Seeing patients day after day reveals something striking: even when people have the same illness, their symptoms and their responses to treatment differ. The gap is not only a matter of age or sex. Patients of similar age and constitution, and of the same sex, can react in markedly different ways. That is why treatment tailored to a patient's overall health and lifestyle matters. So what if, before treatment begins, a virtual patient identical to the real one could be created to predict in advance how well a therapy will work?
The digital twin, a technology drawing attention in medicine of late, is an attempt to turn that idea into reality. A digital twin replicates a real-world object or system in virtual space. Until now it has been used mainly in manufacturing, to predict equipment failures or improve production processes. More recently its scope has widened into health care, where it is being studied as a way to project an individual's health status, the course of a disease and the changes that follow treatment.
The core of a medical digital twin lies in linking a person's varied health information into a single model. Health screening results, medical records and medication data are combined with information gathered in daily life, such as heart rate, sleep duration and physical activity, to build a virtual patient. As new information is continuously fed in, it becomes possible to track changes in health and to simulate how a particular treatment or a change in lifestyle would affect the body.
Research on using digital twins in health management is active. A study published in the international journal npj Digital Medicine examined the potential of digital twins in precision medicine. The researchers screened 1,321 publications and analyzed the 12 studies that met their selection criteria, finding positive results in 36 of 45 outcome measures, or 80%, across health management, tailored treatment and disease risk prediction.
What stands out is that the individualized care digital twins aim for overlaps with a principle Korean medicine has long emphasized. Korean medicine speaks of dongbyeongichi, meaning that the same illness is treated differently depending on the characteristics of the patient. A Korean medicine doctor decides on a course of treatment by weighing not only symptoms but also complexion, constitution and everyday habits. Herbal prescriptions likewise vary in composition and dosage according to the patient's condition. In taking each patient's differences as the starting point of treatment, the approach shares common ground with the precision medicine that digital twins pursue.
Clinical outcomes of integrative Korean medicine treatment that accounts for a patient's condition have also been studied. A Jaseng Hospital of Korean Medicine study published in the international journal Medicine reviewed the medical records of 1,788 traffic accident patients aged 65 and over who were admitted to the Gangnam, Bucheon, Daejeon and Haeundae Jaseng Hospitals of Korean Medicine between 2021 and 2023. After integrative treatment combining acupuncture, pharmacopuncture, herbal medicine and Chuna manual therapy, neck pain scores on the numeric rating scale fell from an average of 5.17 to 3.49, and lower back pain from 5.19 to 3.55. Quality-of-life measures improved as well. Because the analysis compared conditions before and after treatment, however, whether the improvement can be attributed to integrative Korean medicine treatment alone needs to be confirmed through further research.
If the clinical experience of Korean medicine is combined with data technology, the scope for tailored treatment could widen further. Systematically accumulating and analyzing patients' symptoms, constitutions, lifestyles, prescriptions and treatment courses would make it possible to identify in more concrete terms which patients, with which characteristics, respond better to which treatments. Applying such information to digital twin technology could in turn help predict treatment outcomes in advance and refine treatment strategies for individual patients.
Digital twins have not, of course, reached the stage of perfectly reproducing every change in the human body. Plenty of challenges remain, including the accuracy of medical information, the protection of personal data and the clinical validation of predictions. Even so, the direction medicine is heading is clear: finding the treatment best suited not to an "average patient" but to the one person in front of you. Should Korean medicine's experience of valuing each patient's individual traits meet advanced data technology, new possibilities may open for tailored care.
