Clone screening and selection are critical yet complex steps in cell line development (CLD), demanding precision, consistency, and time. Without regular, accurate measurements of important parameters like antibody titer and cell count, researchers are often forced to make decisions based on isolated snapshots of information. Additionally, many labs still rely on fragmented systems and manual workflows, where delayed or incomplete data increase the risk of selecting suboptimal clones. These challenges can lead to unreliable results, increased costs, and extended development timelines.
To address these inefficiencies, labs are shifting toward automated, high-throughput cultivation platforms that streamline workflows and provide greater experimental control. By integrating analytics with continuous monitoring and regulation of key cultivation parameters, these solutions minimize human error, reduce contamination risks, and create more uniform culture conditions. With a standardized and scalable approach, lab managers and scientists can select top-performing clones with greater confidence, improving reproducibility and accelerating CLD.
This application note explores how an automated and fully integrated platform can reduce hands-on time, enhance accuracy, and enable more informed decision-making. Download now to discover strategies for increasing throughput and improving confidence in clone selection.