- Rita Lencastre Fernandes, Head of Lab, NNIT.
- Matias Ejstrup Rosenkvist, Senior Consultant, NNIT.
Efficient integration of laboratory instruments with systems like LIMS, ELN or scientific data platforms can significantly boost productivity and unlock new business opportunities. But only if the integration rests on a strategic foundation.
Integrating laboratory instruments with the core systems as Laboratory Information Management Systems (LIMS), Electronic Laboratory Notebooks (ELN) or laboratory execution and data platforms is critical for ensuring that the constant stream of lab data is recorded, shared, and analyzed efficiently. Unfortunately, many organizations still treat integration as a narrow technical task rather than a strategic business initiative.
Integration of lab equipment is often treated as a one-off project, owned and initiated by individual teams. With this bottom-up approach, the stakeholders typically don’t see the bigger picture and how the integration impacts the rest of the organization. This results in both missed opportunities and complicated cross-lab reporting, validation documentation, and system maintenance, says Rita Lencastre Fernandes, Head of Lab at NNIT.
For example, a lab team may request custom integration for a digital scale used in a stability study. However, they do so without realizing that the organization operates 50 identical scales across multiple departments, some of which are already integrated. Establishing a project-specific integration with unique protocols and documentation is needlessly complicated and creates inconsistencies in how weight data is formatted, time-stamped, and transferred to LIMS.
Integration complexity increases with the degree of lab digitalization
As digital ambitions in laboratories evolve from using a few core systems like LIMS to implementing lab automation, digitally enabled workflows, integrated wet and dry labs and AI driven experimentation, the complexity of integration of increases exponentially. This goes for both wet lab equipment, data pipelines, and applications.
If you want digitally enabled workflows, then point-to-point integrations between individual instruments and systems will not suffice. Instead, you need a scalable strategy that uses integration platforms to decouple data producers (like instruments) from data consumers (such as analytics tools or LIMS). This approach provides greater flexibility, scalability and long-term maintainability.
Not every integration needs to be complex
Despite the need for strategic planning in the face of increasing complexity, don’t get carried away with integration for the sake of integration. You should always begin any integration project by asking these critical, pragmatic questions:
- What is the integration aiming to achieve?
- How much manual work will it eliminate, and what is the expected value/benefit?
- Can the same objective be achieved by tweaking the process?
- Are there simpler alternatives to integration – such as using barcodes instead of manual entry, or attaching files instead of parsing data?
And before building any integration, always ask:
- What will it cost to implement and maintain?
- Who will be responsible for implementation and ongoing support, and do they have the necessary skills and expertise?
Lost in translation during implementation
Challenges often arise because IT teams do not fully understand laboratory workflows, and lab personnel are unfamiliar with the technical requirements of integrations. This gap in understanding can result in critical data being missed, incorrect data transfers, or workflows that require unnecessary manual steps.
A trained scientist can easily spot the peak in a chromatographic measurement by looking at the graph, but if the system is not properly configured with the correct algorithms and parameters, a computer may struggle to identify that same peak. Without an integration partner that understands both the technical and scientific challenges, integrations fail to deliver their full potential, says Matias Ejstrup Rosenkvist.
Shared use of instruments across multiple project teams, like a High-Performance Liquid Chromatography (HPLC), can also lead to fragmented data handling. For instance, one lab may have three separate teams focused on small molecule stability, protein aggregation, and metabolite identification. Each team has its own summary report structure, using unique file types, naming conventions, and data layouts. As a result, integrating these outputs into the LIMS requires multiple custom pipelines and mapping logic.
By taking a holistic view of how the data is generated and used, labs can identify significant overlap among these methods. In the example above, all team reports share core data fields like sample ID, retention time, peak area, and concentration, with only a few method-specific differences. This allows the laboratory to standardize all HPLC outputs into a single summary report template, Matias Ejstrup Rosenkvist explains.
A unified integration design also means that instead of maintaining and troubleshooting three separate integrations, the lab only needs to support one. This not only streamlines regulatory reporting and cross-team data analysis but also reduces the risk of data inconsistency and integration errors.
Vendor-specific or multi-vendor approach
Another factor that has a significant impact on the integration strategy is whether the lab equipment comes from a single supplier or several different vendors.
If all instruments are supplied by a single manufacturer, labs may be able to take advantage of vendor-provided software to streamline their data flow. This software typically includes workflow and data management tools that interface with all instruments from that brand.
By developing a single integration between the vendor’s application and for example the LIMS, labs can automate worklist distribution, trigger analyses, and route results directly to appropriate database fields. This eliminates the need for manual data entry, reduces the risk of errors, and speeds up the lab work, says Matias Ejstrup Rosenkvist.
However, many laboratories use instruments from multiple vendors, each with different communication protocols and data formats. In such cases, labs can implement middleware for protocol conversion to standardize communication across all instruments.
The middleware acts as a translator, converting incoming data into a unified format such as JSON or XML. The LIMS then accesses this standardized data through a single API endpoint, enabling seamless integration across the entire instrument fleet regardless of vendor or device complexity.
These two integration models show how the optimal integration approach depends on the lab’s instrument landscape, scalability needs, and digital ecosystem. They also highlight why a solid grasp of both the available technical options and the different lab workflows and requirements are essential for making the right choices.
Want help to build a strategic implementation foundation?
At NNIT, we are ready to assist you with a comprehensive integration design that will enable you to eliminate manual data entry, ensure consistent data quality, and support regulatory compliance.
