A review of international biobanks and networks: success factors and key benchmarks

Biopreserv Biobank. 2009 Sep;7(3):143-50. doi: 10.1089/bio.2010.0003. Epub 2010 Mar 17.

Abstract

Biobanks and biobanking networks are involved in varying degrees in the collection, processing, storage, and dissemination of biological specimens. This review outlines the approaches that 16 of the largest biobanks and biobanking networks in Europe, North America, Australia, and Asia have taken to collecting and distributing human research specimens and managing scientific initiatives while covering operating costs. Many are small operations that exist as either a single or a few freezers in a research laboratory, hospital clinical laboratory, or pathology suite. Larger academic and commercial biobanks operate to support large clinical and epidemiological studies. Operational and business models depend on the medical and research missions of their institutions and home countries. Some national biobanks operate with a centralized physical biobank that accepts samples from multiple locations. Others operate under a "federated" model where each institution maintains its own collections but agrees to list them on a central shared database. Some collections are "project-driven" meaning that specimens are collected and distributed to answer specific research questions. "General" collections are those that exist to establish a reference collection, that is, not to meet particular research goals but to be available to respond to multiple requests for an assortment of research uses. These individual and networked biobanking systems operate under a variety of business models, usually incorporating some form of partial cost recovery, while requiring at least partial public or government funding. Each has a well-defined biospecimen-access policy in place that specifies requirements that must be met-such as ethical clearance and the expertise to perform the proposed experiments-to obtain samples for research. The success of all of these biobanking models depends on a variety of factors including well-defined goals, a solid business plan, and specimen collections that are developed according to strict quality and operational controls.