CytoCatch™ is a medical device that automates the isolation and analysis of circulating tumor cells (CTCs) with over 97% recovery rates, enhancing reliability and reproducibility in cancer diagnostics. The technology integrates advanced imaging and machine learning to accurately classify CTCs, enabling comprehensive molecular analyses for early cancer detection and treatment monitoring.
Funding
$4.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Isolating and analyzing circulating tumor cells (CTCs) for cancer diagnostics is challenging due to the rarity of CTCs in blood samples and the limitations of manual methods, which can lead to variability and cell loss. Existing methods often lack the sensitivity and reproducibility needed for reliable early cancer detection and treatment monitoring.
Solution
CytoCatch™ automates the isolation, classification, and analysis of CTCs, addressing the limitations of manual methods. The system uses a microfluidic device to capture CTCs from blood samples with high recovery rates. Integrated advanced imaging and machine learning algorithms then accurately classify the captured cells, enabling comprehensive molecular analyses. This automated approach enhances the reliability and reproducibility of CTC isolation and analysis, providing a standardized platform for cancer diagnostics and research.
Target Audience
The primary users are cancer researchers and clinical laboratories involved in early cancer detection, treatment monitoring, and personalized medicine.
Features
- Automated CTC isolation using a microfluidic device with >97% recovery rates across multiple cancer cell lines (prostate, breast, lung, and colorectal).
- Integrated imaging system with advanced computer vision and machine learning algorithms for accurate CTC classification.
- Customizable components, including objectives, fluorescent filter cubes, and LEDs, for experimental flexibility.
- Compatibility with traditional molecular biology techniques and next-generation sequencing for in-depth molecular analyses.
- Fully automated platform minimizing human error and cell loss.