SingleCell Biotechnology

Our SCI-AP Platform of High-Density Single-Cell Assays redefines cancer stem cell analysis by integrating unparalleled single-cell data across all three cancer stem cell states. Powered by machine learning (ML), the platform delivers the most accurate and rapid analysis of cancer stem cells available. Utilizing proprietary protocols and custom plates compatible with high-throughput imagers, the system automates data analysis for faster, deeper insights than traditional methods.

The SCI-AP Platform addresses critical challenges in cancer research, particularly the need to better understand cancer stem cells, which are key drivers of tumor recurrence and therapy resistance. Traditional assays fall short due to low throughput, long timelines, and limited biological relevance. This platform overcomes these barriers by enabling high-density single-cell analysis, rapid machine learning-driven insights, and assays for clonogenic, migration, and dormancy studies. By studying cancer stem cells’ ability to grow, migrate, and enter dormancy, researchers can identify new drug targets, develop therapies to prevent recurrence, and accelerate breakthroughs in cancer treatment.

Created Label-Free clonogenic model Awarded Rising Star at BioNTX IC3 Conference Awarded CPRIT SEED Grant ($2.5M) to optimize assays and demonstrate usefulness in drug development for GBM. Successfully tested on primary patient GBM tumor cells direct from the operating room to demonstrate use as a personalized diagnostic device. Platform successfully tested on Glioblastoma (brain) cancer AND breast cancer PDX cell lines to demonstrate usefulness as a drug discovery tool. Used platform to demonstrate effectiveness (or non-effectiveness) of current drugs and radiation on dormant and migrating cells. Demonstrated use case of a repurposed drug using the platform. Prototype stage completed