Sample management has become one of the less visible but very important parts of drug research and development.
A discovery laboratory can handle thousands of compounds, biological samples, cell lines, proteins, plates and assay results. If researchers cannot quickly answer what the sample is, where it is, how it was prepared and which experiments used it, valuable research time can disappear into spreadsheets and disconnected databases.
That is why modern informatics platforms are moving beyond simple sample storage. The stronger systems connect sample identity, inventory, lineage, experiments, assays, instruments and research data in one environment.
Drug discovery is generating far more complex data than traditional laboratory workflows were designed to handle.
Drug discovery industry size is calculated at USD 71.96 billion in 2025, grew to USD 78.61 billion in 2026, and is projected to reach around USD 174.14 billion by 2035. The market is expanding at a CAGR of 9.24% between 2026 and 2035.
Towards Healthcare estimates that LIMS represented 23% of life science software revenue in 2025, while research and drug discovery accounted for 30% by application. The same analysis identifies pharmaceutical and biotechnology companies as the leading end users, with a 49% share.
There is also a practical reason behind this adoption.
A study cited by Towards Healthcare found that 57% of LIMS users reported improved sample-management practices, while 61% said removing manual procedures increased productivity.
Benchling: Strong for Biotech R&D
Benchling is one of the most recognizable names in modern life-science R&D informatics.
Its platform combines ELN, LIMS, molecular biology tools, sample management and inventory. Researchers can connect samples with experiments, protocols and results while maintaining data lineage across the research process. Benchling says its platform is used by more than 1,300 biotechnology organizations.
For emerging biotech companies, its strength is the connection between scientific work and sample records. A scientist can move from designing a construct to tracking the resulting sample and then connecting it with experimental results without maintaining separate systems.
Thermo Fisher: Built for Complex Laboratory Operations
Thermo Fisher Scientific’s SampleManager LIMS is particularly relevant for larger pharmaceutical and biopharmaceutical organizations.
The system can track samples, assays, inventory, requests, processes and data across discovery and development. It also supports accessioning, shipment management, storage and chain-of-custody requirements.
This becomes especially useful when research moves across multiple laboratories and instruments.
Thermo Fisher also offers connected ELN, scientific data management and laboratory execution capabilities, making it a strong option for organizations looking beyond sample tracking alone.
Sapio Sciences: Connecting Samples With the Science
Sapio Sciences takes a more integrated approach to sample management.
Its platform connects sample inventory, LIMS, ELN, workflows and scientific data, allowing researchers to follow sample lineage from receipt and storage through aliquoting, testing and downstream experiments. It also supports freezer management, barcodes and RFID.
For drug discovery organizations, this connection is important because a sample is rarely useful by itself.
The real value comes from knowing the sample’s history and linking it to the experiment, assay and scientific decision that followed.
STARLIMS and LabWare: Enterprise-Scale Options
STARLIMS is another established enterprise informatics provider. G2 lists it among leading LIMS solutions for pharmaceutical and biotechnology laboratories, with the company reporting more than 1,100 customers worldwide.
LabWare LIMS is similarly positioned for large and diverse laboratory environments where organizations need extensive configuration, sample tracking and standardized workflows across sites. Current industry comparisons continue to position LabWare strongly for large enterprise laboratories.
These platforms are particularly relevant when sample management has to operate within a broader regulated laboratory infrastructure.
A Simple View of the Leading Vendors
| Vendor | Main strength | Sample management | Best fit |
|---|---|---|---|
| Benchling | Biotech R&D | Strong | Molecular biology and discovery teams |
| Thermo Fisher | Enterprise laboratory operations | Strong | Large pharma & biopharma |
| Sapio Sciences | Connected scientific workflows | Strong | Drug discovery & multi-site R&D |
| STARLIMS | Regulated enterprise informatics | Strong | Pharma and regulated laboratories |
| LabWare | Configurability and scale | Strong | Large enterprise laboratories |
| Azenta Life Sciences | Dedicated sample & biobanking management | Very strong | Biobanks, repositories & sample-intensive research |
Azenta deserves particular attention where sample custody and storage are the central problem. Its Limfinity platform supports sample lifecycle tracking, storage management, laboratory workflows and clinical-trial sample support, while FreezerPro focuses specifically on freezer and inventory tracking.
What Drug Developers Should Actually Compare
Choosing a platform should not start with asking which vendor has the longest feature list.
The better question is whether the system can follow the complete life of a sample.
That includes receiving the material, assigning an identifier, storing it in the correct location, creating aliquots, recording transfers, connecting it to experiments and assays, and maintaining a clear history of every change.
Integration is equally important. A sample-management system that cannot communicate with ELNs, laboratory instruments, automation systems and analytical platforms can simply create another data silo.
The most useful informatics systems are gradually changing the role of sample management.
It is no longer just about knowing “where is sample 48372?”
Researchers increasingly need to know where it came from, what was done to it, which experiments used it, what the results were and whether related samples produced similar findings.
That is why Benchling, Thermo Fisher, Sapio Sciences, STARLIMS, LabWare and Azenta stand out for different parts of the drug R&D workflow.
For pharmaceutical and biotechnology companies, the strongest platform is ultimately the one that turns sample information into usable scientific context—and helps researchers spend less time searching for data and more time deciding what the data means.
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