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

Area of Science:

• Precision Health and Bioinformatics
• Genomics and Personalized Medicine
• Public Health and Epidemiology

Background:

• Precision health encompasses disease prediction, prevention, treatment, and management, extending beyond precision medicine.
• It utilizes genetics, lifestyle, social determinants, and environmental factors for personalized health strategies.
• Biobanks are vital for precision health, providing samples and data for disease prediction, diagnosis, and treatment.

Purpose of the Study:

• To explore the role of biobanks in advancing precision health.
• To identify challenges in biobank integration and propose solutions.
• To recommend strategies for leveraging biobanks for population-level health research.

Main Methods:

• Literature review on precision health and biobank integration.
• Development of a dynamic consent mechanism using digitalization and blockchain technology.
• Case study implementation at Taoyuan Tiansheng Hospital.

Main Results:

• Biobank integration faces challenges like data inconsistency, privacy concerns, and legal issues.
• Digitalization and standardized methodologies can overcome integration hurdles.
• A dynamic consent model using blockchain technology was proposed and validated in a case study.

Conclusions:

• Integrating population-based biobanks with dynamic consent is crucial for precision health.
• Recommended strategies enhance biobank utility for diverse disease research.
• The study provides insights for researchers, healthcare professionals, and policymakers in precision healthcare.