1. Introduction
The term biobank first appeared in 1996 and referred to collections of human specimens. Hewitt and Watson (2013, p. 309) define biobank as ‘biological collections of human, animal, plant or microbial samples; and that the term biobank should only be applied to sample collections with associated sample data, and to collections that are managed according to professional standards’. Global biobanking has expanded rapidly in last two decades driven by public infrastructure funding and basic research on biobank specimens, substantial increases in the incidence of fatal chronic diseases, and the rise of personalised medicine. The total value of the global biobanking market was estimated at $42,104.30 million in 2020 (Srivastava et al. 2021). Dynamic growth in the biobanking market was mirrored in the substantial proliferation of scientific literature on biobanks, with the terms ‘biobank’ and ‘tissue bank’ generating 11,038 and 1921 hits respectively in the Web of Science Core Collection database in 1996–2021. Yet some fields of biobanking research expanded more than other ones. This study, for example, found only some 165 studies (1.27%) on biobanks and tissue banks referred to the business and economics of biobanks. This is rather surprising given the substantial investment from public and private sectors provided to biobanks. Significant investments in infrastructure and running costs were not always accompanied by the implementation of elementary business practices, such as business plans, cost-recovery models and calculation of the biobank’s economic and social benefits. Funding for large infrastructure is cyclical with many biobanks facing the loss of funding or closure and promises and expectations sometimes turned to disappointment (Stephens and Dimond 2015). As noted by Vaught (2013, p. 259), economics is the neglected ‘Omics’ of biobanking.
This research reviews the scientific literature on the business and economics of biobanking to explore the key themes and paradigms, as well as their evolution over time. The paper is organised as follows: chapter two introduces the research methods and data sources. The chapter three presents the results of the structural analysis, identifying the key authors, journals, and studies in the field of biobank business and economics. Chapter four reviews the most important themes in the business and economics of biobanks and their evolution over time. The concluding part of the paper summarises the key findings, notes some important limitations, and suggests directions for further research.
2. Materials and Methods
The two-stage literature review was performed (Figure 1 and Figure 2). The initial body of literature was primarily identified based on searches of the Web of Science (WoS) combining the terms ‘tissue bank’ OR ‘biobank’ AND ‘business’, ‘plan’, ‘sustainability’, ‘cost’, ‘revenue’, ‘budget’, ‘finance’, marketing’, ‘advertising’, ‘bioeconomy’, ‘commodification’, ‘commercialisation’, ‘investment’, ‘fee’, ‘charges’, ‘price’, ‘customers’, ‘economy’, ‘finance’, ‘income’, ‘public-private’ and ‘private-public’. The initial search produced 2784 items. A search query may generate both relevant and irrelevant items. Some keywords (e.g., ‘plan’ and/or ‘management’) appear in multiple contexts, both economic and non-economic. Some 1990 studies were considered for further screening.
In stage two, we combined individual inspection of each abstract with analysis of the co-citation networks. Inspection of abstracts indicated that some economic terms, e.g., costs, appeared in the abstract but were only loosely related to the business of biobanks. Some studies also noted concerning storage costs for biobank specimens but did not focus on the biobank’s economics and business. We also excluded literature on the ethics of biobanking and studies on the cost-effectiveness of specific drugs or treatment methods that relied on biobank samples.
The findings from the abstract screening were compared to the results from the analysis of the co-citation networks (Figure 2). The CiteSpace 5.8.R3 software (Chen 2017) was used to map and visualise the scientific literature on biobanking. This software enables the direct import of citation networks from the WOS and identifying and analysing clusters of related publications. The software produced a network of clustered co-citations by 1,990 publications. The 21 largest clusters labelled by author keywords appeared in specific clusters. Individual clusters are drawn in different colours and the cluster labels are in bold red and start with #. The 21 largest clusters (#0–20) were labelled and the relevant and irrelevant topics appeared well-separated in isolated clusters. The largest relevant cluster (#3 business planning, drawn in yellow), for example, partially overlapped with clusters #1 (big data) and #7 (stakeholder view) and the most frequent keywords in these clusters included ‘business planning’, ‘biobank sustainability’ ‘research biobank’, ‘maintaining sustainability’, ’public-private partnership’, ‘academic biobank’ ‘applying business processes’, and ‘public-private relationship’. Some clusters were only marginally related to business and economics of biobanks (e.g., clusters on blood transfusion service or proteomic research). We used the silhouette statistics (Rousseeuw 1987, p. 53) to measure homogeneity of specific clusters and to identify self-standing clusters (e.g., #12, 19, 20) unrelated to the economics and business of biobanking. After comparing the studies established by the network analysis with the individual abstracts, we identified some 155 studies relevant to the business and economics of biobanks, winnowing these out from the original body of 1990 papers. Finally, we screened the reference lists and identified ten additional studies, so that the final sample contained 165 studies.
Phase three of the literature review identified the major themes in the business and economics of biobanks, combining conceptual evaluation and analysis of the co-citation network for the 165 studies. The reference co-citation network (Figure 3) contained 49 clusters. The largest cluster (#0 business model, 61 members), for example, contained keywords on ‘business planning’, ‘sustainability’, ‘business model’, ‘recovery’, and ‘biobank sustainability’. Finally, the comparison of the results of the abstract screening and co-citation networks revealed seven themes relevant to the business and economics of biobanking.
3. Results: Structural Analysis
The structural properties of the literature on the business and economics of biobanks were analysed as follows.
3.1. Authors, Papers and Journals
Business and economics are niche subjects in biobanking research, with studies concentrated in a small number of journals by a few authors (Table 1). More than one-third of the studies were published in the Biopreservation and Biobanking journal, with other journals including Cell and Tissue Banking, New Genetics and Society, and European Journal of Human Genetics. Daniel Simeon-Dubach was the most prolific author within the sample of 165 papers, followed by Marianne K. Henderson and P. Watson (all associated with the editorial board of Biopreservation and Biobanking). Papers by Henderson et al. (2013a), De Souza and Greenspan (2013), and Harris et al. (2012) generated the most citations in the WoS.
3.2. Countries, Institutions and International Collaboration
Most studies were published by authors from developed Anglo-Saxon countries (the UK, USA, and Canada) and the US and Canadian institutions (the US National Institutes of Health, the US National Cancer Institute, and the University of British Columbia). International collaborative research was rather underrepresented compared to nationally circumscribed research in the sample of 165 studies, with only 49 studies (29.7%) involving at least one international co-author. Case studies of specific biobanks were the most common types of articles explaining why many studies included no international co-authorship.
Some 31 countries (out of a total of 40) produced at least one international co-authorship, but strikingly, some large countries produced few or no international co-authorships. For example, China produced only two international co-authorships, and there were no international co-authorships for India, Russia, Mexico, and Korea. This is rather surprising, as international collaborative research generates many benefits. Insights provided by researchers from diverse countries help to combine different research perspectives and solve complex problems in contemporary science.
The network of co-publications consists of nodes (circles) representing countries (denoted by their country codes) and edges (curved lines) representing the number of co-authorships (Figure 4). The higher the number of total international co-authors the larger the circle, and a distinctive loop-like curve depicted if two or more co-authors came from the same country. The thickest loop-like edge on the diagram, for example, represented 51 papers co-authored by at least two US-based authors. Regarding the international co-authorships, the thickest line runs between Switzerland (CH) and Canada (USA) and denotes 13 Swiss-US co-authorships, whereas the medium-thick line between the UK and the US represents 12 UK-US co-authorships. The network comprises several clusters (modules), with members of a specific module accounting for denser mutual connections than connections with members of other modules. Specific modules are depicted in different colours, with the largest (red) module comprising the global-leading countries in biobanking research (the USA, UK, Switzerland, Canada, and Germany) plus several other countries that produced the most mutual international co-authorships within the sample of 165 studies. The second-largest (green) module consisted of 11 European countries, which were more likely to seek co-authors from their continent than from other parts of the world. The module membership was probably informed by participation in European research schemes (such as Framework and Horizon programmes). Finally, the small (blue) module involved four European countries.
To detect some potential changes in research paradigms, the occurrence of the top seven themes in abstracts from 165 studies were checked between two time periods: 1997–2014 and 2015–20211 (Table 2). There was considerable increase in the average annual occurrence of the sustainability, utilisation, and business plan topics compared to the funding, costs, economic, and commercialisation topics. This is closely related to the implementation of business plans, improved utilisation of specimens, and sustainability issues.
4. Results: Thematic Review
The seven major themes in the business and economics of biobanks, as established by the literature review, were reviewed.
4.1. Business Plan
Large businesses offering a service to customers use to draft a business plan, a concise document on the organisation’s vision and mission, and management and marketing. Some businesses also prepare separate documents for sales and competition analysis. As for the biobanks, Henderson et al. (2017, p. 1) argue for a ‘robust marketing plan to advertise the facilities and services, within and outside the organisation’.
There is some evidence that business planning is underdeveloped in the biobanking sector, as few biobanks drafted a robust business plan to support their operational costs. Simeon-Dubach et al. (2017, p. 72) surveyed 32 biobanks in the 2016 Annual meeting of the International Society for Biological and Environmental Repositories (ISBER), reporting that only 17 biobanks had a business plan, ten had a business plan in progress, and five reported no business plan.
Ciaburri et al. (2017) acknowledged that many biobanks are managed by health researchers or clinicians who may not be familiar with the business, financial, and economic affairs. Ciaburri et al. (2017, p. 47) suggested adopting a typical business plan for biobanks including some standard components, such as mission statement, market analysis, marketing strategy, organisational structure, and economic and financial provisions. There are, of course, substantial differences in size, scope, research orientation, and number of customers among individual biobanks. These differences are mirrored in the diversity of business plans. Large biobanks with many customers resemble small- and medium-sized enterprises (SMEs), so managers of large biobanks may learn from standard business practices (Simeon-Dubach et al. 2017, p. 72). The diversity of biobanks suggests that individual biobanks should apply different marketing and advertising strategies. For profit biobanks, for example, may benefit from a comprehensive marketing strategy that describes the products and services, website sales, research services, consultancy, training, and hiring a business manager (Brown et al. 2017 p. 70).
Plans for establishing and managing biobank infrastructures should include a strategy for risk management and risk mitigation (Henderson et al. 2013b). Crises may come from various sources, such as changes in public opinions about biobanks and the regulatory framework, natural disasters, technology failures, customer complaints, and problems with sustainability of funding (Parry-Jones et al. 2017, p. 256). Crisis management seems rather underdeveloped in biobanking. Church and Richmond (2019) performed a survey on a sample of experienced US practitioners in biobanking, showing that about one-quarter of surveyed biobanks had no continuity plan and 61% indicated concern in having a mandated continuity plan. Forward-thinking and business planning by biobanks is rare, even in the USA renowned for its business culture. The 2012 national survey of 456 US biobanks indicated that only 34% had a formal business plan and 26% elaborated plans for what to do with specimens if the biobank closed (Cadigan et al. 2017, p. 153). The US Biobanking Financial Sustainability survey produced similar results, showing that most biobanks had no formal plans for the long-term stewardship of their collections (Rao et al. 2019). The storage of biospecimens and their use for research purposes is the key function of a biobank. If the specimen utilisation rate is low, the biobank does not serve its basic purpose, and as a result, it becomes financially and socially unsustainable.
There are a number of potential explanations for missing business plans. Most biobanks operate on the non-profit basis. These bodies may consider business plans non-essential for their operations. If the non-business people run biobanks, they may underestimate the importance of business plans. For the non-profit bodies there is no market sanction for failure. Non-profit biobanks are financed from taxpayer money. Some public biobanks may act under the impression that if they ever fall on hard times, the taxpayer is going to be there to bail them out. This leads to a moral hazard situation. The lack of realistic business and marketing plans may contribute to the failure and closure of a public biobank.
4.2. Funding
The literature on biobank funding explored the sources and structure of funds, funding adequacy, and the evolution of funding sources over time.
A variety of biobank models is reflected in the diversity of funding sources. A typical biobank was embedded with a larger (often parent) organisation, such as an academic or research institution, hospital or government department. The vast majority of biobanks operated on a non-profit basis and the parent organisation was a key source of biobank funding. In Europe, most biobanks were research infrastructures established by the public sector, while in the USA and Canada, some biobanks operated on a for-profit basis and derived their incomes from commercial activities. For-profits operating models were rather scarce and accounted for only 5% of the total in the USA by 2013 (Henderson et al. 2013a, p. 7).
Gee et al. (2015, p. 439) provided the typology of the biobank revenue sources. Typical sources included infrastructure grants, project funding, endowments and philanthropic support (Bromley 2014; Wilson et al. 2014), membership and for-service fees, as well as income from intellectual property rights. Additional income sources were obtained via specific contract services, such as clinical studies (Kozlakidis et al. 2012, p. 358). The user fees varied by user group, e.g., academic vs. industry, local vs. international (McDonald et al. 2012; Barnes et al. 2014). Doucet et al. (2017, p. 3) presented a detailed review of the biobanks’ funding in 23 French and 22 Dutch biobanks, showing that the major sources of finance were direct public funds (32%), funding by the host institutions (27%) and indirect funding by research grants (25%).
In some biobanks, the funding structure evolved over time. While infrastructure and project grants by a single donor were the major sources of funding in the initial stages of a biobank’s lifecycle, mixed funding resources were key for the biobank’s survival in the latter stage of development.
4.3. Costs and Cost Recovery
The literature on biobanking costs explored several important themes: (i) cost types, (ii) cost modelling and accounting, and (iii) cost-recovery models.
Costs of biospecimen acquisition, procuring, processing storage, and preserving represent a substantial proportion of the total expenses by a biobank (Leboeuf et al. 2008; Petrini 2014; Andry et al. 2017). A specific type of costs related to the permission to contact and obtaining informed consent from donors (Naveen et al. 2020). Other types of costs resulted from regulatory requirements (Koller 2007; De Souza 2015) and implementation of standardisation and certification procedures, which increased the opportunities to participate in prestigious research programmes and collaborations, but at the same time, they also imposed additional operational costs. Ling et al. (2018), for example, estimated the relative costs of gaining certification between 2% and 6% of current total annual wage costs in three Australian cancer banks.
The extraordinary rate of growth in biospecimen volumes implied the need for strategic planning and cost analysis (Abdaljaleel et al. 2019). Huttin and Liebman (2013, pp. 186–188) considered several cost models for biobanks, such as the cost-recovery model, the total lifecycle of ownership model (TLCO), and the cost model of biobanks for an adaptive knowledge platform. Gonzalez-Sanchez et al. (2013, p. 273) recommended that the cost model should reflect the stages of the production process, including collection in the laboratory, biospecimen processing, storage, order processing, sample processing, and sample distribution. Gonzalez-Sanchez et al. (2014) also presented mathematical models quantifying (i) the total production cost for a specific product and (ii) request costs. Several practical calculators for accounting expenses of biobanks have been developed and presented in the biobanking literature. Odeh et al. (2015) presented the Biobank Economic Modelling Tool (BEMT), an online financial planning tool. Matzke et al. (2014) drafted the Biobank Costing Modelling Tool, a calculator for expenses, services, and salary and equipment costs. Similar tools were developed elsewhere. Clément et al. (2014) designed cost-recovery models for public-public and public-private collaborative partnerships.
The diversity of ownership, orientation, and operations make it difficult to develop a single cost model for all biobanks. Some biobanks used a fee-for-service model for recovering their costs. But the full cost recovery is hardly possible for public biobanks. Only one per cent of the total budget was provided by the cost recovery in a sample of 45 French and Dutch biobanks (Doucet et al. 2017, p. 3). In Canada, the user fees covered some six per cent of the overall operational budget (Barnes et al. 2014). Albert et al. (2014) deemed full cost recovery through the distribution of fees infeasible. The cost recovery from distribution fees was in the range of 5–25%, with the lower range more realistic for academic research only.
Gee et al. (2015) suggested that diverse resources should be used to cover specific cost types. The sample acquisition costs should be an integral part of the research proposals to ensure that specimen acquisition is driven by research needs. The central public funds should pay for direct investment and running costs of public biobanks, with a fee-for-service model applying to specimen users.
4.4. Utilisation of Specimens
Storing, handling, and sharing specimens is the biobank’s core business. If specimens are left unused, the biobank fails to fulfil its mission. Many studies acknowledged that large numbers of underutilised specimens were a major problem for the financial sustainability of biobanks (Campos et al. 2015; Lin et al. 2019). A global survey of 276 biobanks (Henderson et al. 2019b, p. 217) indicated that in over half of the institutions, the utilisation rate was 10% or lower, and the actual annual utilisation rates of samples were by 2.5 to 5 times lower than the target. Henderson et al. (2019b, p. 217) argued that underutilisation ‘breaks the trust between the scientists/biobanks and the donors’ and is a threat to the social sustainability of biobanks.
If stocks of samples are growing faster than utilisation rates, the sustainability of a biobank is under question. Amassing substantial stocks of specimens without concern for demand undermines the long-term sustainability of both commercial and non-profit biobanks. This probably is the worst scenario. Why, then, are there still so many biobanks, and why does the public continue financing the current economic models?
There are specific reasons for the underutilisation of biospecimens. Sometimes there was a problem associated with restrictive policies limiting access to specimens (Bledsoe and Sexton 2019, p. 248). The specimens may have been collected with no clear vision of their use or their numbers, and quality may have not suited specific research needs. Alternatively, high stocks of specimens may simply reflect classical behavioural biases, such as endowment effect, status quo bias, and/or sunk-cost fallacy (Kahneman et al. 1982).
Several strategies were suggested to increase the utilisation of specimens (Bledsoe and Grizzle 2019). In the initial stage of the biobank, resource sharing may improve access to biospecimens and increase the utilisation rates (Uzarski et al. 2015; Macheiner et al. 2017). A strategy for optimal utilisation should begin with sharing of resources, infrastructure, and investments in the planning stage of a biobank. A good quality business plan, engagement with stakeholders, targeted marketing, and advertising may improve publicity, attract new customers, thereby increasing utilisation rates (Henderson et al. 2019a, p. 74). With increased numbers of repositories and volumes of specimens stored, the biobanks should be more selective as to what is stored (Yong et al. 2014). This may assist the transition from a biobanking model based on mostly retrospective samples of pre-defined specimens to a more prospective, investigator-driven collection (Quinn et al. 2021, p. 7). Improved requirements for registration of collections and stock targets for biobanks may reduce expenditure on duplicate collections (Watson 2017). Finally, culling stocks of unused specimens is another option for improving sustainability of biobanks.
4.5. Economic and Societal Effects of Impacts
Findings on biobank costs and utilisation of specimens raise some critical questions. If the revenues from operations and sales are very low, should one consider biobanks businesses or rather public goods? If non-profit biobanks are public goods, do they deliver a real value? Do biobanks’ cost (including initial investment to the biobank’s infrastructure) equate to value? If yes, how should the value be computed?
The sustainability of biobanking may be enhanced by an improved understanding of the biobanks’ wider benefits for the economy and society. Economic criteria and analytical tools for monitoring and evaluating their activities (Fernandez et al. 2020), as well as quality metrics for biobank inputs, outputs, and impacts, are necessary for assessing biobanks’ performance. The metrics should distinguish between outcomes and (wider) impacts, with the former capturing progress towards specific objectives, such as utilisation rate or increases in funding, while the later metrics assess achieving some ultimate goals in the biobanks’ mission, such as advancement in knowledge or improvement in diagnosis and treatment. A substantial majority of biobanks operate within their parent academic/health institutions, so their economic effects refer to the activities of their parents, donors, or clients. Direct financial outputs, for example, can be measured via cost-recovery and revenue derived from fee-for-services. Such revenue, however, constitutes a minor part of the overall economic impact. The indirect impact relates to research outputs coming from the biobank infrastructure, such as the value of patents, numbers of spin-offs and research employment (Simeon-Dubach and Watson 2014, p. 304; Campos et al. 2015, p. 388; Tarling et al. 2017, p. 41).
The wider economic and social benefits may include potential reduction in the duration and cost of clinical trials, more accurate patient diagnoses, and improved quality of a patient’s life (Vaught et al. 2011, p. 30; Rogers et al. 2011, p. 34). Finally, some wider economic benefits of the biobank may fully materialise in the time of a crisis. For instance, the biobanks played an important role in basic discovery, and in the development of assays, and therapeutic drugs during the COVID-19 pandemic (Simeon-Dubach and Henderson 2020, p. 507). The crisis highlighted the importance of sharing data and samples and maximising the knowledge gained from the biobanks’ resources
4.6. Commercialisation
The commercialisation of public goods generates much controversy, with the debate revolving around ethical, legal, and economic issues.
There are several issues related to the commercialisation of biobanks, with some authors expressing sceptical views about the commodification of tissues. Fannin (2013, p. 32) considered speculative practices in commercial stem cell banking and specifically gendered forms of capitalist ‘tissue economies’. Commercialisation may transform bodily materials into research tools and marketable products. Maseme (2021, p. 674) discussed the arguments for and against the commodification of the body and its parts. The arguments for commodification included the right to sell or donate one’s organs and/or tissues for any reason, including financial motives, while the arguments against referred to the interference of commodification with human dignity and a potential dilution of altruism, which is undermined by commodification.
The long-term storage of biospecimens and related personal health data poses specific challenges and is fraught with economic, ethical, and legal uncertainties (McHale 2011, p. 232; Rial-Sebbag and Cambon-Thomsen 2012). Information asymmetries between tissue donors and beneficiaries may arise. The broader population has expressed mixed feelings about research on biospecimens. Evidence from a nationally representative US survey suggested that most people are not comfortable with the commercialisation of biospecimens, believing that profits from commercialisation should be used only to support future research (Spector-Bagdady et al. 2018, p. 1313). Thus, the careful management of public/private interests is needed to generate ‘biovalue’ that has both commercial as well as scientific and public health values (Esteve et al. 2012).
The material stored in biobanks and big data allow for utilising currently uncovered information and knowledge (Kinkorova and Topolcan 2018). However, the emerging ‘health data economy’ raises several concerns about the public sector being the key producer and provider, while the commercial sector is the key user of the biobank data (Tupasela et al. 2020).
Several papers discussed the potential conflict between the common good and private interests. The entrance of a private investor or funder may increase financial resources but also impact public trust in a biobank, as donors and the public may feel less secure about their privacy and object to a private investor profiting from using their specimens. Other concerns were raised about access to knowledge and research results. For example, a private partner may ask for restrictions to the free sharing of specimens. Huzair and Papaioannou (2012, p. 500) argued that restricted access to knowledge is ‘subject to the tragedies of commons and anti-commons’. The human costs of restrictions could be considerable (Evers et al. 2012, p. 46), and there is also uncertainty about the control of biobank’s resources in the case of closure or bankruptcy (Stephens and Dimond 2015).
Some authors argue that it is inappropriate to use vague quasi-economic concepts, such as ‘biovalue’ or ‘capital’ in biobanking. The value generated by biobanking is realised ‘by the application of knowledge (constituted in intellectual property) derived from biobanking science’ (Turner et al. 2013, p. 76). Once the focus shifts from tissues and data to knowledge derived from biobanks, commercialisation may align with public health interests rather than erode trust. The concepts of ‘common good’ and ‘private interests’ are not mutually exclusive. The private sector, of course, wants and can extract commercial benefits from donated samples, but commercial research also can generate innovative testing and therapeutic benefits for donors. Public-private partnerships (PPPs), if managed properly, help advance scientific discoveries and medical innovations (Lawlor and Scarpa 2017, p. 12; Hämäläinen et al. 2019). Some authors maintain that hurdles in establishing the PPPs are not related to the fear of commodification and private interests, but rather to limited business expertise and the absence of experience in drafting contracts with private partners (Hofman et al. 2014). The PPPs have the potential to improve business and management practices in public research infrastructures. Public biobanks also have an opportunity to learn how to implement industry-wide standard operating practices, cut their operating costs, and improve the handling of specimens (Somiari and Somiari 2015 p. 25).
The discussion on commercialisation helped to redefine the concept of ‘donor’. Goisauf et al. (2019) performed a survey of 273 experts and researchers in biobanking from 32 countries, reporting that people donating their tissues are no more viewed as simple ‘donors’; rather, they are considered ‘participants, ‘partners’, or even ‘stakeholders’ as a recognition of their active involvement in the biobank’s activities including research. Some biobanks already developed activities oriented to the engagement of participants, such as campaigns channelled via social media and interactive events (Platt et al. 2013). It is understood that biobanks should consider more proactive practices in communicating with participants, as well as engaging with the private sector to advance research and personalised medicine. The partnerships, of course, must comply with all applicable laws and regulations and operate on mutual trust and transparency (Graeber 2008, p. 493). The benefit-sharing should be based on ‘equitable benefitting and ownership issues arising from biomaterials and associated data’ (Maseme 2021, p. 669). Hybrid models of biobanking (Neresini 2011; French et al. 2018) include both public-private and private-public collaborations. The former model refers to the case when a public biobank provides its resources to all bona fide scientists, research institutions, and industry (Trehearne 2016), whereas in the latter model, the private biobanks provide services that usually are performed by public biobanks. Hybrid banking models may assuage at least some concerns about the commercialisation of human tissues (Andrews 2005; Martin et al. 2008).
4.7. Sustainability
Sustainability has been a recurrent theme in the literature on biobanking and was the most common keyword in the literature search. The challenge of sustainability stems from a biobank’s mission and funding mode, as most biobanks are funded by public sectors and/or donations. The biobanks maintain open access to specimens, but service fees seldom reimburse costs. As noted by Henderson et al. (2015, p. 385) many biobanks were established via ‘‘one-shot’’ institutional funding. Moreover, funding is generally often irregular, uncertain, and only cover the costs for a certain period (Carpenter et al. 2014; Parry-Jones 2014; Yuille et al. 2017). Globally, biobanks are struggling with sustainability, with many having folded (Quinn et al. 2021, p. 6). Some biobank networks ceased to exist, due to funding withdrawal or a shift in operational focus (Devereux 2019, p. 512).
Previous chapters discussed some basic managerial solutions for sustainable biobanking, such as (i) setting and applying the quality business plan; (ii) introducing cost-effective procedures for sample acquisition, storage, and handling; (iii) introducing fee-for-service business models; (iv) increasing the number of samples distributed; and (v) culling the stock of unused samples. Stock culling has been discussed little in the biobanking literature so far—there is a certain gap in the literature on sustainable biobanking.
Individual authors offer specific conceptual perspectives on sustainable biobanking. One stream of the literature concentrated on the interaction of a biobank with its environment. Alternative sustainability strategies included (i) integration of biobanks into the host medical institutions, (ii) sample sharing (Doucet et al. 2017), (iii) involvement in consortia and networks to increase the long-term use and exchange of samples (Kirsten and Hummel 2016), (iv) access to international and global funding mechanisms (di Donato and Aure 2017), and/or (v) engagement with multiple types of stakeholders, such as patient associations and donors, hospitals and clinicians, biobank networks, researchers, public administration, charities, and the private sector (Cañada et al. 2015).
The other stream of sustainability literature concentrated on the evolution in biobanks’ mission and business profiles (Simeon-Dubach and Henderson 2014). Biobanking 1.0 focused on the numbers, while Biobanking 2.0 on the quality of biospecimens and data, with Biobanking 3.0 regarding the sustainability driven by orientation on existing or new customers. A biobank is only sustainable if it has an added value for the customers. Meijer et al. (2012) argued that with the increasing numbers of biobanks and improved networking, the biobanks should specialise and professionalise their technical expertise, thereby increasing their competitive advantage and improving the chances of sustainable funding.
Simeon-Dubach and Watson (2014, p. 307) and Watson et al. (2014, p. 62) considered three dimensions of biobank sustainability: social sustainability (acceptability by the broader public), operational sustainability (cost-efficiency), and financial sustainability (accomplishment). The diversity of biobanks also implies a diversity of sustainability dimensions and strategies. Seiler et al. (2015, p. 405) referred to Watson et al.’s (2014) three-dimensional concept of sustainability (operational, social, and financial). Biobanks with many external customers and relatively low operational costs may apply more realistic cost-recovery models than biobanks with high operational costs and few customers. Small or non-profit biobanks with limited numbers of customers may not achieve sustainability based on cost-recovery, rather accentuating operational and social targets in their business plan. The availability of specific samples may help obtain institutional grant funding for their parent body and offset some operational losses of a biobank (Seiler et al. 2015, p. 407).
5. Conclusions, Discussion and Directions for Further Research
Research on business and economics constitutes a minor proportion of a vast body of literature on biobanks. This finding is at odds with the substantial public investment in and concerns about biobank sustainability. Most studies reviewed in this paper were case studies of individual biobanks. There was little literature on competition, cost structure, and opportunities for differentiation and threat of substitute products. Furthermore, the research on business and economics is concentrated in a relatively small number of journals, institutions and countries, and would, no doubt, benefit from more intensive international collaboration and involvement of some large world countries.
We noted the same shifts in focus on specific themes, with the discussion about commercialisation seeming less intense than in the 2000s. The commercialisation of research results is accepted under the condition of equitable sharing of benefits across various stakeholders.
Most biobanks are heavily subsidised by public sector and are considered public goods rather than business entities. This is fine, but underutilisation of specimens and low rates of cost recovery suggest that current mainstream operating model is hardly sustainable. With many biobanks maturing, long-term sustainability became a key topic of the discussion of biobanking trends. Sustainability is conditional upon improvements in business planning, cost-effectiveness and cost recovery, and the utilisation of specimens.
Our research has some notable limitations. Unsurprisingly, most studies originated in advanced Western economies and were published in English. Yet there are hundreds of biobanks operating in non-Western countries, and details on their operations remain unknown to the authors. Consequently, our results are partial and fragmentary.
The limitations suggest directions for further research. Biobanks operate within specific economic, legal, and cultural institutional settings, which are likely to impact their missions and visions, business plans, financial planning, engagement with stakeholders, and marketing/advertising activities. Comparative research about the impacts of institutional settings on biobanks operations has been limited so far. Indeed, relatively little is known about the approaches to marketing and advertising in different cultures.
Most biobanks are costly research infrastructures paid for by taxpayers, so the sustainable financing of biobanks is inevitably tied to the acceptability of the biobank activities by the broader public. Further research should concentrate more on the costs and benefits of biobanks. Few studies demonstrated the economic benefits of biobanks so far. Some biobanks already use metrics for their inputs, throughputs, outputs, and results, but no study to date demonstrated the wider impacts of biobanks on the economy and society. Rogers et al. (2011, p. 34) suggested several impact indicators, such as improved patient diagnosis and therapeutic care. Biobanks support the pre-analytical sample processing and storage. The pre-analytics, in turn, improve accuracy of laboratory analytical results, while better analytical results ultimately can lead to improved diagnosis or treatment. But it still remains quite a challenge to attribute the improvements in diagnosis and treatment to specific biobanks. Neither traditional quasi-experimental designs (difference-in-differences, Aussems et al. 2011) nor novel approaches to evaluation of public interventions (such as the synthetic control method, Abadie et al. 2015) were tried to disclose wider economic benefits of biobanks.
Conceptualization, V.B.; methodology, V.B.; software, V.B. and T.J.; validation, V.B.; formal analysis, V.B.; investigation, V.B.; resources, V.B. and T.J.; data curation, V.B. and T.J.; writing—original draft preparation, V.B.; writing—review and editing, V.B.; visualization, V.B.; supervision, project administration and funding acquisition, M.B. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Not applicable.
The authors claim no financial interest or benefit that has arisen from direct applications of the research.
Footnotes
1. Total sample of 164 papers roughly fell in two periods. Some 72 papers (43.6%) were published in 1997–2014, while 93 (56.4%) in period 2015–2021.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Enlarge this image.Figure 2. Overview of the co-citation network for 1990 studies: clusters labels by keywords. Source: authors’ visualisation in the CiteSpace software (Chen 2017).
Enlarge this image.Figure 3. Network overview of 165 articles on biobank business and economics. Cluster labels by keywords. Source: authors’ visualisation in the CiteSpace software (Chen 2017).
Top journals, authors, papers, institutions and countries.
| Top Journals | Number of Articles |
| Biopreservation and Biobanking | 56 |
| Cell and Tissue Banking, New Genetics and Society | 5 |
| European Journal of Human Genetics | 4 |
| Bundesgesundheitsblatt—Gesundheitsforschung—Gesundheitsschutz; Journal of Translational Medicine | 3 |
| Authors | Number of Articles |
| Simeon-Dubach, D. | 14 |
| Henderson, M.K. | 10 |
| Watson, P.H. | 8 |
| Goldring, K., Kaye, J., Schacter, B.A., Tupasela, A., Vaught, J., Watson, P.H., Zatloukal, K. | 5 |
| Yuille, M | 4 |
| Most Cited Papers | Citation in WOS |
| 138 | |
| 123 | |
| 98 | |
| 98 | |
| 75 | |
| Top Institutions | Number of Articles |
| National Institutes of Health (NIH USA) | 16 |
| National Cancer Institute (NHI—NCI) | 16 |
| University of British Columbia | 15 |
| British Columbia Cancer Agency | 9 |
| Medical University of Graz | 8 |
| Top Countries by Author | Number of Articles |
| USA | 51 |
| United Kingdom | 39 |
| Canada | 23 |
| Switzerland | 18 |
| France | 15 |
Source: The Web of Science. Journals do not include book series. Notes: institutions and countries are listed by the author’s first affiliation. Publications and citation as of December 2021.
The occurrence of the top seven topics in the abstracts.
| 1997–2014 | 2015–2021 | Per Annum Growth Rate: |
|||
|---|---|---|---|---|---|
| Total | Per Annum | Total | Per Annum | ||
| business plan | 11 | 0.61 | 23 | 1.28 | 2.09 |
| funding | 19 | 1.06 | 24 | 1.33 | 1.26 |
| costs | 29 | 1.61 | 39 | 2.17 | 1.34 |
| utilisation | 5 | 0.28 | 15 | 0.83 | 3.00 |
| economic | 15 | 0.83 | 20 | 1.11 | 1.33 |
| commercialisation | 20 | 1.11 | 15 | 0.83 | 0.75 |
| sustainability | 24 | 1.33 | 51 | 2.83 | 2.13 |
Source: The Web of Science. Notes: introduction/background section was used for documents with no formal abstract.
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; Jeck, Tomáš 2
; Balog, Miroslav 1 1 Institute for Forecasting, Centre of Social and Psychological Sciences, Slovak Academy of Sciences, Šancová 56, 813 64 Bratislava, Slovakia;
2 Institute of Economic Research, Slovak Academy of Sciences, Šancová 56, 813 64 Bratislava, Slovakia