How can automation overcome sample degradation in biobanking?

12/08/2020

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Biobank research is essential for advancing our knowledge of the genetic make-up of diseases and supports a future of more powerful, personalized medicine.  However, biobank research faces many challenges, including weak process links that threaten the integrity of samples and the overall robustness of the research effort. In a recent blog, we tackled some of the unwitting ways that researchers could be degrading their samples through traditional biobank processes. 

Frozen tubesThese weaknesses include the variable length of time between sample post-processing to storage, the false sense of security instilled by transporting samples on dry ice, and variable freezing profiles of samples stored in racks in the freezer. The impact of these process issues could be severe, especially for protein-based samples for which there is no readily available quality control assessment. In short, degraded samples could make their way into research without the quality issues ever being detected. It is therefore essential that we use all available methods to iron out these process glitches.  

Happily, automation has the potential to resolve many of these difficulties for biobanks, minimizing errors and reducing inadvertent exposure to temperature variation. Temperature variation is, of course, one of the primary causes of sample degradation. Let's take a look at some of the ways automation practically helps to address the weak links. 

The ability to automatically transport samples 

One of the problems we outlined in our earlier blog was the temperature exposure caused by leaving samples out in batches during processing, then the transportation on dry ice to the freezer. Automatic transportation using pneumatic tube systems allows researchers to send an individual sample to the storage - preventing multiple specimens from being left out in sub-optimal conditions.  

Increased uniformity with automated storage 

Manual freezers are subject to ongoing temperature variations when researchers open and close the door to retrieve samples. This issue leads to hotspots and coldspots and subjects samples to multiple thermal shocks. A critical advantage of automated storage systems is the enhanced ability to maintain a uniform temperature throughout the unit. Improved uniformity translates to improved sample quality.  

Protect samples through automated picking

Instead of having to pick samples in full racks, automation allows researchers to easily call on individual samples. This 'cherry-picking' avoids exposing entire racks to freezing and thawing cycles. By picking one sample at a time, we are ensuring protection for the other tubes in the storage until they are needed.  

Unfortunately, the benefits of automation have often been out of reach for many biobanks due to the significant up-front capital requirements, major infrastructure changes, lengthy implementation and often painfully slow return on investment. Yet, to effect a positive impact on the long term curation of samples, we need to embrace planning, and assure consistency as well as making the most of available technology.  
  
Happily, the choice for biobanks is no longer “all or nothing” between expensive, high-investment automated units or manual freezers. Modular systems such as SPT Labtech's arktic XC empower biobanks to build up their automated capability step by step starting with standard "off the shelf" storage systems. These scalable options have an immediate effect on sample integrity by improving handling and storage. At the same time, they give biobanks the flexibility to manage budgets more effectively by allowing them to increase capacity only when needed. In today's demanding healthcare environment, adaptable systems that fit seamlessly into existing and future infrastructure are vital for enabling researchers to respond to demand swiftly while ensuring quality. 

To learn more about sample integrity download our latest whitepaper 'Garbage in garbage out! Are your samples fit for purpose?' which explores how to reduce bias and improve the reliability of analytical results by ensuring sample quality is not compromised at any stage of the sample management process.