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How it Works: Managing R&D Data

Laboratory Information Management Systems (LIMS) are essential tools for managing data for QA/QC/Process labs throughout the chemical and petroleum industries.

by Agilent Technologies
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Problem: Laboratory Information Management Systems (LIMS) are essential tools for managing data for QA/QC/Process labs throughout the chemical and petroleum industries. However, the rigid database structure requires strict standardization of test conditions and results in order to populate predefined reports or integrate into distributed control systems. While this attribute is highly desirable for these routine labs, it creates problems for R&D labs where tests conditions are frequently modified or procedures are altered for a particular project. In these non-routine environments, LIMS are used primarily for sample tracking purposes rather than for data management. Non-routine, non-standard testing labs need a more flexible means for managing data that provides organized storage while retaining the ability for search and retrieval when required.      

Solution: Agilent Technologies Open- Lab ECM software provides a versatile complement to LIMS for storing and managing non-routine data. This open architecture system can automatically collect, classify, and store data acquired from nearly all types of laboratory instruments as long as it is in electronic form (Figure 1). Scheduling agents “crawl” through the LAN to collect all types of files from pre-defined locations at specified times, create meta-data from the files for advanced indexing capabilities, and store all data securely in a central repository. The agents can retrieve files from any LANconnected computer including personal machines. This allows all types of data for a project, including data contained in e-mails that were previously relatively inaccessible, to be brought together in a single location. This facilitates sharing of information among project members, reduces the loss of knowledge when team members depart, and secures intellectual property to support any patent applications that might result from the project. The system has multi-level security that strictly limits access for each folder to authorized users and limits functional capabilities based upon the permission level granted by the folder administrator. Data are viewed through an intuitive user interface that facilitates the easy manipulation and comparisons needed to extract the critical information required to solve a particular problem (Figure 2).

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The metadata extends the search capabilities so that data that were not recognized as relevant at the time of collection can still be easily searched and retrieved. For example, if a researcher observes an unexpected peak in a chromatogram, he can query the system and nearly instantly retrieve all chromatograms containing a peak with the same retention time. The system also has a business process module that automates and manages the lab’s workflow so that tasks such as approvals, release of reports, instrument maintenance, document control, and so forth can be assigned and tracked. And, the software is scalable so that it can support a single workgroup or an entire company.

As resources have declined over the past decade, it has become even more critical for laboratories to increase productivity in order to continue to meet the needs of the business. Data management has been identified as a major bottleneck for most labs and thus presents a significant opportunity for increasing productivity by reducing the manpower lost to tedious tasks such as filing, collating, searching for information, etc. While the actual time spent on these tasks will vary from lab to lab, most labs identify these tasks as an impediment to their operations that detracts from time spent on the science. For labs generating large quantities of data, the financial payback can easily be less than one year.

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