Unlocking Potencial: Seamless Integration of Cutting Edge Digital Solutions in our CLD Platform

Accelerating Cell Line Development Using High-Throughput Single Cell Cloning and Multi-Model Predictive Modeling

Cell line development (CLD) is a critical step in biopharmaceutical manufacturing but selecting the high performing clone from thousands is laborious and time-consuming. High-throughput robotic single cell cloning instrument can revolutionize the process, allowing high-throughput isolation and cloning of individual cells, significantly reducing development time.

Additionally, leveraging artificial intelligence (AI) and machine learning (ML) techniques with support of multivariate data analysis (MVDA) can predict cell behavior based on early-stage data from single cell cloning devices. Integrating ML methods like artificial neural networks and random forests with traditional regression models and MVDA creates a multi-model approach, yielding more accurate and reliable predictions. This approach improves the selection of high-performing clones for large-scale production.

Here, we discuss the benefits and challenges of AI and ML techniques in supporting CLD services and highlight the latest advances in predictive modeling. By integrating the multi-model approach within MVDA software, an easy-to-adapt, optimized, and transfer platform is developed, enhancing CLD efficiency. Moreover, this methodology surpasses conventional selection strategies based solely on fluorescence data, increasing the likelihood of identifying superior clones.

Combining high-throughput single cell cloning with multi-model predictive modeling streamlines cell line development, enabling faster and more reliable identification of high-producing clones with reduced timelines and high productivity for biopharmaceutical manufacturing.