Nanotechnology (Commonwealth Union) – Biomarkers have always played a significant in medical science. A variety of factors have been attributed as biomarkers which include C-reactive Protein, blood pressure and cholesterol. Researchers recently found a biomarker for glioblastoma which has the ability to avoid surgery for diagnosis.
Scientists at the Nanyang Technological University (NTU) have created an advanced biochip that, when combined with Artificial Intelligence (AI), can rapidly and precisely identify extremely low levels of microRNAs — tiny genetic indicators associated with illnesses such as heart disease.
The breakthrough biosensing system, detailed in the scientific journal Advanced Materials, integrates a specially engineered nanophotonic chip with AI-powered image analysis technology.
Using only a small drop of blood placed on the chip, the platform can swiftly detect several microRNA biomarkers at once. Its built-in AI imaging capability enables thousands of microRNA signals to be captured and analysed simultaneously in a single image.
In comparison with the current standard method for microRNA detection — polymerase chain reaction (PCR), which works by repeatedly amplifying tiny amounts of genetic material — the new technology reduces testing time from several hours to just 20 minutes.
MicroRNAs are tiny RNA molecules that play an important role in controlling how genes function in the body. Since abnormal microRNA levels have been associated with numerous illnesses, researchers have been exploring their use as biomarkers for diseases including cardiovascular conditions, cancer, neurodegenerative diseases, and metabolic disorders. Research from over 5 years back identified fatigue as a biomarker associated with Parkinson’s disease.
Chen Yu-Cheng, Associate Professor at Nanyang Technological University who headed the research at the School of Electrical and Electronic Engineering, said the team’s goal is to develop a platform capable of rapidly and accurately detecting multiple microRNAs, potentially enabling the identification of biomarkers connected to a broad range of diseases.
According to Prof Chen, successful experiments using lung cancer cells demonstrated that, by applying suitable probes designed for different biomarkers, the technology could eventually be modified to identify many other forms of cancer as well as cardiovascular and viral diseases. Prof Chen, known for his innovations, was included in MIT Technology Review and also serves as a professor at NTU’s Lee Kong Chian School of Medicine.
“In the future, it may be possible to use a blood or saliva sample in an automated system that screens for hundreds or even thousands of biomarkers at once. This could support large-scale screening and may help advance personalised medicine.”
The researchers developed a compact prototype featuring a colour camera capable of capturing images of the nanophotonic chip, along with a mobile application that uses AI-powered algorithms to analyse the images for microRNA and deliver rapid results.
The innovation has received support from NTU’s Innovation and Entrepreneurship initiative, while a technology disclosure has also been submitted through NTUitive, the university’s innovation and enterprise arm.
The addressing the difficulties of microRNA detection has been a significant factor many researchers. The significance of microRNAs gained global recognition in 2024, when the Nobel Prize in Physiology or Medicine honoured the discovery of microRNA and its role in regulating genes.
Detecting microRNAs remains challenging because they are extremely small, usually present in very low quantities, and many closely related microRNAs have highly similar sequences, making them difficult to distinguish. To tackle this issue, the NTU researchers created a nanocavity — a microscopic light-trapping structure that is hundreds of times thinner than a strand of human hair.
The first author of the study, Bowen Fu, a PhD student at NTU’s Institute for Digital Molecular Analytics and Science (IDMxS), said: “Our goal was to create a platform that can directly measure multiple microRNAs with very high sensitivity and at high throughput. By combining nanophotonic signal enhancement with AI-based image analysis, we were able to detect tiny amounts of RNA molecules across thousands of nanocavities within minutes.”
