Imagine cancer as a weed where some seeds are tougher than others and keep growing back even after treatment. This project builds a high-tech screening system using tiny lab-grown versions of a patient's own tumor to find drugs that kill these 'seed' cells. It uses computer vision to spot exactly how the cells change, making it easier to find the right medicine to stop the cancer from returning.
Colorectal cancer has high relapse rates because current drugs fail to target cancer stem cells. There is a critical lack of therapeutics that can shift the balance between stem cells and differentiated cells to prevent treatment resistance.
A drug discovery platform combining patient-derived organoids (PDOs) and machine learning-assisted phenotypic validation to target Wnt signaling pathways.
If you are a drug discovery firm dealing with high failure rates in colorectal cancer trials — this project developed a phenotypic screening platform that identifies drugs targeting stem cell signaling. This allows for the discovery of therapeutics that prevent relapse by shifting the balance between stem and differentiated cells.
If you are a precision medicine startup dealing with the need for patient-specific drug testing — this project developed a system using patient-derived organoids (PDOs) and machine learning. This enables the validation of drugs based on actual patient tissue rather than generic cell lines.
If you are a health-tech AI developer dealing with the challenge of analyzing complex biological images — this project developed dedicated data analysis pipelines for phenotypic images of organoids. This provides a proven method for using computer vision to measure stem cell signaling activity.
Based on available project data, specific pricing for the platform is not provided, as the project is currently in the development and validation phase for a future spin-out company.
The project uses high-throughput biology and machine learning pipelines, which are designed for scalability in drug screening. The goal is to transition this into a NewCo business model.
The project team has refined their IP strategy and developed a business plan as part of the final results to support the creation of a spin-out company.
It integrates patient-derived organoids (PDOs) with automated image analysis pipelines, allowing researchers to measure stem cell signaling activity in cultured human cells.
The project period runs from 2022-11-01 to 2026-04-30, with the ultimate aim of spinning out a company based on the validated platform.
The consortium is highly academic and research-focused, consisting of 2 partners from a single country (Germany). It is led by the Deutsches Krebsforschungszentrum Heidelberg, with a 0% industry ratio, indicating the project is currently in the technology transfer phase from research to a potential commercial spin-off.
Contact the Deutsches Krebsforschungszentrum Heidelberg regarding the ACHILLEUS spin-out NewCo
Contact us to explore licensing opportunities for this phenotypic drug discovery platform.
