Unlocking New Frontiers – Accelerating Digital Health Integration with Research Infrastructures

Author: Dr. Zisis Kozlakidis
Head
Laboratory Support, Biobanking, and Services
International Agency For Research on Cancer/WHO

Biobanks have emerged as a primary infrastructure for biomedical research, drug development, and personalized medicine. These repositories of biological specimens, including blood, tissue, DNA, and linked data, have grown in number over the last two decades. They have enabled researchers to conduct large-scale studies, including genome-wide association studies (GWAS), and identify genetic predispositions of patients to diseases. However, to ensure that biobanks make the most of their resources and have a wider scientific impact, they must cultivate the ability to work together and collaborate not just with other biobanks but also with other research infrastructures.

What are these research infrastructures we are talking about?

Research infrastructures encompass a diverse range of resources that offer valuable provisions and support to research communities, enabling them to carry out studies and groundbreaking innovations within their respective domains. These encompass crucial technical resources such as biobanks, research institutions, advanced equipment, and software systems, as well as knowledge-centric facilities such as scientific data infrastructures and databases.

Over the last couple of decades, another development has been emerging – the use of large datasets and reference maps, as valuable resources for scientific and clinical research, drug development, and medical practice. The COVID-19 pandemic also encouraged countries to reassess and allocate resources toward their own healthcare infrastructure, in particular digitally enabled infrastructure. This has resulted in a push for the availability of scientific reference data sets, which, in turn, has led to the creation of specialized research infrastructures that gather data and offer services to various research communities. These research infrastructures are purpose-built to support pre-determined activities and comprise diverse technical components tailored to meet professional, regional, and societal requirements and regulations.

Some infrastructures have been established in the field of infectious diseases, such as the Global Action Plan on anti-microbial resistance (AMR) in 2015. These initiatives, including AMR surveillance programs, are designed to track disease trends, establish standard treatment guidelines, and facilitate the quick identification and control of disease outbreaks by sending alerts if any novel strains emerge that are resistant to treatment. But there’s a catch. These infrastructures do not house any biospecimens, nor can they establish connections with physical specimens stored in biobanks.

Thus, various methods have emerged that allow research infrastructures, including biobanks, to

1. Emerge as part of new infrastructures
   
2. Integrate with existing infrastructures
   
3. Become a distinct, separate, but interoperable part of the existing infrastructural landscape

Let us take a look at the above three recourses with the help of examples from across the globe.

1. Biobanks emerge as part of new infrastructures.

The use of outdated procedures for gathering and retrieving biological samples and associated metadata can diminish operational and financial efficiency, and in worst-case scenarios lead to errors. Thus, the development of improved and sustainable infrastructures to replace or enhance existing ones is often sought. An approach to establishing novel infrastructures involves amalgamating diverse technologies such as genomics, digital records, automation, and biobanking into a single framework. A prime example of this method is the successful implementation of a digital national surveillance program for COVID-19 in Indonesia, where cutting-edge technologies were introduced as part of a single surveillance infrastructure. The next step of the program entails expanding the infrastructure’s implementation to the surveillance of other infectious diseases, as well as connecting with Indonesian biobanks in a unified framework.

2. Biobanks integrate with existing infrastructures.

An alternate method of creating infrastructures is through consolidated biomedical and research laboratories that provide centralized resources and services. These infrastructures may also include biobanks, which provide high-quality samples to researchers. For instance, the Labor Berlin Services in Germany is a result of centralizing the two main healthcare networks in the state of Berlin. As the diagnostic laboratory for Europe’s largest university hospital, Charité, Labor Berlin has established a robust research and development platform by setting up a diagnostic clinical scientist program and linked biobank. Another example of the integration of biobanks with existing research infrastructure is from Estonia. The digital environment in Estonia includes the biobanking infrastructure, where the physical specimens are connected to health registries that are capable of exchanging information with each other. This allows researchers to access well-characterized specimens.

3. Biobanks become a distinct, separate, but interoperable part of the existing infrastructural landscape.

In certain situations, neither of the two aforementioned methods for infrastructure creation may be viable. This is especially true in cases where large-scale implementation is hindered by insufficient capital investment. Moreover, the creation of a unique infrastructure can prove to be challenging in countries with decentralized political structures and stringent regulations. Therefore, a more practical solution is the interoperability of existing infrastructures. This approach is especially useful in low-and-middle-income countries where resources are limited. Take for example the Ebola outbreak in Sierra Leone between 2014 & 2015 where residual clinical specimens and data were collected in the field and sent to PHE-led (Public Health England-led) laboratories for routine diagnostic testing. After the epidemic, some samples were kept in Sierra Leone while the rest, along with accompanying data, were transferred to PHE laboratories in the UK for curation. To facilitate future research opportunities, the Ministry of Health and Sanitation and Public Health England (MOHS-PHE) Ebola Biobank created a single governance group, comprising representatives from different stakeholders, to manage this interoperable infrastructure. The biobank enables identified, targeted, residual diagnostic samples of interest to be retained for future research.

Why is a Biorepository Management System crucial in a connected world of digital research infrastructures?

In this new era of digital research infrastructures, laboratory information management systems (LIMS) play a crucial role in the efficient management of biobanks. With the increasing amount of data generated from biobanks, it is essential to have a system that can store, retrieve, and analyze this data efficiently. A biobanking LIMS, also known as a biorepository management system, can help ensure compliance with regulatory requirements and support data sharing and collaboration across different research infrastructures, including biobanks and other digital infrastructures. This is particularly important as biobanks and other research infrastructures become more interconnected, and researchers seek to access and analyze data from multiple sources. Thus, whether it’s a single comprehensive national infrastructure or integration of biobanks into specific local healthcare systems, by providing a centralized system for managing laboratory and healthcare data, a biorepository management system can help improve the quality and reliability of research results, facilitate data sharing and reuse, and support collaborative research efforts.

Conclusion

Biobanks have become indispensable and foundational infrastructure crucial for medical research, drug development, and personalized medicine. However, to maximize their impact and scientific reach, biobanks need to foster their interoperability, both with other biobanks and with existing research infrastructures. The examples provided in this blog show how biobanks can emerge as part of new infrastructures, integrate within existing infrastructures, or become an independent, yet interoperable component of the existing infrastructural landscape. In addition, implementing a LIMS can further enhance the interoperability and efficiency of biobanks by allowing for better sample tracking, quality control, and data management and accessibility. By working together, biobanks can help accelerate scientific breakthroughs and improve healthcare outcomes for current and future generations.

Disclaimer

Where authors are identified as personnel of the International Agency for Research on Cancer/WHO, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer/WHO.