Effective sample inventory management is a growing priority for biotech and life sciences organizations managing biological materials such as DNA, RNA, tissues, plasma, and cell lines.
As research becomes more data-driven, laboratories must track not only where each sample is stored, but also its associated metadata, including lineage, experimental context, freeze–thaw cycles, and regulatory information.
Without a structured approach to biospecimen management, many labs rely on spreadsheets that quickly become fragmented, outdated, and difficult to scale. This leads to inefficiencies, lost samples, and reduced confidence in experimental data.
In this article, we explore five common challenges in sample inventory management for biotech labs, and how modern sample management software can help overcome them.
Sample inventory management in biotech labs is the process of tracking biological samples and their associated data, including location, metadata, usage, and experimental context throughout their lifecycle.
Sample inventory management refers to the process of tracking, organizing, and managing laboratory samples and their associated data throughout their lifecycle.
In biotech and life sciences, this includes:
Modern sample inventory management systems enable laboratories to replace spreadsheets with centralized, searchable, and scalable platforms.
Many laboratories still rely on spreadsheets to manage sample inventories. While simple at first, spreadsheets introduce major limitations:
One of the most common issues is that inventory data quickly becomes outdated. When multiple versions exist, scientists cannot trust the data, leading to delays, duplicated work, or even lost biospecimens.
Modern sample inventory management software provides a centralized, web-based system where all users can access real-time data. Advanced search capabilities allow scientists to locate samples using multiple parameters, such as:
With the advent of AI, new innovation in sample management software allows scientists to use simple natural language to locate their samples. This improves visibility, reduces errors, and ensures that sample data remains accurate and accessible across teams.
Early-stage biotech companies often rely on spreadsheets due to perceived cost savings. However, this approach can become inefficient and costly over time.
Managing biological samples requires tracking complex and evolving data, including:
Spreadsheets are rarely flexible enough to support these requirements at scale.
Today, cloud-based sample inventory management software has made professional solutions far more accessible. SaaS platforms eliminate the need for infrastructure, reduce IT overhead, and allow labs to scale gradually.
Solutions such as Cenevo’s Mosaic provide flexible, modular subscription plans and capabilities that grow with the organization, from early research to large-scale operations.
Managing biospecimen registration is widely recognized as one of the most complex aspects of laboratory data management due to the diversity of sample types and lack of standardized identifiers.
Even when the number of biospecimens is relatively small, the diversity of sample types can be significant. A single project may begin with primary cell lines, track multiple passages, and later involve DNA extraction. Other projects may focus on RNA, or on biological materials such as blood, plasma, and additional derivatives.
Beyond the variety of sample types, each biospecimen category often requires its own set of properties and metadata, many of which are not applicable across other sample types. This variability adds complexity to biospecimen registration and highlights the need for flexible, structured sample inventory management systems.
Each sample type may require different properties, naming conventions, and identifiers.
In spreadsheet-based systems, this often leads to multiple tracking systems, inconsistent naming standards, or difficulty searching across datasets.
Modern sample inventory management systems, such as Mosaic, allow laboratories to define flexible sample types and customizable metadata fields.
This enables teams to:
The result is a more structured, scalable approach to biospecimen registration.
Modern sample inventory management software, such as Mosaic, is designed to handle the complexity of biospecimen registration without adding operational burden.
At the core of Mosaic is a flexible Substance Type Editor, which allows teams to define and manage biospecimen types as their research evolves. New sample types can be created instantly, without relying on developers, custom code, or maintaining multiple spreadsheets, enabling labs to stay agile as projects change.
The platform also provides fully configurable metadata management. Teams can add properties at any stage, define required versus optional fields, and tailor data structures to different biospecimen types. This ensures that all relevant sample information is captured consistently, while remaining easy to search and access across the organization.
As laboratory operations scale, Mosaic grows with them. Its modular architecture supports integration with automated instrumentation, cross-site sample request management, and additional workflow capabilities, making it a strong foundation for scalable, connected sample inventory management in biotech environments.
Accurate storage tracking is essential for preserving biospecimen quality.
Samples are often stored across complex freezer environments, including freezers, racks, shelves, boxes, or individual positions.
If a sample cannot be located quickly, freezer doors may remain open longer than necessary, increasing the risk of temperature fluctuations and sample degradation.
A robust sample inventory management system models the full storage hierarchy and tracks the precise location of each sample.
Advanced capabilities include:
This ensures that biospecimens remain viable and accessible throughout their lifecycle. Learn how Mosaic supports sample inventory management in manual freezer environments.
Effective sample inventory management systems go beyond tracking physical samples; they require linking each sample to its associated data.
Because labels have limited space, most samples are identified using barcodes. However, the real value lies in connecting that barcode to rich digital information.
When a barcode is scanned in a sample management system, users can instantly access:
Modern systems also support customizable labels that combine barcodes with key human-readable information, such as sample type or hazard indicators.
This integration ensures full traceability and simplifies data access across workflows.
Improving sample inventory management in biotech labs leads to better efficiency, data quality, and scalability.
Key capabilities to focus on include:
By replacing spreadsheets with modern sample management software, laboratories can gain greater control over their biospecimens while reducing operational risks.
Modern laboratories are moving beyond spreadsheets toward scalable, connected systems.
See how modern sample inventory management software can help you:
Stop relying on spreadsheets. Start managing samples with confidence.
*Originally published on www.titian.co.uk