The Internet of Things (IoT) Within The Laboratory

Getting real value out of IoT it can be viewed as a ‘perfect storm’ in the sense that it presents “a rare combination of circumstances with the potential to result in an event of unusual magnitude.” IoT can be defined as physical objects that are connected to a network to collect data, like a fitness tracker recording personal activity data.

So writes Dassault Systèmes BIOVIA in an article for Laboratory Network. Here is an extract:

“In the context of the laboratory, the direct interfacing of objects removes the need for manual data entry or transcription, which safeguards the integrity of the collected data, as well as aiding compliance with standards and regulations like 21 CFR Part 11. Efficiency is boosted through the removal of non-value-adding activity, while more data (and more complete data) of higher quality is collected, being attributable (who created a record and when), legible, contemporaneous, original and accurate.

In addition to providing a greater volume of complete data, the IoT gives an overview of processes and activity. Once analytics are applied, insight can be gained into trends or the effect of implemented changes, enabling organizations to act in a pre-emptive manner. When an organization has disconnected standalone equipment, however, it becomes difficult to obtain such an overview, especially when devices may be spread in various locations around the world. Questions can then arise as to whether each device is correctly calibrated, its maintenance status, where this information is documented, and how the data can be linked to that of the samples being tested in order to provide evidence that the instrument was in perfect working order during the time of measurement.

From a cost perspective, having detailed information regarding the location of equipment and how it is being used may reveal that instruments could be relocated, or used in a more efficient way rather than an organization needing to incur the cost of purchasing additional equipment. However, there are two key difficulties in leveraging this data; the first being that the documentation often remains in the form of paper records or Excel spreadsheets; and the second is the equipment being disconnected, making the access to data difficult.”

The full article can be read here: Lab Network

Posted by Dr. Tim Sandle