Monthly People
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About this ebook
Connecting people to people,
Connecting people and values.
We see the future through people. We interview entrepreneurs, scientists, government officials, politicians, and others to see a better vision.
We hope that you, the reader, will use us as a medium to create better opportunities.
We hope that the stories of the people introduced through Monthly People will inspire you to have a better future and vision.
We bring to life the stories of people who are responding to the issues of the day and making innovations in various fields through on-site interviews.
Through our content, we aim to provide our readers with forward-thinking insights and inspire them to create their own lives and opportunities.
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Monthly People - Sung-rae Park
Monthly Column
1715767043413_2Sijung Yoon Ph.D.
Research and Adjunct Professor, Genomics, Johns Hopkins University
President and Chief Operating Officer, PredictiveCare
Precision Medicine and Digital Twin
T
he average life expectancy of South Koreans has been increasing rapidly in recent decades. The average life expectancy rose from 41.7 years immediately after the Korean War to 83.6 years in 2023, making it one of the seven longest-lived countries in the world. The main reason for this steep rise is regular health check-ups, which are not yet common in other countries. The majority of the population undergoes a health check-up every one or two years, which allows for early diagnosis of many potentially life-threatening diseases. This prevention and management has led to an increase in healthy life expectancy, a measure of how long people live in good health.
However, the rate of increase in life expectancy has recently slowed down, suggesting that the current system and methods have reached their limits in increasing life expectancy and healthy life expectancy. In addition, Korean society is experiencing a rapidly declining fertility rate. If this combination of declining life expectancy and healthy life expectancy and ultra-low birthrate continues, we will face a national economic crisis due to an unprecedentedly rapid decline in the labour force. However, there is currently no clear solution to this gloomy forecast that every Korean is familiar with.
Digital twin-based precision medicine is a technology developed about 20 years ago as a way to optimise the design of aircraft engines, large buildings, etc. by pre-implementing and simulating twin models in the virtual world. It can be applied to humans as well, with basic implementations such as online phone books, KakaoTalk profile pictures, and avatars in the metaverse.
Digital twins become more effective the more quality data you feed them. Imagine if you had thousands of pages of the Seoul phone book online. This could be a digital twin in a primitive sense. The representation of your digital twin in the phone book becomes your name
and you can search for a phone number by that name. However, this is unlikely to be useful beyond the basic ability to look up a phone number and tell you some fun facts about your name and phone number, such as how many people in Seoul have the same name as you. To make a digital twin of a person useful, you need more specific and helpful data about them than just their name and profile picture.
We all have unique genetic information. By creating a digital twin based on this unique data, you can learn a lot about your health and be prepared. With the exception of identical twins, the approximately 3 billion sequences in the chromosomes of each of your cells are ∂uniq∂ue to you, and it is currently possible to test your blood, oral epithelial cells, or fingernails for less than $1,000. Recent advances in science and technology have made it easy to learn the seque∂nce of your 3 billion bases within days. Knowing the sequences of all of the 20,000 proteins that make up the various functions in your body can tell you a lot about your health by comparing it to various databases of health information.
For example, you can know which cancers you are more likely to develop, and you can predict your risk of developing genetic diseases such as haemophilia or complex conditions such as diabetes. But importantly, even if you don't know when you'll develop these diseases, and even if you're at high risk, such as for diabetes, you can manage your diet and exercise habits so that you don't develop them in your lifetime. In other words, with the exception of rare genetic disorders, you can take steps to prevent the diseases to which you are genetically susceptible and live a healthier, longer life. While it makes sense to accurately predict the probability of precipitation if it's a natural phenomenon like rain that we can't change, I think it's pointless to predict the exact probability of a disease, even if it's statistically likely that you'll get it, if you can prevent it through preventive medicine. However, there is great value in knowing which diseases you are susceptible to so that you can take preemptive measures to prevent them from developing.
Genetic information not only tells you what diseases you are genetically susceptible to, but also your personal drug sensitivity. You may have taken a medication on the recommendation of a friend or spouse, but it didn't work well for you. Did you know that the experience of your parents or siblings may be more useful than a friend or spouse who has no genetic connection to you when it comes to saying, This medication works well for this symptom?
This is because many medications are converted into active ingredients by the action of enzyme proteins in the liver, and the type of enzyme protein is determined by genetics. Therefore, a medication recommended by a genetically related parent or sibling is likely to be more effective for you. However, it's unlikely that they've tried all of the hundreds or thousands of medications on the market, and it's not always possible for a parent's genetic makeup to be exactly the same as their child's, so it's best to use your own genetic information to determine your drug sensitivity. Knowing your drug susceptibility allows for more effective and safer treatment because you know which drugs work for you and which ones may cause side effects.
Imagine creating a digital twin of this vast amount of information (3 billion sequences) as a report. It would be quite a report to begin with. It would be a very inconvenient and inefficient way to view the information, requiring you to flip through pages and pages to find the information you want or need. Therefore, a successful digital twin requires a digital twin system that stores genetic information on a website and allows you to selectively view the information you need. Combine this with electronic medical records and AI, and you have a platform that can predict your health and healthcare more precisely and extend your life.
The United States is already working on the