Intelligent biosensor developed at INL combines NMR and AI to improve infectious disease diagnostics

In the fight against infectious diseases, rapid and accurate diagnosis is key to effective treatment and control. INL researchers have developed a breakthrough biosensor that combines cutting-edge nuclear magnetic resonance (NMR) technology with artificial intelligence. This portable device not only speeds up diagnosis but also provides detailed insights into the immune response, opening new possibilities for point-of-care testing.

The study, led by Juan Gallo and Weng Kung Peng published in the journal Biosensors and Bioelectronics, demonstrates how this innovative approach can detect viral infections and monitor patient recovery faster and more precisely than traditional methods, all within a compact, user-friendly system.

The technology uses magnetic nanoparticles specifically designed to detect viral particles, as well as the immune response they trigger in the body. When these nanoparticles bind to target molecules in a small biological sample, they cause measurable changes in the sample’s magnetic properties. These changes are captured by the portable NMR system and translated into meaningful diagnostic information using machine learning models.

“What sets this system apart is its ability to offer a more complete picture of the patient’s status,” explains Juan Gallo. “It doesn’t just tell you if someone is infected – it can help determine whether they are in the early stages, recovering, or already immune. And it does all this using a fast, accessible, and portable platform. It is the first time that this multiplexing ability is demonstrated on NMR-based systems.”

The team validated the system using COVID-19 samples, achieving high accuracy rates and consistent results. They also demonstrated the sensor’s ability to reliably measure immune markers, such as antibodies, confirming its potential for both diagnosis and ongoing monitoring of patient recovery.

This dual-detection strategy – simultaneously identifying viral antigens and antibodies – offers more comprehensive clinical information than typical rapid tests. It allows healthcare providers to distinguish between active infection and past exposure, assess a patient’s immune status, and make better-informed decisions about treatment and isolation.

Although this study focused on SARS-CoV-2, the platform is designed to be adaptable. Future versions will expand its detection capabilities to other pathogens and enhance antibody analysis by distinguishing between different immune responses. Specifically, while the current system measures total anti-nucleocapsid antibodies, upcoming developments aim to differentiate IgM and IgG antibodies – markers that indicate recent or ongoing infection and past infection or immunity, respectively. This advancement will provide more detailed insights into the stage and progression of the immune response.

“This is not just a diagnostic tool,” concludes Juan Gallo. “It’s a step towards smarter, more responsive healthcare systems, especially in scenarios where time, precision, and accessibility are crucial.”

Text and Photography by Catarina Moura, Science Communication Officer