Researchers develop nasal antiviral platform using AI technology to block flu and COVID-19​

Respiratory viruses that have diverse strains and mutate rapidly, such as influenza and COVID-19, are difficult to block perfectly with vaccines alone. To solve this problem, KAIST's research team has successfully developed a nasal (intranasal) antiviral platform using AI technology to overcome the existing limitations of interferon-lambda treatments—namely, being "weak against heat and disappearing quickly from the nasal mucosa."

KAIST announced on December 15th that a joint research team—consisting of Professor Ho Min Kim and Professor Hyun Jung Chung from the Department of Biological Sciences, and Professor Ji Eun Oh from the Graduate School of Medical Science and Engineering used AI to stably redesign the interferon-lambda protein and combined it with a delivery technology that ensures effective diffusion and long-term retention in the nasal mucosa, thereby implementing a universal prevention technology for various respiratory viruses.

Interferon-lambda is an innate immune protein produced by the body to block viral infections, playing a crucial role in stopping respiratory viruses like the common cold, flu, and COVID-19. However, when formulated as a treatment for nasal administration, its actual efficacy was limited by its vulnerability to heat, degrading enzymes, mucus, and ciliary motion.

The research team used AI protein design technology to precisely reinforce the structural weaknesses of interferon-lambda.

First, they significantly increased stability by changing the loose "loop" structures of the protein—which were prone to instability—into rigid "helix" structures that lock in place like a firm spring.

Additionally, to prevent "aggregation" (proteins sticking together to form lumps), they applied "surface engineering" to make the surface more water-compatible. They also introduced "glycoengineering," adding sugar chain (glycan) structures to the protein surface to make it even more robust and stable.

As a result, the newly produced interferon-lambda showed a massive improvement in stability, surviving for two weeks 50℃ and demonstrated the ability to diffuse rapidly even through thick nasal mucus.

The research team further protected the protein by encapsulating it in microscopic "nanoliposomes" and coated the surface with "low-molecular-weight chitosan." This significantly enhanced "mucoadhesion," allowing the treatment to stick to the nasal lining for an extended period.

When this delivery platform was applied to animal models infected with influenza, a powerful inhibitory effect was confirmed, with the virus level in the nasal cavity decreasing by more than 85%.

This technology is a mucosal immune platform that can block viral infections in their early stages simply by spraying it into the nose. It is expected to be a new therapeutic strategy that can respond quickly not only to seasonal flu but also to unexpected new or mutant viruses.

Through AI-based protein design and mucosal delivery technology, we have simultaneously overcome the stability and retention time limitations of existing interferon-lambda treatments. This platform, which is stable at high temperatures and stays in the mucosa for a long time, is an innovative technology that can be used even in developing countries lacking strict cold-chain infrastructure. It also has great scalability for developing various treatments and vaccines. This is a meaningful achievement resulting from multidisciplinary convergence research, covering everything from AI protein design to drug delivery optimization and immune evaluation through infection models."

Professor Ho Min Kim, Department of Biological Sciences, KAIST

This research involved Dr. Jeongwon Yun from the KAIST InnoCORE (AI-Innovation Drug Discovery Research Group), Dr. Seungju Yang from the Department of Biological Sciences, and PhD student Jae Hyuk Kwon from the Graduate School of Medical Science and Engineering as co-first authors. The results were published consecutively in the renowned international journals Advanced Science (Nov 20) and Biomaterials Research (Nov 21).

• Paper 1: Computational Design and Glycoengineering of Interferon-Lambda for Nasal Prophylaxis against Respiratory Viruses, Advanced Science, DOI: 10.1002/advs.202506764
• Paper 2: Intranasal Nanoliposomes Delivering Interferon Lambda with Enhanced Mucosal Retention as an Antiviral, Biomaterials Research, DOI: 10.34133/bmr.0287

This research was conducted with support from the KAIST InnoCORE Program, the National Research Foundation of Korea (NRF) Mid-Career Researcher Support Program, the Bio-Medical Technology Development Program, the Korea Health Industry Development Institute (KHIDI) Health and Medical Technology R&D Project, the KAIST Large-scale Convergence Research Institute Operation Project, and the Institute for Basic Science (IBS).