How are you currently managing your samples? How are you scaling up in the next 2–5 years? Do you have a digital sample management strategy yet?
Traditionally, secure sample identification and traceability, as well as assuring that the freezer is working properly, have been challenging. Vials were often labeled with a marker and put into a box in the ULT, and the location was perhaps written on a paper list taped to the door. The sample origin and some sample data were typically recorded—in ink—in somebody’s notebook. The system for monitoring the health and temperature of the -80 freezer likely consisted of a thermometer attached to an audible alarm.
However, the storage and management of biological samples have evolved. There are now efficient, interconnected, end-to-end solutions—from reliable and trackable sample identification to remote monitoring systems and cloud-based laboratory notebooks and sample management software where data are stored, tracked, and retrieved.
Ultra-low temperature (ULT, often called “minus-80”) freezers are an essential part of biomedical laboratories and biobanks, housing the most important assets in the laboratory. At any given time, there may be thousands of precious samples in a freezer, in boxes arrayed in racks on shelves behind heavily insulated doors.
ULT freezers don’t take a break like most other lab equipment—they are always plugged in, turned on, and in use maintaining the sample’s integrity. Doing so consumes a lot of energy.
Labs are demanding that their ULT freezers are not only robust and reliable to preserve their precious samples, but also as cost-efficient and “green” as is feasible. And manufacturers are meeting the demand: Eppendorf’s new CryoCube line, for example, boasts up to 29% energy savings compared to the previous generation of comparable-capacity ULT freezers. Door openings, internal temperature, alerts, and maintenance reminders, along with a host of other use and functionality parameters can be tracked and logged with the remote monitoring software VisioNize Lab Suite.
Non-readable sample labels or even non-labeled tubes are a risk to reliable science. Many experiments need to be repeated or fail to be repeated due to issues with sample identification. Manual writing and even barcode stickers can be generated by the user and used to identify samples. Yet these run the risk of coming off and getting lost, rendering that sample useless.
A quick trip to the supermarket or looking at conference ID badges leaves no doubt about the utility of one- and two-dimensional barcodes.
Barcoding provides an easy way for a given sample to be uniquely identified and ultimately tracked. These codes can store a wide range of information with only a scanner and associated database necessary to retrieve it. Sample content, source, concentration, volume, or even patient ID or protocol can be stored and accessed from anywhere via compliant software and a secure data portal.
While keeping track of biological samples with a pen and paper list on the freezer door or in an Excel file can be fast and convenient, it has many drawbacks. Among these are that it becomes more cumbersome to keep track as more samples are added, and that the data is available only on-site and is not searchable. Most importantly, this method also affords no traceability, compliance, or audit capabilities.
A better option is dedicated professional cloud-based sample management software such as eLabInventory that builds on the functionality of a database management system. Such software can keep track of an entire lab’s sample inventory and allow for secure sharing among authorized users.
Sample management databases can also be integrated with electronic laboratory notebooks, such as eLabJournal, for a complete digital solution, ensuring that your data is secure and that your results are reliable. Knowing that your samples are protected means more time for your research.
An efficient, scalable, and auditable sample management digital strategy must provide confidence at every step: securing, storing, tracking, and monitoring all samples. Each element of the solution must work seamlessly together to ensure that your data is secure and that your results are reliable.