Device Diagnoses Diseases in Less Than an Hour

Researchers from the National University of Singapore have created an easy to use device that can swiftly screen for a range of diseases like Ebola, Dengue, Hepatitis, Malaria and Zika and costs less than 75¢ a test.

The device called ‘enzyme-assisted nanocomplexes for visual identification of nucleic acids’ or enVision for short is an amazing step forward in diseases screening, taking between 30 minutes to an hour to work, which is almost 4 times faster than existing methods. On top of its speeding results, the device can also screen for some types of cancers and genetic diseases.

“The enVision platform is extremely sensitive, accurate, fast, and low-cost. It works at room temperature and does not require heaters or special pumps, making it very portable,” says team leader Shao Huilin, assistant professor from the Biomedical Institute for Global Health Research and Technology (BIGHEART) and biomedical engineering department at National University of Singapore.

“With this invention, tests can be done at the point-of-care, for instance in community clinics or hospital wards, so that disease monitoring or treatment can be administered in a timely manner to achieve better health outcomes,” says Shao, who is also an investigator with the Institute of Molecular and Cell Biology.

In clinical trials using the human papillomavirus, the device outperformed the gold standard, demonstrating superior sensitivity and specificity. “EnVision is not only able to accurately detect different subtypes of the same disease, but it is also able to spot differences within a specific subtype of a given disease to identify previously undetectable infections,” Shao says.

Further, test results are easily visible—the assay turns from colourless to brown if a disease is present. Researchers could also further analyze the results using a smartphone for quantitative assessment of the amount of pathogen present. That makes the device an ideal solution for personal health care and telemedicine.

“Conventional technologies—such as tests that rely on polymerase chain reaction to amplify and detect specific DNA molecules—require bulky and expensive equipment, as well as trained personnel to operate these machines,” says co-first author Nicholas Ho, a researcher from NUS BIGHEART and IMCB. “With enVision, we are essentially bringing the clinical laboratory to the patient. Minimal training is needed to administer the test and interpret the results so more patients can have access to effective, lab-quality diagnostics that will substantially improve the quality of care and treatment,” Ho says.

EnVision adopts a “plug-and-play” modular design and uses microfluidic technology to reduce the number of samples and biochemical reagents required, as well as to optimize the technology’s sensitivity for visual readouts. “The enVision platform has three key steps—target recognition, target-independent signal enhancement, and visual detection. It employs a unique set of molecular switches, composed of enzyme-DNA nanostructures, to accurately detect, as well as convert and amplify molecular information into visible signals for disease diagnosis,” explains co-first author Lim Geok Soon, a researcher from NUS BIGHEART and IMCB.

Each test is housed in a tiny plastic chip that is preloaded with a DNA molecular machine that is designed to recognize disease-specific molecules. Researchers then place the chip in a common signal cartridge that contains another DNA molecular machine responsible for producing visual signals when it detects disease-specific molecules.

The innovative design allows for multiple units of the same test chip or a collection of test chips to detect different diseases onto the common cartridge. “Having a target-independent signal enhancement step frees up the design possibilities for the recognition element. This allows enVision to be programmed as a biochemical computer with varying signals for different combinations of target pathogens,” Ho says.

“This can be very useful to monitor populations for multiple diseases like dengue and malaria simultaneously, or testing for highly mutable pathogens like the flu with high sensitivity and specificity,” Ho says.

The research team foresees that a smartphone app could include more advanced image correction and analysis algorithms to further improve its performance for real-world application.

Source: National University of Singapore

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