Laboratory organizations have a myriad of reasons for choosing to implement a Laboratory Information Management System (LIMS). The key reasons can vary dramatically depending upon the industry and type of science being conducted in the laboratory as well as the type of laboratory to be automated and managed with the LIMS. That being said, we have compiled our top four reasons that drive organizations to implement a LIMS include.
Regardless of the industry or type of science being conducted in the lab, if the lab to be automated and managed with your LIMS primarily provides Quality Assurance / Quality Control (QA/QC) support, then improving efficiency and productivity will be a key reason for implementing a LIMS. When implementing a LIMS in this type of environment, improving efficiency and productivity includes that of the lab personnel (technicians, scientists, group leaders, managers, etc.), the lab’s work and data processes, and the lab’s operating processes.
Improving efficiency and productivity with your QC/QA LIMS will be driven by automating manual, mundane, or repetitive lab processes. For example, technician productivity can be improved by automating in the LIMS the development of the QC Batch (Samples, Duplicates, Spikes, etc.) and automating all the associated batch and sample calculations. While, a scientist’s productivity may be improved by automating the generation and delivery of routine reports that are being manually generated today (i.e. COA, OOS, Daily, Weekly, Monthly, etc.). Even larger efficiency and productivity gains can be leveraged through the implementation of a LIMS when time and effort is expended upfront to document your current lab workflows and processes, then optimized for maximum efficiency, and then automate the new, improved workflows in your LIMS.
Improving quality can have multiple connotations including both the quality of the data that the laboratory produces and the quality of the product, entity, or process that the lab is monitoring. It is important to note that the “quality of the data” that we are speaking about has nothing to do with Data Integrity but rather is oriented towards the accuracy and precision of the data recorded in the LIMS and any derived data (i.e. calculated result) generated from the recorded data.
Improving data quality with a LIMS is primarily achieved through the computerization and automation of processes, and procedures while minimizing manual lab tasks such as data entry, data manipulation (calculations, statistics, etc.), data review/approval, data visualization, and data reporting in your LIMS. By automating these mundane routine tasks, one can dramatically reduce the opportunities for human error to creep in to your data. This can be something as simple as interfacing your lab instrument, like a pH meter or balance, with your LIMS. This will eliminate manual data recording and manual data entry (transcription errors).
Another great example is the automation of your previously manually performed calculations in your LIMS. By doing this, you will again eliminate a major source of human error and can even correctly and consistently enforce other math/science rules like significant figures and rounding. Further, by automating your calculations you will remove the need for a scientific peer or supervisor to rerun the calculations to ensure that they were done correctly.
Switching gears to improving the quality of the product, entity, or process, a LIMS can affect quality in many ways. A good example can be seen when one interfaces their LIMS to their manufacturing system (ERP, MES, etc.). In this situation, the ERP or MES will need the test results from a variety of intermediates. The data and results from the lab will be used to determine the quality of these intermediates (i.e. do they meet the specifications) and thereby whether or not the manufacturing process can continue or needs to be adjusted in some way. By integrating your LIMS to your manufacturing system, you will remove the human error that may be caused when transcribing data and results from your LIMS into your
ERP or MES. Further, by integrating these systems you will greatly reduce the time needed for the lab data to get into the manufacturing system. This can lead to significant quality improvements, since the operation will more quickly learn of any deviations or errors quality issues within the intermediaries, allowing for faster adjustments to the manufacturing process to bring the quality back in line.
Another major driver for lab organizations to implement a LIMS is the need to adhere to, and be able to prove adherence to, regulations that pertain to the lab’s industry and the type of science being conducted in the environment. Some may argue that only labs that are regulated by a regulatory body (international, national, industry-specific, etc.) are the only lab organizations that would seek to improve regulatory compliance through the implementation of a LIMS. However, regardless of the regulatory realities of your situation, all labs should seek to adhere to Good Laboratory Practices (GLP) which will necessitate the adherence to at least a modicum of regulatory constraints that can be easily addressed in your LIMS.
FDA regulated organizations like pharmaceutical and biotechnology companies that are manufacturing and marketing a finished product, have some of the most stringent and broad-reaching regulations to adhere to. Automating most of these regulatory lab and data management needs in your LIMS will greatly reduce your organization’s risk and exposure while ensuring that you have the records and data needed to withstand a regulatory audit. Of course, the other benefit to enabling your regulatory compliance through your LIMS will be an improvement in efficiency and productivity as the manual records upkeep will be eliminated.
At the end of the day, the true product of your lab is information, not just data. Data is important, of course, but data without context and/or interpretation (i.e. information) will not be as useful for decision making. How data becomes information and is then disseminated can be greatly facilitated through the implementation of a LIMS. For example, you may have run a series of HPLC samples in a QC batch to test the efficacy of your drug product. In order to correctly interpret the data from the run, the QC batch data must be reviewed and taken into account in addition to the sample test results. Managing you QC batch through your LIMS and having your CDS integrated to your LIMS will greatly enhance the availability of the data that needs to be reviewed. This will speed up the analysis and interpretation steps of the data workup which in turn will speed up decision making.
Another aspect of improving decision making that is facilitated by a LIMS is the availability and dissemination of the data and information stored in or accessible through the LIMS. A LIMS will provide a number of reporting (standard and ad-hoc) and visualization tools that the lab personnel and their customers will have access to providing quicker and more flexible access to information. Additionally, reports can be fully automated so that they are generated and delivered to the appropriate parties without any human intervention as soon as the information is available.
What were the main reasons you chose to implement a LIMS? Were your reasons to implement a LIMS one of the four noted above?