Research database

STELLAR introduces a groundbreaking approach to early cancer detection, leveraging surface-enhanced Raman spectroscopy (SERS) and artificial intelligence (AI) to analyse microRNAs (miRNAs) in liquid biopsies. This innovative technology aims to revolutionize cancer screening by offering a non-invasive, cost-effective, and highly accurate method for identifying cancer-specific miRNA biomarkers. STELLAR's core innovation lies in its ability to detect and discriminate between normal and mutated miRNAs with exceptional accuracy, even at the level of single nucleotide polymorphisms, without the need for expensive and complex sequencing technologies. The project encompasses the development of a comprehensive system, including a novel miRNA isolation and enrichment method, a SERS-based detection platform utilizing silver nanoparticle-enhanced substrates, and an AI algorithm for data analysis. This integrated approach promises to overcome current limitations in miRNA-based cancer diagnostics, such as high costs, lengthy processing times, and the need for specialized equipment and personnel. STELLAR aims to progress from TRL 2/3 to TRL 4/5, validating the technology with clinical samples and establishing a clear path toward commercialization. The project's multifaceted strategy includes rigorous technical development, IP protection, regulatory planning, and market analysis. The project's success could significantly impact early cancer detection rates, improving patient outcomes and reducing healthcare costs. STELLAR's approach to combining SERS technology with AI-driven analysis opens new avenues for personalized medicine and could set new standards for AI-integrated medical devices. As the project progresses, it will explore various commercialization pathways, including the potential creation of a spin-out company or licensing agreements, with the goal of bringing this transformative technology to market and making a substantial impact on global health.