Automated 'lab-on-a-chip' tech could reduce healthcare costs

A new computer programming language, created by a research team at the University of California, Riverside, will automate "laboratory-on-a-chip" technologies--and has the potential to reduce healthcare costs.

The technology is used in DNA sequencing, virus detection and drug discovery, among other biomedical applications. The device is only millimeters in size and allows for the automation and miniaturization of biochemical reactions, as reported by the school.

"If you think of the beginning of computers they were basically tools to automate mathematics," Philip Brisk, an assistant professor in the department of computer science and engineering at UC Riverside's Bourns College of Engineering, said. Brisk was part of the research team that developed the language.

"What are we are creating is devices that could automate chemistry in much the same way," he said.

Lab-on-a-chip technology has been used in other ways to help lower costs and wait times in many situations, including analyzing blood in about 20 minutes.

The language removes humans from the equation. In the past, the lab-on-a-chip used electronic sensors to enable healthcare professionals to work with the device to analyze the sensor data. But with the data now being funneled into a computer that facilitates automated decision making, professionals don't need to interact with the data.

Brisk said they are trying to eliminate as much human interaction as possible in order to "eliminate human error, cuts costs and speed up the entire process."

His findings were recently published in ACM Journal on Emerging Technologies in Computing Systems.

To create the new programming language, the team started with an existing one on bio programming, BioCoder, developed by Microsoft's research office in India. The researchers used that code to process sensor feedback in real-time. They then used a software simulator to mimic the behavior of a laboratory-on-a-chip. Now, they plan to build a prototype chip that can be used for real world applications.

To find out more:
- read the UC Riverside post
- read the paper (.pdf)

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