Biobanking in health care: evolution and future directions

The aim of the present review is to discuss how the promising field of biobanking can support health care research strategies. As the concept has evolved over time, biobanks have grown from simple biological sample repositories to complex and dynamic units belonging to large infrastructure networks, such as the Pan-European Biobanking and Biomolecular Resources Research Infrastructure (BBMRI). Biobanks were established to support scientific knowledge. Different professional figures with varied expertise collaborate to obtain and collect biological and clinical data from human subjects. At same time biobanks preserve the human and legal rights of each person that offers biomaterial for research.

A literature review was conducted in April 2019 from the online database PubMed, accessed through the Bibliosan platform. Four primary topics related to biobanking will be discussed: (i) evolution, (ii) bioethical issues, (iii) organization, and (iv) imaging.

Most biobanks were founded as local units to support specific research projects, so they evolved in a decentralized manner. The consequence is an urgent needing for procedure harmonization regarding sample collection, processing, and storage. Considering the involvement of biomaterials obtained from human beings, different ethical issues such as the informed consent model, sample ownership, veto rights, and biobank sustainability are debated. In the face of these methodological and ethical challenges, international organizations such as BBMRI play a key role in supporting biobanking activities. Finally, a unique development is the creation of imaging biobanks that support the translation of imaging biomarkers (identified using a radiomic approach) into clinical practice by ensuring standardization of data acquisition and analysis, accredited technical validation, and transparent sharing of biological and clinical data.

Modern biobanks permit large-scale analysis for individuation of specific diseases biomarkers starting from biological or digital material (i.e., bioimages) with well-annotated clinical and biological data. These features are essential for improving personalized medical approaches, where effective biomarker identification is a critical step for disease diagnosis and prognosis.