Lab Design: ULT storage automation

As the need for ultra-low temperature sample storage rises, many labs are stuck expanding outdated ‘freezer farms’ to meet demand. High-density automated cold storage offers a smarter, more efficient solution, but reaping the benefits depends on more than the technology itself – it requires thoughtful change management. How can companies approach change management to drive lasting adoption and maximise the value of automation?

Kathi Shea at Azenta Life Sciences

Pharmaceutical and biotech organisations typically need to store and manage vast numbers of samples to support research and clinical development. Many of these samples must be kept in ultra-low temperature (ULT) freezers, with demand for such storage increasing in recent years due to a shift towards biological therapies.

In response to growing numbers of samples, the default option in many facilities remains the same: buy another freezer. While this may solve the immediate storage need, over time this approach results in sprawling networks of freezers that are problematic and complex to manage. Automated, large-scale cold storage units can offer a more efficient solution. By maximising the use of vertical space and simplifying sample intake, retrieval and tracking, these systems can provide more streamlined sample storage in a reduced footprint. However, their success depends on an effective, thoughtful change management strategy. Without it, the system may be underused, limiting impact and reducing return on investment.

But what does it take to successfully implement automated cold storage? Here, we explore the advantages of automated cold storage, what changes when shifting to automation and how to manage the transition to realise the full benefits.

The value of automated cold storage

As organisations respond to growing sample volumes, many find themselves managing large groups of ULT freezers, often referred to as ‘freezer farms’. These systems are rarely optimised for scale and, in practice, can have significant limitations:

• Inefficient sample management: searching across multiple freezers and locations can be time-consuming and labour-intensive, particularly if tracking systems are informal or vary between departments

• Higher risk of error or misplaced samples: manual tracking and handling increases the risk of misplaced samples and temperature fluctuations during retrieval

• Risk of equipment failure and loss of research materials: as legacy ULT freezers age, they become more prone to mechanical failure, increasing the risk of unplanned downtime, and sample and critical reagent losses, as a result

• Poor space utilisation: ULTs can have poor sample-to-footprint ratios, requiring large amounts of floor space

• High energy consumption and environmental concerns: ULTs are very energy-intensive, driving up energy costs and increasing emissions. Many ULTs also still rely on refrigerants with high global warming potential (GWP), making it harder to meet sustainability goals.

Automated cold storage systems can address these challenges and offer numerous advantages:

• Streamlined workflows: automated retrieval offers easy, accurate sample access and reduces time searching for samples

• Improved sample tracking: centralised storage and digital systems provide complete audit trails and unified sample visibility

• Better sample safeguarding: automated sample retrieval eliminates temperature fluctuations related to door openings. Additionally, some systems come with triple refrigeration redundancy to avoid large-scale sample loss, with a main refrigeration unit, a secondary backup refrigeration unit and a tertiary backup using liquid nitrogen

• Higher-density: a single automated unit can replace 100-160 manual freezers, dramatically increasing sample-to-footprint ratios

• Enhanced energy efficiency and sustainability: large-scale automated cold storage can use significantly less power than the equivalent manual freezers, and some systems use refrigerants with zero GWP, reducing energy costs and making them significantly better for the environment.

While the benefits of large-scale automated cold storage are clear, to achieve them organisations must adjust and engage with new ways of working.

Adjusting to automation: key changes and challenges

Transitioning to automated cold storage changes infrastructure, workflow and workplace culture.

Moving from physical to digital sample management
One of the most significant changes introduced by automation is the move to a digital sample management system, requiring samples to be barcoded and accompanied by complete metadata. In many cases, this shift is accompanied by the implementation, or upgrading, of informatics systems (eg, laboratory information management systems) to track sample data and movements (such as who accessed it and when), offering a much more accurate and consistent approach than manual methods.

This can be a big day-to-day adjustment for staff as, rather than walking up to a freezer and simply retrieving a sample, they will now need to enter accurate metadata for each and submit retrieval orders via a database, which will process the request automatically.

While this ultimately makes sample management more efficient and streamlined, it can initially include additional admin work. For staff used to managing their own samples, moving to digital systems can also feel like a loss of control. This adjustment can be more pronounced in early research or preclinical settings, where existing digital infrastructure may be minimal.

Moving to standardised consumables and labware
Automated cold storage systems rely on robotic handling, which requires consistent, automation-friendly labware. In manual lab environments, it’s common for different departments – or even individuals – to have preferred consumables, leaving organisations with a wide variety of incompatible labware formats.

Moving to standardised consumables can, therefore, be challenging. Researchers may resist giving up preferred labware, especially if it has been validated for specific assays. Lab workflows may have been built around specific legacy formats, and inconsistencies in purchasing across departments can make enforcing standards difficult.

Changing workplace culture and sample perception
Alongside logistical changes, moving to large-scale automated storage can also alter workplace culture. In many facilities, cold storage units are simply seen as a behind-the-scenes necessity. Freezer farms are often tucked away in basements, rarely seen by visitors, and not recognised as a critical part of the scientific infrastructure. With automation, sample storage becomes a point of pride.

Having a more visible, centralised storage system moves samples into the limelight, showcasing the materials that underpin research. As it becomes fully integrated into day-to-day workflows, staff are more likely to see it as a vital enabler of scientific progress, rather than just a logistical requirement. This cultural shift can foster a deeper sense of ownership, care and responsibility around sample management.

Laying the groundwork for success: tips for optimising your change management strategy

Ultimately, the success of an automated cold storage system is not defined by the technology alone, but by how effectively people engage with it and adapt to new ways of working. By following some simple principles, organisations can build a change management strategy that supports long-term adoption, minimises disruption and helps teams embrace the transition with confidence.

Start with the end in mind
A successful change management strategy starts with having a clear understanding of your current situation and what needs to be done to reach the end goal. The process should therefore begin with a comprehensive discovery phase, where companies should:

• Standardise terminology across the organisation to avoid confusion and inconsistencies in tracking samples

• Catalogue stored materials to understand the scope and scale of what needs to be managed

• Map user patterns to find out what’s being used, how often and by whom

• Standardise data practices to ensure sample metadata is accurate, usable and compatible with automated systems.

Plan before you implement
Change management planning should be embedded in the early stages of an implementation. One of the most important first steps is to gather input from stakeholders across departments to find out:

• Their sample management pain-points

• The outcomes they are hoping for from the move

• What would make the transition easier for them.

The new systems need to work for everyone, from researchers to finance staff to senior leadership. Understanding the different value drivers across professions and incorporating them into the end goal can help keep teams on board with the process.

Alongside this, creating a timeline that outlines critical steps and clearly defines success milestones helps keep the implementation on track and people motivated.

If you notice the timeline slipping at any point, you should work collaboratively across teams to identify and address roadblocks.

Guide behaviour changes through system and environment design
Changes in behaviour can be difficult to enforce directly, but can be gently nudged. One example is consumables management, whereby the use of automation-friendly labware can be encouraged by centralising consumable purchasing and only stocking compatible formats in shared stockrooms. You can still offer a repertoire of options, but if you make it easier for staff to access what’s compatible, behaviour change will be driven naturally and without resistance.

Centralising consumable purchasing can also come with other benefits, such as cost savings on bulk purchasing and easier inventory management due to greater consistency across departments.

Implement varied training strategies
No two people learn the same way, and recognising this during the implementation process is crucial for successful adoption. Organisations should use a variety of training formats, including:

• Verbal teaching

• Visual aids

• One-on-one support where needed.

Where possible, embed training materials into everyday workflows to encourage action and bring familiarity to the new processes.

Communicate consistently and transparently

Regular communication is one of the most important tools in any change management strategy. It builds trust, reinforces progress and creates a sense of shared purpose. To keep teams on board throughout the transition:

• Use visual cues to show progress, such as before and after images of sample organisation systems

• Communicate around the identified value drivers to build confidence and trust (eg, if a key value driver for lab staff is fewer lost samples, communicate before and after figures)

• Celebrate wins, especially if they address known pain points

• Invite two-way communication from staff to find out what is going well and what could be improved. Communicating firsthand successes from staff themselves to wider teams can spur motivation, and taking feedback on board demonstrates a willingness to adapt if needed.

Recognise that change management is a journey
Organisational change, particularly at the infrastructure level, is rarely quick and easy. The implementation process can take anywhere from a few months to over a year, depending on a company’s specific requirements.

For example, for a company with a small molecule compound library that may already be using standardised labware and structured inventory systems, change management may focus mostly on training staff on new equipment. In contrast, a research or clinical team with varied labware and limited digital infrastructure may face a longer, more complex transition.

Whatever the starting point, it is vital that organisations do not underestimate the importance of the change management process. Success depends on approaching change as a journey, starting with the end in mind, and developing a structured, thoughtful plan tailored to your organisation’s specific needs.

Change management as the foundation for automation success

Automated cold storage offers a powerful solution for managing growing sample numbers, particularly when it comes to maximising space efficiency through vertical storage, streamlining sample management and improving lab sustainability. But unlocking the full value of these systems relies on more than the technology itself; it depends on how well the change process is managed.

By implementing a tailored, well-planned change management strategy, underpinned by effective communication and training to drive behaviour changes and motivate staff, organisations can ensure a successful transition to automated large-scale cold storage and reap the full benefits.