Autonomous Biochip Leads to Rapid Diagnostic Capability

The novel biochip uses trenches patterned underneath microfluidic channels that are about the width of a human hair. When whole blood is dropped onto the chip's inlets, the relatively heavy red and white blood cells settle down into the trenches, separating from the clear blood plasma.

The Self-powered Integrated Microfluidic Blood Analysis System (SIMBAS) was developed by an international team, led by scientists at the University of California Berkeley (USA) and is able to process whole blood samples without the use of external tubing and extra components. The blood moves through the chip in a process called degas-driven flow, where air molecules inside the porous polymeric device are removed by placing the device in a vacuum-sealed package. When the seal is broken, the device is brought to atmospheric conditions, and air molecules are reabsorbed into the device material. This generates a pressure difference, which drives the blood fluid flow in the chip.

For the new SIMBAS biochip, the scientists took advantage of the laws of microscale physics to speed up processes that may take hours or days in a traditional laboratory. In experiments, they were able to capture more than 99% of the blood cells in the trenches and selectively separate plasma using this method. The team demonstrated the proof-of-concept of SIMBAS by placing into the chip's inlet a 5 µL sample of whole blood that contained biotin at a concentration of about one part per 40 billion. The biodetectors in the SIMBAS chip provided the readout of the biotin levels in 10 minutes and the limit of detection was 1.5 picomoles.

Luke P. Lee, PhD, the principal investigator of the study, said, "Field workers would be able to use this device to detect diseases such as human immunodeficiency virus (HIV) or tuberculosis in a matter of minutes. The fact that we reduced the complexity of the biochip and used plastic components makes it much easier to manufacture in high volume at low cost." The study was published online in March 17, 2011, in Lab on a Chip.

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