Antimicrobial resistance is often framed as a treatment problem. In reality, it is also a data and knowledge problem. The World Health Organization identifies antimicrobial resistance as one of the most serious global public health threats and highlights the importance of surveillance, quality diagnostics, and reliable information in shaping an effective response. Put simply, without trustworthy data, it becomes far more difficult to understand what is circulating, what is becoming resistant, and how to act.
This is where antimicrobial resistance biobanks become essential. A biobank of this kind is not just a set of tubes stored in a freezer. It is an infrastructure designed to preserve microbial strains and, just as importantly, the data that gives those strains meaning. That is what allows them to remain identifiable, comparable, and reusable over time. The International Society for Biological and Environmental Repositories (ISBER) defines repositories as structures in which specimens and their associated data are preserved for protection and distribution, while the Organisation for Economic Co-operation and Development (OECD) presents Biological Resource Centres as quality infrastructures for biological materials and related information. Isolate banks developed by institutions such as the Centers for Disease Control and Prevention (CDC) and the Food and Drug Administration (FDA) reflect the same principle: they support diagnostics, research, the study of resistance mechanisms, and the identification of emerging threats.
First, what is actually being preserved?
When we talk about a pathogenic strain, we are not only preserving a microorganism. We are also preserving its scientific identity. A strain only becomes truly valuable when there is a clear understanding of what it is, where it came from, under what circumstances it was isolated, how it was tested, and how it has evolved within the collection. This is fully aligned with the FAIR principles, which state that useful data should be findable, accessible, interoperable, and reusable, supported by unique identifiers, rich metadata, clear provenance, and shared standards.
In practice, documenting a strain means clearly and consistently recording a number of essential elements:
- a unique identifier for the strain or isolate;
- the date of collection;
- the location or geographic origin;
- the sample type;
- the isolation source;
- the host or sampling context, when relevant;
- antimicrobial susceptibility results;
- genomic or molecular data, when available;
- the method used for characterization;
- storage and traceability information.
Seen this way, a strain record is far more than a technical entry. It should make it possible to answer practical questions such as:
- what strain is this;
- when was it collected;
- where was it isolated;
- in what context;
- what resistance profile does it show;
- how was that profile determined;
- where is it stored today.
That level of structure is what turns a biological collection into a usable scientific resource. Standardization frameworks such as MIABIS, Minimum Information About BIobank data Sharing, were developed precisely to harmonize the description of biobanks, samples, and associated data in order to improve interoperability, sharing, and reuse.
Next, the strain’s lifecycle needs to be tracked
One of the most underestimated points is that the value of a strain does not depend only on its initial registration. It also depends on everything that happens afterward. ISBER best practices recommend systems that can track a specimen from collection or acquisition through transfer, distribution, or disposal across its full lifecycle. They also emphasize chain of custody, the use of inventory management systems, and the presence of an audit trail showing what was changed, by whom, when, and, where possible, why.
In an antimicrobial resistance biobank, that level of tracking is not just administrative. It makes it possible to know whether a strain has been moved, thawed, reprocessed, shared with a partner, retested, or enriched with new data. It also maintains continuity between the physical sample, the digital record, antibiotic susceptibility testing results, sequencing data, and the history of handling. Without this level of traceability, a collection may still exist physically, but it quickly loses part of its scientific value.
Where things become more challenging
The first challenge is not always the lack of samples. More often, it is the heterogeneity of the data. From one laboratory to another, the same information is not always named in the same way, the same fields are not always completed, and the same reference systems are not always used. Yet if collections are meant to be shared, searched, and compared, a common language becomes essential. This is exactly what MIABIS is designed to support, by standardizing the data elements used to describe biobanks, samples, and associated data. The FAIR principles reinforce the same need for rich metadata, persistent identifiers, and community standards.
The second challenge is operational fragmentation. As collections grow, manual tracking becomes increasingly fragile. Physical locations may be recorded in one place, analytical results in another, access histories in a separate tool, and exported files with little or no governance. ISBER guidance makes clear that virtual platforms, catalogs, and federated systems require harmonized terminology, data integrity, access control, and security. It also recognizes that implementing best practices can be difficult depending on the physical, financial, or organizational constraints of each repository.
The third challenge, less visible but just as important, is long-term sustainability. A biobank only remains valuable if the associated information is still usable years later. That means preserving not only the material itself, but also provenance, links between datasets, readable metadata, and the ability to retrieve a strain quickly through a searchable system. This is exactly what FAIR-aligned data stewardship and repository management frameworks are meant to support.
Preservation is no longer enough !
Once data becomes scattered, inconsistent, or difficult to connect, the limitation is no longer biological. It becomes organizational. At that point, the question is no longer simply how to preserve strains, but how to preserve them together with complete, coherent, and traceable information.
A solution adapted to an antimicrobial resistance biobank should therefore make it possible to centralize data, structure metadata, link analytical results to the correct strains, and ensure reliable tracking of movements, handling, and updates. The goal is not simply to organize information more neatly, but to make collections clearer, more reliable, and easier to use over time.
This is the context in which specialized solutions such as those developed by DiData become particularly relevant, by providing a more structured framework for documenting, tracking, and using strains consistently.
That continuity between the sample, the data associated with it, and the way both can be used afterward is what gives a biobank its full value. When a collection is well structured, it does more than preserve strains. It makes them available as reliable assets for surveillance, research, and decision-making.