With the pressure to generate results, optimise workflows and meet deadlines, sample integrity is taken for granted… until something goes wrong. Yet what happens around the bench in terms of layout, logistics and zoning is as important as what happens on it, cautions Katy Linkens.

We’re all familiar with the buzzwords in life sciences today – actionable insights, patient outcomes, and real-world impact. R&D teams across the country work tirelessly to deliver on these goals; troubleshooting experiments, generating data and navigating a plethora of lab logistics. Amidst this high-level work is an often-overlooked fundamental stands at the centre – the sample. In the pressure to generate results, optimise workflows and meet deadlines, sample integrity is taken for granted… until something goes wrong.

Sample integrity is the foundation of any experiment, with most landmark discoveries coming from humble beginnings such as cells, DNA or clinical specimens. But in the drive to produce headline-grabbing discoveries, do samples really get the attention they deserve? A poorly handled sample can undermine even the most sophisticated downstream work.

Having worked in labs for more than 10 years, I’ve seen a wide spectrum of environments. Ranging from bespoke workflow-designed facilities to office-spaces repurposed as labs, and even setting up labs from scratch. I’ve encountered everything from last-minute trips to supermarkets for ice due to delayed equipment delivery, to fully automated high-end workflows.

These experiences have shown me first-hand that detail-focused planning regarding sample handling delivers cleaner data and smoother downstream workflows. In contrast poor design and planning can compromise samples, causing neverending snags in any ensuing experiments. Below are some key considerations for maintaining sample integrity, applicable to both greenfield builds and retrofit adaptions.

1. Sample pathway

Sample integrity begins well before the sample reaches the lab bench. Consider the full sample pathway; collection, transport, receipt, processing and storage. Ensure that chain-of-custody procedures and documentation are in place ahead of time, with a clear audit trail maintained throughout. Always expect delays and mitigate any transport risks, for example, by including ample dry ice for temperature sensitive samples. Assign clear responsibility on-site for sample receipt, minimise handling steps and ensure rapid transfer to storage or processing if time-sensitive.

For high-throughput labs, contingency storage, such as additional fridges and freezers helps prevent bottlenecks during peak intake periods. A well-defined pathway reduces errors, preserves quality, and supports reproducibility. The sample path continues through the lab as described below.

2. Lab zoning

Creating defined physical zones for separate workflows reduces risk of contamination and improves operational efficiency. When setting up new labs, we designated specific areas for activities such as molecular biology, virus work and flow cytometry. Where possible, arrange these zones strategically to encourage one-way movement of personnel and materials. Shared resources such as balances or pH meters can be centralised in dedicated media or buffer preparation areas. Where physical separation is not feasible, visible cues such as floor markings, colour-coded benches or standardised equipment labelling can reinforce zoning principles.

Effective zoning supports both sample integrity and day-to-day efficiency, enabling smoother workflows and easier maintenance of organised lab spaces.

3. Space considerations

Crowded benches are a common but perfectly avoidable risk. A crowded bench increases the likelihood of mix-ups, mislabelling and spillages, especially when multiple experiments are running in parallel. Sufficient bench and storage space should be allocated to allow for concurrent workflows. Every reagent, instrument and sample should have a clearly defined and labelled location, easily accessible for the scientist at the bench.

4. Cold storage

Cold storage is another critical component of sample integrity, yet it is often where systems begin to break down. Many labs are familiar with the black hole of freezer organisation, where space is limited, nothing is quite where you expect it to be and opening any given drawer risks an avalanche of ice. Look closer, and issues become more apparent; halffilled boxes, tubes labelled with a single digit, samples stored ‘temporarily’ for years and legacy material that has no more relevance or use. Without active management, these systems quickly become inefficient and increase the risk of sample loss or degradation. Consistent labelling and logging systems should be implemented, with periodic audits to remove obsolete samples.

It’s important to place cold storage strategically. For example, tissue culture labs always need a -80°C freezer nearby. Each zone should be assessed for whether it needs fridge/freezer. Cold storage should also be designed with future growth in mind, never underestimate how quickly these fill up (!) Allow some capacity for expansion. When integrated effectively into lab workflows, this reduces retrieval time and protects valuable samples.

5. Environment maintenance

Lighting, temperature, airflow – environmental conditions are often overlooked but play a significant role in sample stability and user performance. Temperature-controlled spaces must be designed and maintained to ensure consistency. Lighting should be appropriate for the work being conducted, i.e. allowing for dimmer switches in molecular laboratory rooms.

It is also important to consider every lab’s most valuable asset – scientists themselves. Adjustable lighting, temperature and airflow contribute to comfortable working environment, helping to reduce fatigue and minimise handling errors over long experimental days.

Sample integrity is not incidental, in fact it is a direct outcome of laboratory design. From the moment a sample enters the lab to its final analysis, layout, zoning, storage and environmental control all play critical roles. Investing in these elements upfront not only protects experiments but also enhances workflow efficiency, reproducibility, overall lab performance and happier scientists.

• Katy Linkens is currently completing her PhD in molecular biology at UCL, where she has spent the last four years developing gene therapies