CELL EXPANSION BIOREACTORS FOR ASSAY-READY IMMUNOCOMPETENT PATIENT MODELS

Link Biosystems Inc., Irvington NY

Investigators

Abstract

Project Summary/Abstract Although cancer is a leading cause of death globally, oncology drugs have the lowest success rates, cost the most to develop, and constantly show promising results in animals and then fail to work in patients. Thus, there is a need for models that facilitate understanding of how a drug will work in humans and for specific patient populations. The availability of human tumor samples will further facilitate enhanced preclinical screening, where long timelines (>10 years), high costs ($2.6B), and low success rates (1/5,000) plague the development of new drugs. Link Biosystems provides a universal approach to tumor cell expansion via a custom bioreactor product that uses a defined serum-free media and relies on controlled aggregation for enhanced paracrine signaling and cell-cell contact, enhanced nutrient delivery via low-shear perfusion, and organotypic tissue niches to generate thousands of identical immunocompetent tumoroid tissues that can be further scaled as needed. This approach would enable the establishment of robust tumor models for early and late stage cancers, rare cancers, and previously biobanked samples at quantities suitable for screening large drug panels – including immunotherapies, biologics, and drug-drug combinations, to find an optimally effective drug regimen for the specific patient. Additionally, the ability to generate quality-controlled patient cells at scale will enable the establishment of patient tumor biobanks and subsequent personalized drug screening for optimal treatment guidance and to overcome drug resistant phenotypes. To this end, we are similarly evaluating our bioreactors versatile utility for expansion of direct patient tumor samples and previously biobanked organoid models, providing the raw material needed for downstream drug screening assays that are human, robust, reproducible, incorporates immune and stromal components, and captures the heterogeneity of patient responses.