Curiosis sales manager Dongmin Choi discussed on Apr. 17 the importance of automated imaging and colony picking in cell-based workflows, highlighting how these technologies improve consistency, reproducibility, and data quality for researchers.
Automation is increasingly seen as essential in laboratory settings where maintaining consistent results across experiments can be challenging due to manual labor and human error. Choi said that standardized workflows and standard operating procedures are critical but often difficult to achieve without technological support. "This is where automation systems play an important role, helping labs reduce variability, improve consistency, and generate more reliable data over long-term experiments," he said.
Continuous monitoring of cells within a stable environment allows researchers to observe dynamic behavior over time without disturbing cultures. According to Choi, placing imaging systems directly inside incubators enables real-time observation while minimizing environmental disruption: "By placing the imaging system directly inside the incubator, researchers can monitor cells continuously under stable conditions. This allows them to capture real-time changes more naturally and consistently." He emphasized that reducing manual intervention increases the credibility of experimental data.
Automated colony picking was also highlighted as a key factor for ensuring high-quality downstream results in applications such as antibody production. Choi explained that automated systems like the CPX-α help ensure accuracy and efficiency: "Automated systems like the CPX-α improve accuracy and efficiency, helping ensure that the correct colonies are selected and reducing the risk of errors that could impact downstream results." He added that many laboratories underestimate how much automation can enhance reproducibility compared to experienced personnel performing tasks manually.
Choi noted a shift toward greater integration of automation with artificial intelligence-driven analysis software in laboratory environments: "Automation ensures reproducibility at scale, which is critical for generating credible scientific data." He described new models such as Celloger M22 and M26 designed for high-throughput screening environments by enabling simultaneous scanning of multiple plates while maintaining consistent imaging conditions.
Looking ahead, Choi predicted laboratories will require tools with better ease of use, standardization, connectivity—and further integration between automation technologies and AI-driven analysis—to support larger datasets and more meaningful insights from research.
