How to Mitigate Assay Variability with an Eye Toward Automation

The liquid handling component of assay variability is often underappreciated yet can have a significant impact on data quality. Many laboratories rely on precision alone to assess and mitigate assay variability. However, both the accuracy and precision of the liquid handler need to be measured in order to reduce overall assay variability. To improve data quality even further, the same technology can be applied to study the assay workflow, ensuring successful assay transfer and saving time, money and resources.

In a webinar, now available on demand, William Ivory, Senior Scientist and Automation Lead at DiscernDX, and Dr. Nathaniel Hentz, Director of Scientific Market Development at Artel, present two examples illustrating how to mitigate assay variability:

• Optimization considerations for automating a binding protein assay
• Workflow optimization for a next-generation sequencing (NGS) assay

Watch this expert webinar if you want to:

• Understand the impact of and how to detect liquid handling variability on assays
• Understand the importance of studying key liquid handling parameters during the assay optimization process
• Learn how to improve an assay workflow by studying the assay process
• Learn the importance of ensuring the performance of your liquid handlers during an assay transfer

Think you could benefit from this webinar, but missed it? You can now watch it on demand at a time that suits you and find some highlights from the Q&A session below.

Q: Of the sources of variability you discussed, which ones should I focus on during assay development?
NH: I think there are a lot of different sources of variability to consider, but you have got to really think about the impact on the assay. What I would suggest is take a holistic approach. For example, I wouldn’t test all these different buffers in your assay, but the particular buffer you have chosen should be studied in detail. Also, when you consider different liquid handlers, the liquid class options are going to be labelled slightly differently and these may have different impacts on a particular assay. So those are things that definitely have to be studied during assay optimization.

Q: What are some of the shortfalls of using default liquid classes?
WI: I think the default liquid class settings are a great place to start to check the performance of your assay. However, if you are dealing with fluids that have different properties, you really need to get in there and tweak your liquid class settings. A lot of these settings are adjusting for things like the aspirate/dispense rate and the speed of withdraw of the tip from the solution. So, there are several different considerations and the fluids are always going to have a different impact, depending on the tip types versus all these different settings. Take advantage of the default settings as a starting point; if they work, great, if they don’t then make some adjustments. The main thing I would suggest is to always check!

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