Using Smart Instruments and Infrastructure to Improve Data Reliability
by Nicole Keppy, Senior Product Specialist, UV-Visible Spectroscopy, Thermo Fisher Scientific; and David Joyce, Senior Product Manager, Laboratory Informatics, Thermo Fisher Scientific
Safe pharmaceuticals may be the end goal of pharmaceutical QA/QC laboratories, but reliable, accurate and accessible data is what makes that goal possible. When data isn’t collected and organized well, labs become inaccurate and inefficient, which can result in delays– and even product recalls. These errors quickly become lost revenue through reduced productivity and time-consuming rework.
Errors in laboratory data fall into two categories: the first, data collection, encompasses all errors made at the instrument level. This includes improperly calibrated or misused instruments, user error and problems with sample collection or preparation. The second category is information management, which includes how the collected data is transmitted, stored, accessed and analyzed.
Ensuring data integrity by reducing the potential for error in both these categories is one of the most critical challenges that QA/QC laboratories face. Successfully meeting this challenge requires two things: smart instruments and a smart laboratory infrastructure. The cornerstone of a smart lab infrastructure is a laboratory information management system (LIMS), which can collect and manage raw instrument data from a series of integrated smart instruments in the lab. Every lab instrument– from simple scales to complex spectroscopic and chromatographic instruments– can be integrated into the LIMS (also known as a scientific data management system, or SDMS), ensuring that data is easily, reliably and efficiently collected.
Just as business innovation is facilitated by a well-organized, collaborative team, reliable QA/QC is the product of seamless integration between laboratory instruments and software. The end result is a highly-automated paperless laboratory where all instrument data is accessible enterprise-wide in real-time, increasing efficiency and ensuring reliable QA/QC data. To create this environment, QA/QC lab managers need to focus on two things: data collection and information management.
The first step in creating the paperless lab is to select the right instruments– not only do they have to be appropriate for the application, but they also must be able to interface with a LIMS. Most common instruments for pharmaceutical QA/QC labs, such as UV-visible spectrophotometer, have many different variants that are each appropriate for a different application. For at-line measurements using a UV-visible spectrophotometer, an instrument equipped with a sipper module is the best choice. Biopharmaceutical samples, however, are best analyzed using a double-beam instrument equipped with a thermal accessory and xenon lamp. Regardless of the application, it’s critical that the instrument has the capability to interface with a LIMS.
Laboratory managers must also decide the appropriate time interval for performance verifications of smart instruments – their smart technology does not exempt them from the need for maintenance to ensure that they remain on specification. Lab administrators must make this judgment based on the level of risk acceptable for the lab. The cost and frequency of maintenance is indirectly proportional to the possibility for instrument error, and each lab must decide the appropriate balance of these two factors.
In addition to performance verification, many laboratory instruments and accessories also require periodic alignment or calibration to perform accurate analysis. This is another facet of laboratory management that can be made more efficient using a LIMS– automating these vital procedures and executing them on a pre-defined schedule saves time, keeps labs up to specification and helps ensure regulatory compliance. Additionally, processes defined for one smart instrument, such as a spectroscopy system, can be easily applied to other instruments in the lab via the LIMS.
In addition to being properly collected, the data from laboratory instruments and systems must also be properly analyzed and managed. This is best done using a combination of software that starts at the instrument level. The GRAMS Suite of software, for example, is used by many QA/QC labs to automate and integrate data collection from multiple spectroscopy systems and other lab instruments. Automating this data integration not only speeds up the process but also significantly reduces the possibility of human error by eliminating manual data collection. Many software suites– including GRAMS– are instrument agnostic, which minimizes training expenses by requiring technicians to only learn one software package.
Despite their high level of automation, many of today’s software-enabled instruments still require human operation– and are therefore still subject to human error. Fortunately, software solutions exist to help lab managers reduce the possibility of user error. Labs that use Thermo Fisher INSIGHT 2 software, for example, can custom configure their spectrophotometers to better serve the specific applications of their instruments. Used in conjunction with customized user environment (CUE) software, the spectrophotometer can guide the user through a step-by-step process to ensure proper operation. All data collected can be easily audited by an administrator, as well as formatted for use by customers and/or other systems further downstream.
When smart instruments and smart infrastructure work together, laboratories can reach an unprecedented level of connectivity, reliability and efficiency. Labs that integrate their instruments with LIMS, GRAMS and SDMS software also benefit from a data “safety-net” that reaches from loading bay to final shipment and ensures the reliability of accessibility of their data – not only across labs, but across continents. Critical lab data can be easily accessed by anyone within the enterprise using desktop, mobile and web applications. Perhaps most importantly, automated smart laboratories reduce the time employees waste on routine tasks, freeing up human capital for more valuable and productive work.