In drug discovery, growing pressure to generate human-relevant data, reduce late-stage failures, and support New Approach Methodologies (NAMs) is driving the adoption of complex 3D models like spheroids and organoids. The primary challenge labs face is successfully integrating this higher biological relevance into workflows without causing bottlenecks, increasing technical variability, or sacrificing operational efficiency.
To successfully navigate this shift, laboratories must adopt a fit-for-purpose approach rather than applying advanced models universally. This article explores key aspects to consider when matching the right model system with appropriate drug discovery workflows.
- Learn how incorporating 3D organoids and spheroids can impact predictive accuracy in downstream drug development applications.
- Understand the importance of optimized resource allocation by combining low-cost 2D workflows with 3D models in high-value applications
- Gain actionable insights on standardizing cell quality, assay design and automated high-content imaging without sacrificing throughput or reproducibility.
A decision tree is included to help evaluate team readiness, identify technical gaps, and ensure added model complexity translates directly into actionable data.
