08.12.25 -- Navigating The Complexities Of NK Cell Therapy Development

Continuous bioprocessing is revolutionizing biotherapeutic manufacturing. Gain expert insights about cutting-edge innovations in monoclonal antibody production that enable scalable solutions for next-gen therapies.

From discovery to patient doses, viral vectors and exosomes face a complex journey. Researchers must navigate five key downstream processing challenges to ensure these therapies reach their full potential.

The use of manifolds to fill bags for bioprocessing or advanced therapies contributes to time savings, improved process quality, and optimal use of cleanroom and personnel resources.

This study demonstrates the Korus platform's ability to reduce manufacturing variability by elutriating lymphocytes from apheresis, providing a more consistent cell product for downstream manufacturing.

George White, Cytiva’s GM of Product Management for Cell and Gene Therapy, provides insight into the latest developments and strategies in cell therapy and where this dynamic field is headed.

Scalability remains a key bottleneck in CGT manufacturing. See how optimized stirred-tank bioreactor systems accelerate translation from clinical to commercial production.

Manual cryovial filling in cell therapy is risky, time-consuming, and unsustainable. Learn why automating this crucial step is essential for precision, viability, and scalability.

Tailor your bioprocess for optimal cell growth, gene expression, and therapeutic production with custom buffers to ensure precise control over pH, ion concentrations, and nutrient availability.

Here, we demonstrate a scalable workflow for the isolation of exosomes that combines tangential flow filtration for the concentration of exosomes followed by gentle size exclusion chromatography.

Automated bioprocessing can significantly improve CAR T cell manufacturing by reducing errors and enhancing scalability. Explore how this approach supports consistent, high-quality cell therapy production.

Explore how preserving spatial molecular information and leveraging AI-driven spatial-omics can transform treatment prediction, patient stratification, and personalized medicine.