Reproducibility is another important parameter for evaluating the quality of
a biosensor, but the expression is often misused as testing the reproducibility
would require to measure the same concentrations on a different instrument and
by a different operator under reproducible conditions which is easiest performed
in another laboratory. What is most often measured is the repeatability, which is
defined as the variation of the signal measured of an analyte concentration in the
linear range on different time points.
In most publications about biosensor development, the calibration curve is
obtained from analyte dilution series in buffer solutions, although it would be
preferable to use spiked artificial or natural sample matrices. However, the
performance of the biosensor on a real sample has to be evaluated. Therefore,
measurements of a natural sample should be performed with the biosensor and
a reference method. If reference methods are not available, spiked natural sample
matrices may be used. The recovery is expressed in percentage.
As the last criteria, stability should be mentioned which refers to the influence
of every external change on the performance of the biosensor. Mostly, the storage
stability (also called lifetime) is the most important external influence. To examine
a biosensor’s lifetime, a batch of biosensors should be produced and used after
different storage times, while the change of the response signal under identical
conditions is stated in percentage.
In conclusion, a thorough characterization of a biosensor is extensive, and
a publication including all criteria is seldom. What has already become established
among publications is the indication of linear range and detection limit of a
biosensor, presumably caused by the pursuit for single-molecule detection.
But most of the published detection limits fulfill the requirements for analytical
diagnostics, but lack real sample validation. Thus, especially for impedimetric
aptasensor, it would be desirable to present the calibration curve from measurements
in spiked natural or artificial sample matrices and perform validation with natural
samples. Besides, normalization of the response to biosensor-specific characteristics
like electrode area, number of recognition elements, and blank signals would be
helpful for proper comparison of different impedimetric aptasensors.
5 Summary and Outlook
Most publications on impedimetric aptasensors are based on the sequential
measurement of frequencies in a small range with measurement times of 1–3 min.
As most biological systems are changing over time, more applications using multisine
and potential step techniques are needed to avoid errors of non-stationarity and enable
kinetic measurements.
To increase sensitivity and reduce non-specific binding, a special design of the
electrode surface is needed. DNA origami and nanocomposites are promising
tools for application-specific surface designs. However, the aim should be to keep
it as simple as possible to enable thorough characterization of the surface and
36
P. Reich et al.
a biosensor, but the expression is often misused as testing the reproducibility
would require to measure the same concentrations on a different instrument and
by a different operator under reproducible conditions which is easiest performed
in another laboratory. What is most often measured is the repeatability, which is
defined as the variation of the signal measured of an analyte concentration in the
linear range on different time points.
In most publications about biosensor development, the calibration curve is
obtained from analyte dilution series in buffer solutions, although it would be
preferable to use spiked artificial or natural sample matrices. However, the
performance of the biosensor on a real sample has to be evaluated. Therefore,
measurements of a natural sample should be performed with the biosensor and
a reference method. If reference methods are not available, spiked natural sample
matrices may be used. The recovery is expressed in percentage.
As the last criteria, stability should be mentioned which refers to the influence
of every external change on the performance of the biosensor. Mostly, the storage
stability (also called lifetime) is the most important external influence. To examine
a biosensor’s lifetime, a batch of biosensors should be produced and used after
different storage times, while the change of the response signal under identical
conditions is stated in percentage.
In conclusion, a thorough characterization of a biosensor is extensive, and
a publication including all criteria is seldom. What has already become established
among publications is the indication of linear range and detection limit of a
biosensor, presumably caused by the pursuit for single-molecule detection.
But most of the published detection limits fulfill the requirements for analytical
diagnostics, but lack real sample validation. Thus, especially for impedimetric
aptasensor, it would be desirable to present the calibration curve from measurements
in spiked natural or artificial sample matrices and perform validation with natural
samples. Besides, normalization of the response to biosensor-specific characteristics
like electrode area, number of recognition elements, and blank signals would be
helpful for proper comparison of different impedimetric aptasensors.
5 Summary and Outlook
Most publications on impedimetric aptasensors are based on the sequential
measurement of frequencies in a small range with measurement times of 1–3 min.
As most biological systems are changing over time, more applications using multisine
and potential step techniques are needed to avoid errors of non-stationarity and enable
kinetic measurements.
To increase sensitivity and reduce non-specific binding, a special design of the
electrode surface is needed. DNA origami and nanocomposites are promising
tools for application-specific surface designs. However, the aim should be to keep
it as simple as possible to enable thorough characterization of the surface and
36
P. Reich et al.