Professor Song Min-ho of the Korea Advanced Institute of Science and Technology (KAIST) has a unique background. He graduated from Chungnam National University School of Medicine in 1986 and has worked as an endocrinologist for nearly 40 years. He also served as the president of Chungnam National University Hospital. While there are several professors from a medical background at KAIST, he is the first to come from a university hospital presidency. Despite the opportunity to earn a substantial income without difficulties as a nursing hospital director after retirement, he chose to move to KAIST to continue his research as he approached retirement.

On the 8th, meeting Professor Song at the KAIST Daejeon Munji Campus, he said, “Since my time in the hospital, I have emphasized to my juniors that physicians should also engage in research, yet I did not want to show myself moving toward positions like a nursing hospital president after retirement.” He noted, “Artificial intelligence (AI) will change the way we treat and the concept of medicine,” and stated, “I have decided I want to produce new knowledge for Korean medicine.”

Song Min-ho, a professor at KAIST Graduate School of Medical Science, is a researcher with a background as a physician who served as the director of Chungnam National University Hospital. He is currently engaged in multi-omics research for healthy aging./Courtesy of KAIST

The research field that Professor Song chose, rejecting the easier path, is Multiomics research. Omics is a field studying various assemblies of living organisms. Multiomics is a technology that comprehensively analyzes an individual's health status using data from various assemblies, including genome, transcriptome, proteome, metabolome, epigenome, and lipidome.

Current health check-ups allow individuals to examine their past and present health conditions, but predicting how it will change in the future is challenging. Professor Song stated that he intends to gather the entirety of human genetic information, the proteins made from it, metabolic substances, and even the complete information of the microorganisms cohabiting within the human body, to train AI.

In other words, it is about teaching AI the big data related to an individual's health. Collecting this information creates a digital twin that accurately reflects the physical entity of a human in a virtual world. Professor Song's goal is for AI to diagnose an individual's health state precisely and to simulate with the digital twin to suggest personalized treatments and lifestyle habits.

Professor Song emphasized, “Current health check-ups only confirm that my body is fine today, and the information provided by the physician from the results is often repetitive,” and added, “Unpersonalized healthcare is meaningless.” He remarked, “With the emergence of AI, the role of medicine will be to suggest ways to avoid illness in the future.”

The more refined Multiomics analysis technology becomes, the more accurately it can predict which diseases a person might get and what ailments they may develop. If diseases can be predicted, it will also be possible to suggest methods to avoid them in advance.

Professor Song stated that a type of navigation will be needed to help predict an individual's health status ahead of time and to age healthily. To this end, he partnered with Professor Adil Mardinoglu of King's College London (KCL) to establish a company called 'Silklongevity.' Silklongevity is part of a large-scale Multiomics research project led by KCL.

Professor Song explained, “For Multiomics to function effectively, global data collection is essential,” noting that there is a collaborative network in London and Stockholm in the UK, San Diego and Pittsburgh in the U.S., Istanbul in Turkey, and Bengaluru in India, with Silklongevity overseeing the project in Korea.

Song Min-ho (right), a professor at KAIST Graduate School of Medical Science, with lab students./Courtesy of KAIST

KCL's Multiomics project also involves Illumina, the world's largest gene analysis equipment company, along with IT companies such as NVIDIA and Amazon, which are actively investing in the bio sector. The goal is to collect Multiomics data from 1 million people worldwide within a short timeframe and to create personalized disease occurrence analysis services from this research. Professor Song remarked, “We have already decided to collaborate with several university hospitals in Korea for this project, and local governments like Gimhae City have also agreed to participate.”

Like the national bio big data project, initiatives to gather Multiomics data are also underway at a government level. However, Professor Song pointed out that speed is crucial in Multiomics research. He said, “The government project aims to collect the genomes of one million people by 2032, but analyzing that data and applying it to actual patients will likely not be feasible until the mid-2030s,” and emphasized, “To provide benefits to the people currently supplying data, we need to accelerate the pace.”

Professor Song noted that healthy aging will become a key keyword not only for healthcare but for society as a whole. He pointed out that Korea is rapidly transitioning into a low birthrate and aging society, emphasizing that if solutions for healthy aging are not found, the societal burden will increase.

Professor Song stated, “Diseases like diabetes, dementia, and hypertension are mostly incurable, and by the time one reaches their 70s or 80s, an individual can typically be taking about 10 medications,” adding, “Healthcare and medicine that do not extend people's healthy lifespan and only allow pharmaceutical companies to profit have their limits.”