Why IoT and LIMS are critical to the future of biobanks

This decade is the age of the biobank, says Lauren Taylor, a scientist and solutions manager in Digital Sciences at Thermo Fisher Scientific. She shares her thoughts on the importance of IoT and LIMS with DDW.

Never have we seen such investment, growth and interest in the meticulous collection of human tissue, fluids and genetic information. By 2025, the biobank and biorepository industry is forecast to be worth $534.6 million with a compound annual growth rate (CAGR) of 14.9% from 2019 to 2026.1 Already, biobanks make up 11% of the life sciences segment and they continue to be a primary driving force for growth in this sector.

The dramatic growth is no surprise. Biobanks are critical for the expansion of several key therapeutic areas, such as cell and gene therapy, genomics and personalised medicine. As the impact of these therapies grows, so too will the reliance on tissue samples, complete with detailed patient information and history.

Biobanks have come a long way from the small private collections housed in university and hospital basements. The modern biorepositories of today are regulated, sometimes commercial, large-scale operations, containing many thousands and sometimes millions of samples. The scale of these systems and the new regulatory landscape bring novel challenges that put strain on the traditional methods of biobank management and threaten to limit growth, if left unchecked.

The many challenges of the modern-day biobank

The rise of the super-biobank has brought the industry under the spotlight, emphasising the enormous potential and power in human tissue samples and associated data. Already, we see biobanks housing millions of samples, such as Biobank Graz in Austria with 20 million individual fluid and tissue specimens,2 Shanghai Zhangjiang Biobank, the largest and most thoroughly characterised in China,3 and the United States ‘All of Us’ research program that aims to provide valuable information for common and rare disease research.4 With biobanks of this size, the simple act of tracking samples becomes an enormous challenge.

Along with the increase in storage capacity, biobanks are growing in diversity. As technology enables the collection of more data points and insights, the complexity of the data and metadata associated with samples, increases. Organising, storing and accessing this information brings additional responsibilities and opportunities.

As more industries rely on the integrity of the samples and information contained within biobanks, regulation begins to tighten to protect the samples they contain. Although rules vary between different regions, there has been a general upward trend around the governance of samples. Documentation, traceability, confidentiality, intended use and security are just some of the areas of focus for the Council of Europe5 and the OECD.6 In Europe, several biobanks are already adopting ISO-9001 as a measure of quality standards.

During collection periods, larger biobanks can receive significant numbers of daily samples, and efficiencies are required to ensure they are quickly and safely stored with tissue integrity maintained. Robust quality control processes are vital as each sample must be traced and tracked as it moves through the biobank. Quality control also extends to the retrieval and shipping of samples, so they are available to researchers in a viable, usable and easily accessible state.

The final, and by no means least, of the challenges come as biobanks interface with research and drug development. When working in ground-breaking and highly regulated areas, such as personalised medicine development, good practice (GxP) standards must extend further than the research and development laboratory. To supply samples into these fields, GxP standards must be applied within the biobank too and effective data management is key to demonstrating compliance.

Manual methods can’t keep pace with demand

Many biobanks, even the larger and more established ones, are relying on outdated methods of data management. Although they may use state-of-the-art ultra-cold storage equipment and remote monitoring systems, the data management technology associated with samples frequently lags behind. Often, biobanks rely on manual input to categorise and track samples, and data is held in siloed, disparate databases, which creates a barrier to integration and flow. This disconnect extends to laboratory management tools and even smart laboratory equipment, meaning that staff can’t make use of the full range of automation or analysis offered by this technology.

Traditional methods of data input and management lead to errors and inefficiencies that can create quality issues and degradation risks. When working with high-value samples, a few losses can have a big impact. Valuable research and drug discovery processes can be impacted, and this can have a very real, human consequence, particularly when researchers are working with rare diseases and unique samples.

Laboratory information management systems (LIMS) have long been established as an effective way of automating, storing and connecting data across the laboratory landscape, yet the acceptance by biobanks has been slow. One reason could be that LIMS are often not tailored to the specific workflows and requirements of a biobank, meaning that sections of the functionality are redundant. Installing and maintaining a system with redundancies is cost-prohibitive and hard to justify. Moreover, when a system is not fit-for-purpose it requires large amounts of training, and often workarounds, that can add substantially to the set-up time, integration and ongoing adoption by the organisation and its stakeholders. It’s easy to see why biobanks are reluctant to adopt a tool that won’t fully solve its data issues and may even bring its own set of challenges.

Next-generation LIMS will power the next phase of biobank growth

Industry 4.0 is bringing another level of digitalisation to the laboratory. We are in an age of connectivity, where big data drives efficiencies and smart equipment provides a constant stream of insight. Yet, to fully utilise the internet of things and the power of big data, laboratory 4.0 will need to combine this new level of digitalisation with automation. Biobanks must also keep pace with this industrial revolution to deliver new levels of efficiency, quality and cost-effectiveness now expected by the industry and its stakeholders.

Biobank-specific LIMS will lead this change as the central source-of-truth for the data and metadata behind every sample, piece of equipment and workflow. These systems already exist, but they vary in their current capabilities and capacity to meet the future demand of this evolving industry. For a LIMS that meets the requirements of today and tomorrow, there are several key elements to consider.

Full integration

Interconnectivity is the most basic requirement for a biobank-specific LIMS. Although it can be tempting to install a point solution (a piece of software that addresses very specific challenges), these systems are often limited in their application and connect poorly with other laboratory software.

More comprehensive LIMS, tailored towards the biobank market, should integrate seamlessly with laboratory systems, such as electronic laboratory notebooks, thereby breaking siloes and providing a centralised single-source-of-truth. The integration should also extend to external databases and software. By connecting with the networks supplying samples, a more streamlined flow of information can be automatically captured and stored.

Similarly, LIMS should interface with smart biobank hardware, including freezers and cryostorage systems, as well as the older more traditional methods of storing samples. The most advanced LIMS will also communicate with the monitoring systems increasingly installed in biorepositories. By relating critical parameter changes, such as power cuts or freezer failures, directly to the samples affected, the validity and quality of samples can be monitored more closely, even remotely. Action can be taken immediately to avoid outages, and if any samples have been compromised, they can be identified and removed.

Complete control from submission to storage and shipping

When working with thousands of individual samples, and their associated data and metadata, the chain of custody is central to effective biobank management. By gaining an end-to-end view of a sample, every piece of tissue can be precisely and completely controlled. This means understanding how it was collected and moved, its journey through the biobank to its exact storage location, and who was responsible for each touchpoint. When it comes to shipping samples, the audit trail extends beyond the biobank, and ensures the tissue and all of its data is disclosed quickly and only to those who have the necessary authority.

By recording this information in a centralised system, quality control procedures can be created and monitored, documenting exactly how long a sample remained out of cold storage, the exact freeze/thaw cycle and, therefore, the sample viability.

When it comes to accepting new samples, the biobank-specific LIMS should automatically manage capacity control. Most commonly, this is accessed through dashboards; at the touch of a button, users should be able to see the exact capacity available in each storage device. As biobanks aim to use all available space and reach maximum efficiency and cost-effectiveness, capacity management is a key functionality, as is the ability to quickly approve or reject additional samples, dependent on suitable storage space being available.

Easy and automated

Automation is a critical step towards industry 4.0, recognising that when manual input and human intervention is conducted, errors can occur and inefficiencies creep in. To accelerate processes across the end-to-end journey of a sample from entry to processing, retrieval and shipping, LIMS should be built on automation. This includes the generation of unique codes and barcodes, integrated label printing, and the tracking of this information throughout the biobank system.

Where automation is not possible, simplicity is key. By presenting only the features that users need, biobank-tailored LIMS are often much more intuitive and easier to use. Simple interfaces should guide users through necessary inputs and actions, and dashboards should provide a real-time overview of the exact status of the biobank, its samples and capacity. By only providing required fields and databases, user training is simplified and the resulting time and cost needed to train users are reduced. Once users see the benefits, uptake increases, the value is realised and the system delivers its cost and efficiency promises, freeing staff to focus on more value-added activity.

Embracing compliance

As the biobank industry grows, so too will the number of regulations surrounding their operation and the proper use of the samples within. Biobanks often supply to highly regulated industries and their sphere of influence means that compliance and ethical standards need to extend into the biobank. By automating processes and developing robust procedures for managing data, biobanks can ensure these systems withstand the scrutiny of the most robust regulatory standards, directly attributing the required informed constant and all associated data to each high-quality specimen.

GxP clinical, manufacturing and laboratory standards, Health Level 7 (HL7) international standards for the transfer of clinical or administrative data7 and ISO 9001 are just a few of the frameworks already being adopted by biobanks.

A LIMS for the real-world and the future landscape

Installing a LIMS is a considerable investment and stakeholders need to be assured that the system is fit-for-purpose and fully tested within the context of a biobank. Some developers provide the opportunity to see the LIMS in action on-site, either in a test environment, fully integrated with equipment and workflows, or by visiting an existing client. Either way, the LIMS can be demonstrated as it is intended to be used.

As the biobank industry grows in size and prominence, LIMS should demonstrate they are one step ahead, anticipating the value of progressive digitalisation and incorporating an evolving regulatory landscape.

Growth orientated biobanks need to look to LIMS

Biobanks have changed dramatically in the past few decades, evolving from the private collections of the prescient few to the vast organisational structures of today. Future therapeutics and the medical research of tomorrow relies on the samples being collected and processed now. There is no room for error when it comes to protecting these immensely valuable resources.

No matter the size or purpose of the biobank, future-proofed organisations must invest in systems that enable them to meet regulatory, efficiency and quality needs. LIMS offer the best opportunity to do this cost-effectively and reliably. As biobanks continue to grow in complexity, collecting more diverse samples and even merging with other biorepositories, they will be under increased pressure to standardise processes, develop more stringent quality control methods and provide robust documentation with a full audit trail.

Some LIMS are already taking the best of industry 4.0 and applying it directly to the biobank environment in a tailored solution. As technology continues to evolve, and systems, such as speech recognition, robotics and machine learning start to enter the biobanking space, these LIMS are ready to deliver yet more advanced levels of automation, digitisation and connectivity.

About the author

Lauren Taylor is a scientist and solutions manager in Digital Sciences at Thermo Fisher Scientific.  She earned her Ph.D. in Cell & Developmental Biology from University of California at Irvine and currently helps develop Lab Information Management System (LIMS) solutions for research, biotechnology and pharmaceutical markets.


  1. Markets and Markets Laboratory Informatics Report, Global forecast to 2026.
  2. https://biobank.medunigraz.at/en/
  3. http://www.outdoivd.com/en/service.aspx
  4. https://allofus.nih.gov/
  5. https://rm.coe.int/CoERMPublicCommonSearchServices/DisplayDCTMContent?documentId=09000016806492a7
  6. https://www.oecd.org/sti/emerging-tech/guidelines-for-human-biobanks-and-genetic-research-databases.htm
  7. https://www.hl7.org/implement/standards/

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