A new biosensing platform from NTU Singapore combines a nanophotonic chip with AI to detect microRNA biomarkers in just 20 minutes—a process that currently takes hours.
Breakthrough in Rapid Disease Detection
Researchers at Nanyang Technological University (NTU), Singapore, have developed a biosensing platform that integrates a nanophotonic chip with AI-automated image analysis. The system can analyze multiple microRNA biomarkers from a small blood sample in approximately 20 minutes, a significant improvement over the hours required by standard methods. The findings were published in the journal Advanced Materials.
Technical Specifications
The platform's core is a nanocavity structure—light-trapping features hundreds of times smaller than a human hair. These cavities enhance fluorescent signals when a target microRNA binds to a matching probe.
An integrated AI imaging system, powered by a deep-learning model called Mask R-CNN, captures and analyzes thousands of microRNA signals in a single snapshot. This allows for the direct, quantitative detection of multiple microRNAs in liquid samples without requiring labeled probes or amplification.
Testing and Performance
The system was tested by measuring three microRNAs associated with non-small cell lung cancer (miR-191, miR-25, and miR-130a) from human lung cancer cell extracts.
The platform can detect microRNAs at extremely low concentrations, down to a few molecules per sample, and achieved over 99% accuracy in identifying targets across different test channels.
The platform also performed reliably when synthetic microRNAs were added to biological extracts.
Comparison with Existing Methods
Current standard methods for microRNA detection, like polymerase chain reaction (PCR), typically require hours and rely on labeled probes and sample amplification. In contrast, the NTU platform directly detects multiple microRNAs in liquid samples, reducing detection time to approximately 20 minutes.
Research Context
MicroRNAs are short RNA molecules involved in gene regulation. Changes in microRNA levels are associated with various diseases, including cardiovascular disease, cancer, neurodegenerative disorders, and metabolic illnesses. The 2024 Nobel Prize in Physiology or Medicine recognized the discovery of microRNA and its role in gene regulation.
Standard detection methods like PCR are time-consuming and require amplification. The small size, low concentrations, and similar sequences among related microRNA types make them particularly challenging to detect.
Development Status
The research team has constructed a compact prototype that includes a color camera to capture chip images and a mobile phone application designed to analyze the images using AI algorithms.
A technology disclosure has been filed through NTUitive, the university's innovation and enterprise company. The study was supported by the Singapore Ministry of Education Academic Research Fund Tier 1 grant and the Agency for Science, Technology and Research's Manufacturing, Trade and Connectivity Interdisciplinary Research Grant.
Future Applications and Next Steps
The researchers aim to build a system that can quickly and accurately measure multiple microRNAs for potential detection of biomarkers linked to a wide range of diseases.
Future applications could include using blood, saliva, or urine samples in automated systems that screen for hundreds or thousands of biomarkers simultaneously.
The device could also be useful for pharmaceutical companies in miRNA-related drug testing. The team plans to consult with clinicians and industry partners to scale up further trials on other microRNA markers.
Statements
NTU Associate Professor Chen Yu-Cheng, who led the study, stated: "Our successful tests with lung cancer cells show that, with the right probes targeting different biomarkers, this technology could potentially be adapted for many other cancers and diseases, including cardiovascular and viral diseases."
Bowen Fu, a PhD student at NTU and the study's first author, said: "Our goal was to create a platform that can directly measure multiple microRNAs with very high sensitivity and at high throughput."
Associate Professor Sunny Wong Hei, a consultant gastroenterologist at Tan Tock Seng Hospital, commented: "A platform that can accurately detect multiple microRNAs could have huge clinical applications, including earlier detection of cancer, risk stratification of patients, and monitoring of treatment response or disease recurrence."