As research programs expand across sites and disciplines, the limitations of traditional sample storage practices become more apparent. Disconnected records, overcrowded freezers, and unclear ownership hinder collaboration and slow scientific progress. At the same time, the growing value of samples demands greater accuracy, traceability, and control.
Kathi Shea
Chief Client Solution Officer
Sample Management Solutions
Azenta Life Sciences
In this Innovation Spotlight, Kathi Shea, the chief client solution officer of Sample Management Solutions at Azenta Life Sciences, discusses how by aligning storage infrastructure with data systems, governance policies, and service-based models, organizations can improve both efficiency and reliability while supporting continued growth.
What are the biggest sample-management challenges in molecular biology and life sciences research environments?
Despite advances in science, many labs still lack basic sample-management infrastructure such as 2D-coded tubes, readers, and digital inventory systems. In our interviews with more than 350 scientists, roughly 90 percent reported missing core tools for accurate sample tracking and retrieval. As a result, sample management remains manual, error-prone, and dependent on individual habits rather than reliable systems.
Sample information is often fragmented across spreadsheets, notebooks, and disconnected databases. This fragmentation makes it difficult to know what samples exist, where they are stored, or who owns them, leading to duplicated experiments, redundant purchasing, and underutilized materials.
Retention and cleanup policies are frequently unclear or unenforced. Scientists rarely feel empowered to discard materials, resulting in overcrowded freezers, limited space for active research, and increased operational risk.
As samples grow more valuable—particularly in genomics, cell and gene therapy, and longitudinal studies—maintaining unambiguous identification across the full lifecycle becomes more challenging. Manual labeling and disconnected systems increase both scientific and regulatory risk.
Scalability is another major challenge. Research is increasingly multi-site and collaborative, yet storage practices remain local. Teams often lack visibility into materials across facilities, limiting reuse and slowing discovery.
Finally, poor storage practices create sustainability and cost pressures. Organizations often respond to perceived space shortages by purchasing more freezers rather than addressing utilization, lifecycle management, and governance—driving unnecessary energy consumption, maintenance costs, and facility expansion.
What are the most common inefficiencies you encounter during facility assessments, and how do you help clients address them?
Across more than 90 facility assessments covering over 4,500 storage units, we consistently see significant inefficiency driven by underutilized cold storage. While 16–26 percent of total lab space is typically dedicated to cold storage, effective utilization often averages close to one-third of capacity once rack, box, and organizational inefficiencies are considered. Many labs could reduce their freezer footprint by 40–60 percent while maintaining appropriate backup capacity.
We begin with structured, data-driven assessments to establish baseline utilization and understand stakeholder pain points. From there, we help clients choose right-size storage based on actual usage, consolidate redundant or orphaned samples, delay or eliminate new freezer purchases, and implement shared sample resource centers to move infrequently accessed materials out of bench-adjacent space.
Many labs still rely on handwritten labels and spreadsheet-based tracking, which consumes scientists’ time and limits traceability. To address this, we deploy vision-based, AI-enabled tools that digitize freezer contents, including handwritten data, into structured and searchable records. Depending on maturity, solutions range from simple inventory tools to fully integrated sample management platforms, paired with 2D- and tri-coded consumables and readers. The goal is to reduce manual effort, improve accuracy, and make samples usable—not just stored.
Disorganized freezers and inconsistent labeling practices contribute to lost samples, wasted space, and increased risk, underscoring the need for standardized, digitally enabled storage systems.
©iStock, Vladimir Zapletin
Inconsistent freezer organization is another common issue. Disorganized layouts and labeling waste time and drive unnecessary duplication. We help establish standardized operating models that include intuitive freezer organization and labeling conventions, digital systems that create a single source of truth, ongoing maintenance services to sustain order, automation-compatible consumables, and shared resource centers with high-density or automated storage. This approach shifts freezer management from an individual burden to a professionalized service model.
Finally, in the absence of lifecycle governance, indefinite retention drives overcrowding and risk. We partner with leadership to define retention guidelines, clarify ownership, and establish routine cleanup processes—transforming freezer cleanouts from disruptive events into manageable, repeatable practices. Across all engagements, change management is foundational, ensuring sample management becomes an organizational capability rather than a temporary initiative.
What strategies do you recommend for scaling cold storage efficiently?
Efficient scaling starts with utilization data. Perceived storage shortages often reflect underused capacity that can be unlocked before new investments are made. Organizations should adopt tiered storage models that keep active samples close to the bench while shifting long-term or infrequently accessed materials to centralized or high-density environments.
Centralization and standardization through shared-resource models improve storage density, consistency, and predictability—especially when paired with early adoption of a unified digital inventory to ensure visibility and prevent duplication. For large or high-value collections, automation further improves density, handling efficiency, and sample integrity, particularly within shared resource centers.
When combined with service-based retrieval models and clear governance around ownership and retention, this approach enables scalable growth without slowing research.
How do Azenta solutions bridge the gap from initial sample intake through long-term storage and eventual use or disposal?
Azenta delivers an integrated lifecycle model connecting consumables, informatics, automation, and services. At intake, standardized 2D- and tri-coded tubes, plates, and reading systems ensure unique identification and metadata capture from the start. For day-to-day management, inventory platforms such as FreezerPro® and Limfinity® provide real-time visibility, mirror physical layouts, and maintain full audit trails so scientists can quickly locate materials without manual records.
As collections scale, storage options range from manual ultra-low temperature and cryogenic systems to fully automated platforms such as SampleArc™ and BioArc™. These high-density systems reduce manual handling while maintaining temperature stability and controlled access.
Throughout the lifecycle, retrieval, consolidation, and compliant discard services support responsible stewardship. Organizations can manage samples onsite or leverage centralized and global repository services, all under harmonized quality systems and unified inventory platforms. The result is connected lifecycle management from intake to disposition.
How do sample storage and management challenges differ across fields, and how does Azenta tailor solutions?
Drug discovery and early research prioritize flexibility and rapid access. Lightweight digital tools, automation-friendly consumables, and scalable inventory systems support unpredictable growth.
Preclinical and clinical development emphasize auditability and compliance. Integrated informatics, controlled environments, and standardized workflows ensure traceability and chain of custody.
Biobanking and long-term repositories focus on preservation, density, and governance. Automated cryogenic storage, high-quality consumables, and harmonized quality systems support decades-long retention.
Cell and gene therapy involves highly valuable, sensitive materials with strict handling requirements. Controlled cold chain solutions, integrated data visibility, and modular storage architectures protect integrity while enabling rapid access.
Across disciplines, Azenta aligns storage models, informatics depth, automation, and services with access patterns, regulatory needs, and scale—allowing organizations to evolve without disruptive system replacement.
Looking ahead, what emerging trends will have the biggest impact?
Sample management is increasingly treated as core infrastructure, with enterprise-wide visibility and governance becoming essential. Organizations are adopting high-density automated solutions supported by hybrid storage models that balance bench-adjacent, centralized, and offsite facilities.
Greater emphasis on lifecycle governance is making retention and compliant disposition intentional rather than ad hoc, while sustainability considerations such as energy efficiency and space optimization are shaping facility planning. Service-based operating models and shared resource centers are also reducing the operational burden on scientists.
Together, these trends reflect a shift toward deliberate, digitally visible, and scalable sample management designed into facilities from the outset.
Is there anything else you’d like readers to know?
Samples are strategic assets, not consumables. Organizations that manage them with the same rigor as data and experimental design move faster and extract greater value from research.
Effective sample management requires integrated tools, governance, services, and change management aligned with how scientists actually work. The objective is consistent: keep samples visible, protected, accessible, and purposeful throughout their lifecycle, enabling better science today and unlocking insight for tomorrow.
