3D cell culture models offer more predictive drug responses and more accurately represent in vivo tissue structure and functionality than traditional 2D models, making them highly valuable for cancer research and drug development. However, this leap forward is not without its hurdles.
A main challenge is the increased complexity of 3D culturing methods. These models are typically more fragile than their 2D counterparts, so extreme precision and care must be taken to avoid disruption or aspiration. As a result, these workflows are time-consuming and cumbersome, making it difficult to scale for high-throughput applications like drug screening. Moreover, manual handling of 3D cultures is error-prone and associated with a high risk of variability, making it challenging for researchers to replicate findings and have confidence in their data.
Automation can address these challenges by managing the entire 3D cell culture workflow. From plating and media exchange to compound addition, staining, and monitoring, automated systems significantly reduce manual intervention. This facilitates scale-up while ensuring consistency across experiments and returning valuable time to researchers. Additionally, the integration of features like automated imaging and AI-driven analysis enables the generation of actionable insights from the beginning, accelerating high-throughput drug discovery and precision medicine applications.
Download this application note to explore how automation enhances efficiency, reproducibility, and scalability for 3D cell cultures, and discover effective methods for automating the culture, screening, imaging, and analysis of 3D spheroids.
