UC Case No. 2010-277
SUMMARY
UCLA researchers have developed a compact and cost-effective platform for extreme throughput single cell analysis. The device has the potential to conduct whole blood cell counts with ten-fold higher analysis speed than conventional flow cytometry.
BACKGROUND
Flow cytometry is regularly used for patient blood analysis. Because, flow cytometry analyzes cells in a serial process, it is time consuming and lacks sufficient throughput (current methods top out at 10,000 cells/sec) to detect rare cells in blood or other dilute solutions which can have concentrations in the range of one in one quadrillion (1:1015). In addition, flow cytometry has high operating costs, lacks portability, and requires dedicated personnel and is therefore impractical for point-of-care use. Because the global flow cytometry market is projected to exceed $1.5 billion with an annual growth above 10%, great attention is being paid to microfluidic devices for healthcare applications. Microfluidics devices offer a significant reduction in cost, increase in portability, and higher throughput efficiency than flow-cytometry with comparable or better sensitivity.
INNOVATION
UCLA researchers have developed a microfluidic chip capable of processing ~28 million cells per second. The design does not require a sheath stream, which simplifies the design without sacrificing efficiency. By coupling the chip with high-speed imaging, the researchers can observe single cells to compare physical characteristics or specifically targeted/stained cells for accurate blood cell detection and analysis.
APPLICATIONS
- Rapid red and white blood cell analysis
- Rare circulating tumor or stem cell detection from blood
- Use in biomedical research as a rapid blood and lymph analysis tool
ADVANTAGES
- Extremely high throughput: ~28 million cells per second
- Efficacious at detecting rare cell populations
- Low cost and convenient
- Fluorescent or chemical cell labeling is not required
STATE OF DEVELOPMENT
The researchers have designed the microfluidic chip architecture to optimize cell ordering which assists analysis. Also, the particle velocity has been optimized to provide uniform particle lattices in the imaging field. The system has been validated using automated image analysis to differentiate between red blood cells and different types of white blood cells. Additional modifications to increase imaging fidelity and cell throughput are currently being incorporated into the prototype.