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Home ELSI Knowledge Base Digitalisation of Biobanks

Challenge: Digitalisation of Biobanks

Overview The digitalisation of biobanks refers to the transformation of traditional biobanking infrastructures into integrated digital ecosystems capable of collecting, managing, storing, sharing, and analyzing large volumes of biological and […]

Overview

The digitalisation of biobanks refers to the transformation of traditional biobanking infrastructures into integrated digital ecosystems capable of collecting, managing, storing, sharing, and analyzing large volumes of biological and health-related data. Beyond the management of biological specimens, digital biobanks incorporate clinical, pathological, genomic, imaging, and other molecular data into interoperable digital platforms that support biomedical research, precision medicine, and the development of data-driven healthcare solutions.

Recent advances in next-generation sequencing (NGS), digital pathology, medical imaging, artificial intelligence (AI), machine learning, and high-throughput omics technologies have generated unprecedented quantities of heterogeneous biomedical data. Digital biobanks serve as critical infrastructures for organizing these data, enabling their standardization, integration, and reuse across institutions and research domains.

Digital biobanks have the potential to facilitate the sharing of curated and standardized clinical, imaging, pathological, and molecular data, fostering the development of predictive computational models and supporting precision medicine. Similarly, the growing adoption of digital pathology and automated data acquisition systems is transforming biobanks into interconnected repositories capable of supporting translational and personalized medicine.

The digitalisation process encompasses multiple components, including digital specimen tracking, laboratory information management systems (LIMS), electronic consent management, digital pathology platforms, cloud computing infrastructures, data integration frameworks, and secure mechanisms for data sharing and governance.

 

Key Ethical, Legal and Societal Issues

Data Protection and Privacy: Digital biobanks process large volumes of sensitive personal data, including genetic, health, imaging, and lifestyle information. Ensuring compliance with data protection principles, including data minimisation, purpose limitation, and security safeguards, is therefore essential.

Informed Consent in the Digital Environment: Digitalization raises important questions regarding consent models. Traditional study-specific consent may not adequately address future secondary uses of data, international sharing, AI-driven analyses, or integration with external datasets. Dynamic consent and electronic consent models have emerged as potential solutions, enabling ongoing participant engagement and greater transparency.

Data Sharing and International Collaboration: The scientific value of digital biobanks depends on data accessibility and interoperability. However, balancing open science objectives with privacy protection remains challenging. Cross-border data transfers, differing legal frameworks, and governance requirements may complicate international collaboration.

Artificial Intelligence and Secondary Data Use: Digital biobanks increasingly support AI and machine learning applications. While these technologies can accelerate discovery and improve diagnostics, they may also introduce concerns regarding algorithmic bias, transparency, explainability, and accountability. Secondary uses of biobank data should remain consistent with ethical principles and applicable legal requirements.

Data Quality, Standardization, and Reproducibility: The integration of data generated by different technologies and institutions requires harmonized standards and metadata frameworks. Insufficient standardisation may reduce scientific validity and limit data reuse.

Equity and Digital Inclusion: Digital transformation should not exacerbate existing inequalities in healthcare and research participation. Unequal access to digital technologies, underrepresentation of specific populations, and disparities in data availability may affect the fairness and generalisability of research outcomes.

Governance and Public Trust: Public trust remains fundamental to biobank sustainability. Transparent governance structures, clear policies regarding data access and sharing, stakeholder engagement, and accountability mechanisms are necessary to maintain societal confidence in digital biobanking initiatives.

Cybersecurity and Data Security: As biobanks become increasingly digitalized, they are exposed to cybersecurity threats such as unauthorized access, ransomware attacks, data breaches, and system failures. Robust technical and organisational measures are required to ensure data integrity, confidentiality, and availability.

 

Relevant EU Legislation

BBMRI Resources

  • BBMRI-ERIC Guidelines and Quality Management Resources: Standardisation
  • MIABIS: MINIMUM INFORMATION ABOUT BIOBANK DATA SHARING

External Resources

 

Relevant Publications

  • Brancato, V., Esposito, G., Coppola, L. et al. Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine. J Transl Med 22, 136 (2024). https://doi.org/10.1186/s12967-024-04891-8
  • Bukreeva, A.S.; Malsagova, K.A.; Petrovskiy, D.V.; Butkova, T.V.; Nakhod, V.I.; Rudnev, V.R.; Izotov, A.A.; Kaysheva, A.L. Biobank Digitalization: From Data Acquisition to Efficient Use. Biology2024, 13, 957. https://doi.org/10.3390/biology13120957
  • Bonizzi G, Zattoni L, Fusco N. Biobanking in the digital pathology era. Oncol Res. 2022 Aug 31;29(4):229-233.  https://doi.org/10.32604/or.2022.024892
  • Tozzo, P.; Delicati, A.; Marcante, B.; Caenazzo, L. Digital Biobanking and Big Data as a New Research Tool: A Position Paper. Healthcare2023, 11, 1825. https://doi.org/10.3390/healthcare11131825

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