Integrating LIMS With External Systems

Most end users want to integrate their LIMS with external systems, such as other applications or instruments. Although this process can be challenging, it’s critical for streamlining data management and ensuring seamless laboratory operations.

Most end users want to integrate their LIMS with external systems, such as other applications or instruments. Although this process can be challenging, it’s critical for streamlining data management and ensuring seamless laboratory operations.

Unfortunately, many LIMS implementations ultimately haven’t included instrument interfaces for a variety of reasons. Common obstacles include time and budget limits, proprietary instrument formats, and available resources. In some cases, stakeholders even question the benefits of interfacing with instruments altogether!

Although each laboratory must assess its own integration needs, there are strong cases for establishing these links, both with external systems and lab instrumentation. For example, integrating with ERP (Enterprise Resource Planning) or MES (Manufacturing Execution Systems) is crucial to the production side of your operations and ensures seamless data flows.  Integrating with other laboratory systems, such as Chromatography Data Systems (CDS), connects disparate data sources and reduces manual data transfer errors and lag times.

Here are nine key factors to consider when planning system or instrument integrations with LIMS:


1.      Compatibility

Data formats are often defined by individual instruments or systems. Depending on the data source and the type of integration, these could include XML, CSV, JSON, text, or other formats. You’ll need to ensure that each device’s data is parsed appropriately and mapped to the correct corresponding items in your LIMS.

Data Mapping

2.      Data Mapping

During the integration process, data formats, units of measurement, and codes should be standardized as much as possible to prevent data inconsistencies.

3.      Integration Method

There are a variety of possible integration methods, including API (application programming interfaces), middleware, ETL (extract, transform, load), file transfer, or even custom scripts. Which method will be most efficient for your integration is a question that will need to be assessed on a case-by-case basis for each instrument, system, or integration type.

4.      Real-Time Versus Batch Integration

The capabilities of each individual instrument will often be the deciding factor when it comes to choosing whether data integration will be conducted in real-time or batch mode.

Real-time integrations have the advantage of generating readily available results, enabling more timely decision-making, data transparency, and easier satisfaction of regulatory requirements. On the flip side, they’re also more complex and potentially more costly. In addition, results might be lost if the instrument suffers any downtime interruptions during real-time integration.

Batch integrations are less complex, allowing scheduled data transfers, greater compatibility with legacy instruments, and more efficient use of your organization’s resources. They’re not without risks, however — batch integrations can delay access to critical data and create the potential for data overload.

5.      Data Validation Rules

Data validation is vital to any integration because it ensures the integrity and accuracy of data during the process. There are multiple different types of validation, which can be carried out by specialized software tools or custom scripts. You’ll need to determine which validation method(s) to use to ensure the quality of your data is retained after integration is complete.

6.      Error handling

Errors may occur during the integration process, so it’s important to have procedures in place ahead of time to handle any challenges that arise.

Data Security

Instrument integration is typically managed by a scientific data management system (SDMS), which will generate a log for each transaction. In the event of an error, the message log can help determine what went wrong.

7.      Data security

Security measures should be implemented to protect your data throughout the integration process. In particular, sensitive data should be encrypted with access restricted to authorized personnel.

8.      Compliance

Integrated systems must comply with any relevant regulatory requirements. Depending on your industry, compliance standards may include CAP, ASTM, ALCOA+ principles, ISO, CLIA, HIPAA, GAMP, or other published standards. Compliance may also govern factors such as data storage and traceability.

9.      Validation

Test, test, test. Conduct thorough testing to ensure data accuracy and system reliability.


How LabVantage Can Help

Have questions about integrating your LIMS with instruments or external systems? The LabVantage professional services organization (PSO) has industry experts who can guide you through these and other considerations, from determining which instruments or systems to integrate with to ensuring that you’re in compliance before, during, and after integration. Contact us today to learn more.

Stay tuned for Part 2 in our system integration series!