Discovery of Candidate Drugs to Suppress Hearing Loss Side Effects... Success of AI and Zebrafish Combined Platform

Korea University Ansan Hospital and College of Medicine Research Team

"Six Existing Drugs Shown to Have Inhibitory Effects"

A candidate drug that could reduce the risk of hearing loss caused by aminoglycoside antibiotics has been discovered. This study selected substances with potential efficacy from among existing drugs by combining artificial intelligence (AI) analysis with animal experiments.

(From left) Jun Choi, Professor of Otorhinolaryngology at Korea University Ansan Hospital, Eunjeong Han, Professor at Korea University Zebra Fish Translational Medicine Research Center. Korea University Ansan Hospital

On March 13, Korea University Ansan Hospital announced that the research team led by Professor Jun Choi of the Department of Otorhinolaryngology at Korea University Ansan Hospital and Professor Eunjeong Han of the Zebrafish Translational Medicine Research Center at Korea University College of Medicine has identified candidate drugs capable of suppressing antibiotic-induced hearing loss by combining AI-based drug analysis with zebrafish animal experiments. The research findings were recently published in the journal "Hearing Research," which specializes in auditory studies.

Aminoglycoside antibiotics are widely used to treat tuberculosis and severe bacterial infections, but they can damage "hair cells," the sensory cells of the inner ear, leading to hearing loss. It is known that once hair cells are damaged, they are difficult to regenerate, which can result in permanent hearing impairment.

The research team analyzed the molecular structures and toxicity data of 2,253 drugs using an AI screening model and selected 28 candidate substances with the potential to suppress hearing loss side effects. The inhibitory effects of these candidates were then validated using a zebrafish model. Zebrafish are widely used in drug toxicity research because of their high genetic similarity to humans.

Experimental results showed that six drugs—ammonium lactate solution, L-glutamine, malic acid, dexpanthenol, calcium citrate, and strontium ranelate—significantly suppressed aminoglycoside-induced hair cell damage out of the 28 candidates.

In zebrafish exposed to aminoglycosides, the number of hair cells decreased to about half compared to normal, but when candidate drugs were administered concurrently, hair cell survival was protected by approximately 15–25%.

The research team explained that the approach of selecting candidate substances through AI-based drug analysis and then validating them with animal experiments can improve the efficiency of large-scale drug screening. They also noted that this method holds promise for "drug repositioning" research, which seeks new therapeutic uses for already approved drugs.

Professor Choi stated, "We have confirmed the potential of a research platform that combines AI-based drug analysis with zebrafish experiments," adding, "If applied to drug repositioning research in the future, it could accelerate the development of new therapeutics."

This content was produced with the assistance of AI translation services.