Organoid and Immune Cell Co-Culture

Organoid and Non-Autologous Immune Cell Co-Culture
for Patient-Relevant In Vitro Immunotherapy Development

Progress your immunotherapy drug discovery by using organoids, the most clinically-relevant in vitro platform now available for immuno-oncology applications. Use our unique organoid and non-autologous immune cell co-culture platform to benefit from:

• Unique organoid models, exclusively developed using Hubrecht Organoid Technology (HUB) protocols
• Higher throughput evaluation and faster results compared with humanized in vivo PDX models
• An easily scalable platform, with multiple tumor organoids and immune cell donor combinations tested simultaneously
• Organoids from both tumor and healthy tissue to evaluate off target effects
• A large library of tumor models reflecting the patient population heterogeneity and antigen expression

Harness Our Organoid Co-Culture Platform For a Variety of Immunotherapy Studies

Our organoid and immune cell co-culture platform is available to:

• Evaluate the potency of your immunotherapies using non-autologous allogenic T cell assays with optimized conditions
• Assess tumor organoid killing by allogenic T cells and CAR-T cells, or to test ADCC and ADCP effects
• Evaluate tumor reactivity of CAR-T and TCR cells
• Profile immunotherapy target gene expression on tumor organoids or identify antigens of interest (e.g. tumor-associated antigens, immune checkpoint molecules)

Develop Unique New Immunotherapy Models through Organoid Engineering

Organoids can be engineered to express your desired immunotherapy target or to detect tumor organoid killing by luciferase or fluorescence.

About HUB Tumor Organoids

Tumor organoids are developed directly from patient tumors and matched healthy tissue using patented and exclusive HUB technology. Our well-characterized and ample patient-derived xenograft (PDX) collection is also available as an alternative source of human tumor tissue. PDX models allow additional tumor organoid development across more indications and to truly represent patient population diversity for biomarker identification and hypothesis generation.