Continuous Biosensor\nBased on Particle Motion: How\nDoes the Concentration Measurement Precision Depend on Time Scale?

Continuous biosensors measure concentration–time\nprofiles\nof biomolecular substances in order to allow for comparisons of measurement\ndata over long periods of time. To make meaningful comparisons of\ntime-dependent data, it is essential to understand how measurement\nimprecision depends on the time interval between two evaluation points,\nas the applicable imprecision determines the significance of measured\nconcentration differences. Here, we define a set of measurement imprecisions\nthat relate to different sources of variation and different time scales,\nranging from minutes to weeks, and study these using statistical analyses\nof measurement data. The methodology is exemplified for Biosensing\nby Particle Motion (BPM), a continuous, affinity-based sensing technology\nwith single-particle and single-molecule resolution. The studied BPM\nsensor measures specific small molecules (glycoalkaloids) in an industrial\nfood matrix (potato fruit juice). Measurements were performed over\nseveral months at two different locations, on nearly 50 sensor cartridges\nwith in total more than 1000 fluid injections. Statistical analyses\nof the measured signals and concentrations show that the relative\nresiduals are normally distributed, allowing extraction and comparisons\nof the proposed imprecision parameters. The results indicate that\nsensor noise is the most important source of variation followed by\nsample pretreatment. Variations caused by fluidic transport, changes\nof the sensor during use (drift), and variations due to different\nsensor cartridges and cartridge replacements appear to be small. The\nimprecision due to sensor noise is recorded over few-minute time scales\nand is attributed to stochastic fluctuations of the single-molecule\nmeasurement principle, false-positive signals in the signal processing,\nand nonspecific interactions. The developed methodology elucidates\nboth time-dependent and time-independent factors in the measurement\nimprecision, providing essential knowledge for interpreting concentration–time\nprofiles as well as for further development of continuous biosensing\ntechnologies.