De-Risking CHO Cell Line Development With Automation And Predictive Modeling

High-throughput, single-cell technologies are revolutionizing cell line development by enabling precise cloning and rapid screening of individual cells. These advancements significantly shorten development timelines by allowing researchers to quickly identify and isolate high-performing clones with greater accuracy. When combined with machine learning (ML) algorithms and multivariate data analysis (MVDA), these technologies offer powerful predictive capabilities. ML and MVDA can analyze complex datasets to reliably forecast cellular phenotypes, thereby streamlining the selection process and enhancing the likelihood of identifying high-producing clones early in development.

In an upcoming webinar, we will explore how integrating automation with predictive modeling can further accelerate and de-risk the clone selection process. By leveraging these innovative tools, organizations can improve efficiency, reduce manual intervention, and make more informed decisions throughout the development pipeline. This session will highlight practical strategies and real-world applications that demonstrate the transformative potential of these technologies in modern bioprocessing.