies for mesoderm induction, larger for pluripotency).
- Image analysis accurately assessed cell number, comparable to traditional methods.
Conclusions:
- Quantitative image analysis is a powerful, complementary tool for in-process control and process development in cell therapy manufacturing.
- This approach enhances analytical capabilities beyond current methods, supporting optimization and scalable production.
