Over the last 10 years, biobanks have become a staple of biomedical research. The ability to accumulate, catalog, and dispense a variety of sample types from a large population of donors, both healthy and diseased, has facilitated an abundance of new discoveries and made biobanks the perfect model for managing samples. Generating new data is so efficient that each week, the UK Biobank publishes a new study based on information obtained from its own samples. However, caring for so many samples requires not just skilled personnel, but also systems that can track and trace these samples without making errors. This has led biobanks to integrate practices from pharmaceutical and biotechnology manufacturing companies to ensure their inventory of samples is properly maintained and distributed accordingly.

The UK Biobank1

The UK Biobank is a perfect example of how manufacturing principles were applied to biobanks. Created in 2007, it harvested blood, urine, and saliva samples from approximately 500,000 donors. The samples were then all linked to the participants’ medical records, so they could follow up with the patient while tracking disease incidence and death. The aim was to provide easily accessible samples that would be used for longitudinal health studies, which in turn could lead to the discovery of new early biomarkers of disease or relationships between the demographic (i.e. gender or age) and molecular (i.e. expression of certain markers) characteristics of the patient. At full capacity, the UK Biobank can store upwards of 15 million samples divided into a working and backup archive.

So, how do they effectively manage 15 million samples? They track and process samples using a commercially available LIMS called Nautilus. This LIMS—now called a biobank information management system, or BIMS—was originally developed for high-throughput analytic labs and was configured to manage the biobank’s repetitive sampling procedures. In doing so, they incorporated two types of barcoding systems: 1D barcodes were adopted for vacutainers while 2D barcodes were used for 1.4 ml aliquot storage tubes. The barcodes used had four levels of redundancy, meaning they could be read even if damaged. For each aliquot, they took advantage of automated labelers to label all tubes with information like time and date of collection, as well as archiving, temperature, and sample volume, matching it with the individual donor. To protect the identities of the participants, they secured each sample by applying only barcodes to each tube as well as a unique 12-digit identifier that corresponds to the participant. They also restricted access to the system and separated the data in the LIMS from that of the assessment center, which holds the identity of each participant. The entire operation is held together by the ability to track samples in real time, with barcodes scanned at every point, from the time they arrive at the biobank to the time they leave for testing.

Quality control is also a key priority in the management of the biobank’s samples. Here is where they’ve implemented ISO standards, including ISO 9001:2015 and ISO 27001:2013. Instead of designing a system to detect and reduce the number of errors associated with sample processing, they’re developed one that aims to eliminate errors altogether, while maintaining a smooth, efficient workflow that’s free of processing bottlenecks. They even adopted a manufacturing approach to implementing their system, carefully designing it, developing prototypes, then integrating and testing the system prior to collecting samples.

It’s worth mentioning that these strategies weren’t implemented to reduce personnel costs. Instead, the main goal was to keep a high throughput of high-quality samples, with the biobank’s staff responsible for identifying errors and making sure everything runs according to plan. The system they used was also not a brand-new, commercially developed system specific to the UK Biobank. They merely took advantage of what was already available (e.g. LIMs and consumables) and adapted it to their needs, paving the way for others to develop similar systems.

Other Biobanking-Derived Solutions to Sample Management

In 2011, the Tohoku Medical Megabank (TMM) Biobank was designed to address the medical issues of patients in areas that were damaged by earthquakes and tsunamis in East Japan. The biobank collected more than 2.8 million specimens from 150,000 people between 2013 and 2017, in addition to generating and storing thousands of Epstein-Barr virus (EBV)-transformed cell lines and proliferating immune cells. Just like the UK Biobank, it integrates a BIMS, automated sample processing, and manufacturing principles—with ISO certification—to deal with the large sample volume. Moreover, they identify the participant’s sex and ABO blood type on all blood collection tubes and genomic data, which is used to identify mismatches and correct them. The TMM biobank also participates in the Proficiency Testing (PT) program at the International Biobank of Luxembourg (IBBL), which is endorsed by the International Society for Biological and Environmental Repositories (ISBER) and used by many other biobanks worldwide, to confirm the quality of their specimens.2,3

Some other tactics that biobanks around the world have adopted include:4

Freezer mapping – This entails designing maps of every item stored in freezers and liquid nitrogen Dewars, effectively reducing the time it takes to retrieve samples and minimizing sample thawing. Here, cryo labels are necessary to ensure proper sample identification, especially in liquid nitrogen, and a thermal-transfer printout is recommended, as it provides the most protection against extreme temperatures.

Radio-frequency identification (RFID) – RFID labels use radio waves to transmit data. There are several advantages to using RFID labels, such as the ability to scan without removing samples from freezers and the ability to scan multiple labels simultaneously.

Setting a Precedent

Many labs are not operating as efficiently as possible. Without a LIMS to store data, manage inventory, and schedule workflow, not only can samples get lost, but their integrity can be questioned if the data associated with it (i.e. the date and time taken, number of times it’s been thawed or processed, sample volume) is not recorded properly. This is especially problematic for labs that store human specimens, as these are usually irreplaceable. By looking to the principles and best practices of biobanks, labs and departments can integrate a framework of automated (or partially automated) sample tracking that would not only eliminate casual errors but also improve the productivity and scientific accuracy of their studies.