11 MARTINDALE CENTER FOR THE STUDY OF PRIVATE ENTERPRISE development in the post-pandemic era. Launched that same year, the TPHI encompasses precision medicine, regenerative health, and digital health innovation (Hsiao et al., 2022). The Taiwan National Development Council identified precision health as a strategic priority with the hope of integrating data from the Taiwan Biobank and the National Health Insurance (NHI) Research Database (International Trade Administration, 2023). By leveraging big data analysis, epidemic prevention products can be developed, positioning Taiwan as a global leader in public health preparedness. As outlined in the following sections, the three components of the precision medicine initiative are expressly interconnected. Precision medicine Precision medicine is geared toward disease treatment, acknowledging the genetic and environmental influences on a patient’s course of recovery or health goals (Hsiao et al., 2022). One of the core components of precision medicine in Taiwan is the biobank system, which allows a shift to optimizing care on a population level in terms of disease identification and treatment by tracking confirmed cases and at-risk individuals. Taiwan was determined not to fall behind during the global race in advanced biomedicine. Former health minister Chen Shih-chung (2017) expressed that “disease knows no borders,” and Taiwan continued to share COVID-19 data with the World Health Organization, despite not obtaining membership (Chen & Cohen, 2020). Taiwan’s Academia Sinica, established in 1928 and comprising nine scientific research centers, has been instrumental in the development of precision medicine. It directs the Taiwan Precision Medicine Initiative (which focuses on early diagnosis through big data analysis) and established the Taiwan Biobank in 2012. The goal of having a comprehensive biobank is to have a repository for researchers to better understand the relationship between genetics, environmental factors, and health issues at both the individual and population levels (Wei, 2021), enabling deep epidemiological inquiries and expanded genomic and medical research. Taiwan’s population size is ideal for genomic tracking: large enough to detect health trends yet small enough for extensive monitoring with limited migration and comprehensive NHI registrations. The funding of the biobank comes from Academia Sinica’s Institute of Biomedical Sciences, which is also responsible for managing and determining its budget. Unfortunately, no specific numbers are publicly available about how the funding is allocated. After congressional approval, the institute’s funding is distributed directly by the Taiwan president’s office (Borman, 2009). The most recent data available are from 1998, when the National Development Fund invested NT$20 billion (US$622,171,000) to expand the biotechnology industry (Harmon et al., 2018). Investments in precision medicine will ensure that the industry continues to gain traction, as emphasized by President Lai Ching-te in his inauguration speech: “we must also make bold investments in quantum computing, robotics, the metaverse, precision medicine, and other advanced technologies, thus giving our young people the opportunity to pursue their dreams and solidifying Taiwan’s leading position in the future global landscape” (Office of the President…, 2024). Biotechnology is crucial for Taiwan’s development, and both former President Tsai’s and current President Lai’s commitment to precision medicine signal support at a presidential level. Individualized data in the Taiwan Biobank are collected regularly from volunteer contributors. Currently there are 197,046 baseline participants and 70,000 follow-up participants, ages 20 to 70 (Taiwan Biobank, 2024). The Taiwan Biobank is one of the largest biobanks for populations of Asian origin, a profound achievement in terms of genome-wide association studies (Chen et al., 2023). Volunteers have expressed gratitude for the research due to the opportunity to better understand their genetic makeup for future generations and the possibility of effective drug creation based on the longitudinal data (Tsai & Lee, 2020). With access to this large database, researchers have an alternative way to understand the etiology of a disease. Analyzing a patient’s medical history is invaluable for elucidating individual and population health issues (Tsai & Lee, 2020). For example, by assessing diabetic patients’ blood level trends along with their dietary choices, exercise routines, and gut microbiome diversity, artificial intelligence (AI) can use a biobank to predict glycemic responses and customize treatment recommendations (Hsiao et al., 2022). This personalization allows individuals to better understand their own health risks and is more effective than universal guidance reliant on a multitude of population-level variables. Wei and colleagues (2021) utilized 103,106 genetic profiles from the biobank to study disease and drug response issues in the Han Chinese population. The genomic assessment used single-nucleotide polymorphism assays, the most common form of genetic variation. One nucleotide base is replaced with another, sometimes causing differences in how traits are expressed, drug metabolism, and risk of
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