enVisioning the future of disease diagnostics
The tiny device is able to quickly and accurately screen for a range of illnesses
A test kit that can fit into the palm of a hand could be changing the face of disease screening and diagnosis. Developed by a multidisciplinary team of NUS researchers, the device named enVision (enzyme-assisted nanocomplexes for visual identification of nucleic acids) is a versatile platform that can conduct specific and sensitive screening and detection for a range of diseases, from infectious diseases and high-prevalence infections, to various types of cancers and genetic diseases.
More effective and less costly than existing infection diagnostic methods, enVision, which took about one-and-a-half years to develop, takes between 30 minutes to one hour to detect diseases — two to four times faster — and each test kit costs under $1 — about 100 times cheaper.
“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. 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,” said team leader Assistant Professor Shao Huilin from the Biomedical Institute for Global Health Research and Technology (BIGHEART) at NUS and NUS Biomedical Engineering.
Patented DNA molecular machines developed by the research team form the backbone of enVision.
“The first machine is a recognition nanostructure which detects specific genetic sequences that relate to different kinds of diseases — the pathogens, bacteria or viruses for example — and produces a signal. It pairs up with what we call an amplifier nanostructure which takes that signal, amplifies it and turns it into a colour read-out,” explained Dr Nicholas Ho, Research Fellow at NUS BIGHEART and the Institute of Molecular and Cell Biology (IMCB) under the Agency for Science, Technology and Research, and co-first author of the study.
The molecular machines were integrated into plastic chips and cartridges which gives enVision a “plug-and-play” modular design. A sample to be analysed — which can be a range of bodily fluids such as urine, blood or saliva — is first placed into the input point of a tiny plastic chip that holds the DNA molecular machine that detects genetic sequences. The sample is then channelled into a reaction chamber housed on a common signal cartridge containing the second molecular machine.
The test results are easily visible — the assay turns from colourless to brown if a disease is present, and the intensity of the colour is proportional to the amount of the pathogen that is present. The darker the colour, the more pathogen there is. Smartphone applications developed by the team can be used to further quantitatively assess the amount of pathogen. This makes the test very suitable for telemedicine or personal healthcare.
Up to four tiny chips can be placed into one cartridge. This means multiple units of different patient samples for the same disease can be analysed simultaneously, or a collection of chips analysed to detect for different diseases.
Using the human papillomavirus (HPV) — the key cause of cervical cancer — as a clinical model to validate the results, the team tested samples from 35 patients and found that enVision demonstrated an accuracy of 95 per cent when compared with a gold standard clinical test. Furthermore, the ability to modify the DNA molecular machines meant that enVision was able to detect substrains of the disease that the clinical test was unable to.
Asst Prof Shao (centre) with the co-first authors of the paper (from left:) Research Fellow at NUS BIGHEART and IMCB Dr Lim Geok Soon and Dr Ho
Looking to the future, the team is hoping to enhance the device’s point-of-care application by working on a sample preparation module for extraction and treatment of DNA material that can be integrated into the enVision platform. They are also looking into further improving the smartphone app to include more advanced image correction and analysis algorithms to enhance its real-world application.
The team also hopes to commercialise the device soon. “We are talking to both clinical collaborators as well as companies to further develop this and we hope that in about a year to two this could be distributed not only within Singapore but also beyond Singapore in our neighbouring countries," shared Asst Prof Shao.
The results of this research were published in Nature Communications in August.
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