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SingleCell Biotechnology

Cutting edge single cell cancer diagnostics empowered with machine-learning for drug discovery.
Dallas

About 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.

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Problem statement

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.

Traction information

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

Milestones

December 2024

Label-Free Machine Learning Model

Achieve successful label-Free cell data model

July 2024

Hired Key employees

Senior Scientist Data Engineer

November 2023

CPRIT SEED Grant Award ($2.5M) to optimize assays and demonstrate usefulness for drug development.

Awarded CPRIT Grant for $2.5M to further the optimization of the plaform assays and demonstrate drug development in finding new biomarkers to combat difficult cancers.

May 2023

4 well device version of platform ready for production

4 well device version of platform devices made ready for production, past the prototype stage.

May 2023

Platform tested on primary tumor cells

Platform successfully tested with primary tumor cells direct from operating room to show that it has the ability to be used as a diagnostic device.

January 2023

Demonstrated platform use case with re-purposed drug

Demonstrated that the platform can be used to identify re-purposed drugs that can be used to enhance or provide improved treatment outcomes.

May 2022

Tested effectiveness of current drugs and radiation against non-dividing cells

Used platform to demonstrate how current drugs and radiation have little to no effect on migrating and dormant cancer cells. Further showing that current treatments targeting rapidly dividing cells leave this lethal population of non-dividing cells behind.

February 2022

Successful platform test with Breast and Glioblastoma PDX cell lines

Platform successfully demonstrated on prototype devices to demonstrate single cell dormancy, migration, and clonogenic assays with both Glioblastoma (brain) cancer and breast cancer patient derived cell lines.

Updates

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SingleCell Biotechnology selected to receive CPRIT Grant Award for $2.5M to further develop their ground breaking assays and demonstrate their usefulness in drug development.

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Funding

Currently raising capital

$0
committed
$2,000,000
round goal
Total raised to date:$635,000

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