Biobanks and Their Clinical Application and Informatics Challenges

Abstract

Biobanks are one of the most important biomedical research resources and contribute to the development of biomarker detection, molecular diagnosis, translational medicine, and multidisciplinary disease research, as well as studies of interactions between genetic and environmental or lifestyle factors. Aiming for the wide clinical application of biobanks, biobanking efforts have recently switched from a focus on accumulating samples to both formalizing and sustaining collections in light of the rapid progress in the fields of personalized medicine and bioinformatics analysis. With the emergence of novel molecular diagnostic technologies, although the bioinformatics platform of biobanks ensures reliable bioinformatics analysis of patient samples, there are a series of challenges facing biobanks in terms of the overall harmonization of policies, integrated processes, and local informatics solutions across the network. Further, there is a controversy regarding the increased role of ethical boards, governance, and accreditation bodies in ensuring that collected samples have sufficient informatics capabilities to be used in biobanks. In this volume, we present a selection of current issues on the inevitable challenges of the clinical application of biobanks in informatics.

Metabolomics technology and bioinformatics for precision medicine

“…They have shown that storage temperature affected metabolite concentrations only little, while the number of temperature change cycles has a strong effect on metabolites stability [110]. Biobanking is considered as a critical component of precision medicine workflow and is being incorporated into several PMIs [112][113][114]. For example, MOBIT project adopted the oncology biobanking procedures developed by a commercial biotech company Indivumed GmbH (Hamburg, Germany) [22].…”

Quality Considerations When Using Tissue Samples for Biomarker Studies in Cancer Research

“…This typically includes pathological data collected and reported according to published national guidelines, treatment type (eg, hormone, chemotherapy, radiotherapy or biological therapy), duration of and response to therapy, dates of local, regional and distant recurrence, as well as the date and cause of death plus other comorbidities. However, the challenges surrounding data linkage from electronic health records and informatics for biobanks are well recognised, 43,44 particularly as academic institutes, healthcare systems and biobank networks are frequently separate entities, which may use different informatics platforms which cannot be linked easily. While steps are now being taken by various biobanks to make this process more streamlined, [45][46][47] manual intervention is often still required making this an inefficient and time consuming process.…”

Qatar Biobank: A Paradigm of Translating Biobank Science into Evidence-Based Health Care Interventions

“…Longitudinal prospective cohort studies are conceptually suitable for the discovery of novel biomarkers through collec-tion of adequate data and biological samples before (preclinical), during (clinical), and after disease development. 2,3 The identification of novel biomarkers that can predict treatment response at the patient individual level requires the standardized collection, processing, and storage of biological samples. Biobanking and the new field of biospecimen science have significantly contributed to generating reproducible results in biomedical research.…”