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3D cell cultures toward quantitative high-throughput drug screening.
1Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556, USA.
Trends in Pharmacological Sciences
|May 3, 2022
Summary
Three-dimensional (3D) cell cultures offer promise for drug discovery but face high-throughput screening (HTS) challenges. Integrating microfabrication, automation, and machine learning can overcome these hurdles for quantitative drug development.
Area of Science:
- Biomedical Engineering
- Pharmacology
- Cell Biology
Background:
- Three-dimensional (3D) cell cultures are increasingly used in drug discovery and development.
- Challenges in implementing 3D cultures for quantitative high-throughput screening (HTS) include architectural complexity, time/labor intensity, and incompatibility with traditional protocols.
Purpose of the Study:
- To review advances in 3D culture models for drug discovery.
- To discuss challenges in applying 3D cultures to HTS.
- To explore automation, high-throughput imaging, and machine learning (ML) integration for quantitative HTS.
Main Methods:
- Review of current literature on 3D cell culture models.
- Analysis of challenges in HTS implementation.
- Examination of automation, high-throughput imaging, and ML applications in 3D culture screening.
Main Results:
- 3D cell cultures present unique challenges for HTS.
- Advances in microfabrication, automation, and imaging are crucial for overcoming these challenges.
- Integration with ML tools can enhance quantitative HTS using 3D models.
Conclusions:
- Overcoming HTS challenges in 3D cell cultures requires integrating advanced technologies.
- Automation, high-throughput imaging, and ML are key to enabling quantitative HTS with 3D models.
- These integrated approaches will accelerate drug discovery and development.
