Integrating population-based biobanks: Catalyst for advances in precision health

Precision health extends beyond the scope of precision medicine and involves a broader range of activities, including the prediction, prevention, treatment, and management of diseases. Tailored to specific populations, precision health offers personalized treatment and preventive measures considering genetics, lifestyle behaviors, social determinants of health, and environmental factors. Precision medicine focuses on the personalized treatment of diseases, whereas precision health aims to promote health and prevent diseases using tools such as big data and advanced analytics to predict health risks and prevent diseases at the population level. Biobanks play a crucial role in achieving precision health because they provide well-characterized biological samples and related data for disease prediction, diagnosis, and treatment. Challenges in integrating different biobanks include data format consistency, privacy concerns, and legal constraints. Standardized methodologies and digitalization can mitigate these challenges. The integration of biobanks can facilitate comprehensive analyses across multiple datasets to achieve various research goals. This study proposes strategies to address these challenges, including the development of a dynamic consent mechanism for population-based biobanks using digitalization and blockchain technology. This study recommends the following: 1) integrating population-based biobanks, 2) introducing dynamic consent tools for human biobanks, and 3) using large human biobanks with dynamic consent for research on diverse diseases. These recommendations can increase the utility of biobanks in realizing precision health. A case study implemented at Taoyuan Tiansheng Hospital demonstrated the effectiveness of these recommendations for achieving precision health and enhancing the value of biobanks. Through a comprehensive examination of precision health and biobanks, this study provides valuable insights for researchers, healthcare professionals, and policymakers in the precision healthcare sector.

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Publication Details

Journal
Computational and Structural Biotechnology Journal
Published
2024-11-05
DOI
https://doi.org/10.1016/j.csbj.2024.10.049
Citations
9
Primary Topic
Ethics in Clinical Research
Type
article
Field-Weighted Citation Impact
4.89
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article

Integrating population-based biobanks: Catalyst for advances in precision health

Jui-Chu Lin, Yukun Liu, Chien-Te Fan, Wesley Wei‐Wen Hsiao
9 citations
Computational and Structural Biotechnology Journal
Ethics in Clinical Research
4.89
article

Integrating population-based biobanks: Catalyst for advances in precision health

Jui-Chu Lin, Yukun Liu, Chien-Te Fan, Wesley Wei‐Wen Hsiao
article en
9 citations

Abstract

Precision health extends beyond the scope of precision medicine and involves a broader range of activities, including the prediction, prevention, treatment, and management of diseases. Tailored to specific populations, precision health offers personalized treatment and preventive measures considering genetics, lifestyle behaviors, social determinants of health, and environmental factors. Precision medicine focuses on the personalized treatment of diseases, whereas precision health aims to promote health and prevent diseases using tools such as big data and advanced analytics to predict health risks and prevent diseases at the population level. Biobanks play a crucial role in achieving precision health because they provide well-characterized biological samples and related data for disease prediction, diagnosis, and treatment. Challenges in integrating different biobanks include data format consistency, privacy concerns, and legal constraints. Standardized methodologies and digitalization can mitigate these challenges. The integration of biobanks can facilitate comprehensive analyses across multiple datasets to achieve various research goals. This study proposes strategies to address these challenges, including the development of a dynamic consent mechanism for population-based biobanks using digitalization and blockchain technology. This study recommends the following: 1) integrating population-based biobanks, 2) introducing dynamic consent tools for human biobanks, and 3) using large human biobanks with dynamic consent for research on diverse diseases. These recommendations can increase the utility of biobanks in realizing precision health. A case study implemented at Taoyuan Tiansheng Hospital demonstrated the effectiveness of these recommendations for achieving precision health and enhancing the value of biobanks. Through a comprehensive examination of precision health and biobanks, this study provides valuable insights for researchers, healthcare professionals, and policymakers in the precision healthcare sector.

Computational and Structural Biotechnology JournalVol. 24
National Taiwan University of Science and Technology (TW), National Tsing Hua University (TW), Min Sheng General Hospital (TW)
Openalex Percentile: Top 4%
Ethics in Clinical Research
4.89
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