Most modern glucose strips for diabetic run an amperometric test, but analyse the data using coulometry; coulometry is simply the integration of current and expressing it as charge. In this video we show how quick Djuli is at analysing data and how by changing the integration window we can affect key performance indicators such as LoD.
Zimmer Peacock has a bespoke cloud system called Djuli. Anyone can sign up for a Djuli account. It is a powerful data management system primarily designed for analyzing electrochemical data. In our labs, we have gathered high-quality data through amperometry at various concentrations, including zero millimolar, 10 millimolar, 20 millimolar, and 50 millimolar. Our team at ZP has also conducted experiments at multiple concentrations, providing a significant amount of data.
Although this data may not be perfect, it serves to illustrate an important point about how Djuli can be used to analyze data in different ways. By accessing the “Tools” section, we can analyze the data using different methods. For instance, we have an “amperometric data” option, which generates an ad3 tab. In this analysis, we focus on the peak area under the curve. The settings indicate a central time spot of 120 seconds, with a range of 240 seconds to 0. Similarly, ad1 has a central point at 25 seconds, ranging from 0 to 50, and ad2 has a central point at 180 seconds, ranging from 280 to 80 seconds. These tabs allow us to examine the integration or area under the curve at different time intervals while using the same dataset.
The key advantage of Djuli is that it provides key performance indicators (KPIs) and statistical analysis of the data. By integrating the curve from approximately 0 to 40 seconds, we can determine that the limit of detection is 19. Although the linearity of the data may not be ideal, focusing on the entire curve gives a sense of its overall quality. Narrowing the focus to the first 50 seconds reveals a limit of detection of approximately 78.8, still disregarding the linearity. Finally, examining the segment centered around 180 seconds shows a limit of detection of 5. This demonstrates that by adjusting the integration window, we can impact the limit of detection. Djuli automates this analysis, making it a quick and convenient process.
Moreover, Djuli allows for the conversion of amperometric data into coulometric data, providing additional analytical capabilities.