As the demand for biotherapeutics continues to rise, so does the pressure on cell line development (CLD) labs to deliver with greater accuracy and efficiency. Traditional, manual methods are typically labor-intensive, limited in throughput and scalability, and prone to variability, making it challenging to keep up with the increased volume and complexity of modern CLD. For instance, manual approaches to quantifying IgG can take days, slowing down the identification of high-producing cell lines and increasing overall development costs and project timelines.
As CLD labs generate increasingly large quantities of complex and diverse data, they require secure, integrated systems that ensure accuracy, facilitate analysis, and support collaboration. Any errors or inconsistencies during data capture—whether due to manual transcription or fragmented data storage—can hinder progress, introduce costly rework, and risk the validity of findings and regulatory compliance.
To overcome these challenges, labs must balance automation, data management, and advanced analytics across every stage of their workflows. By integrating solutions that address the unique demands of CLD—from clone screening to scale-up and critical quality attribute verification—labs can develop processes that accelerate and transform CLD.
Download the full eBook to learn how to:
- Improve precision and efficiency across each stage of cell line development
- Overcome resource limits and reduce variability from manual input and tasks
- Leverage insights to identify trends and make informed decisions
- Implement comprehensive data solutions that boost quality, traceability, collaboration, and compliance