Fitting the experimental results is not always easy. Apparently, there are deviations between the actual measured data and the model applied to the data. Visual inspection of the fitted curve will immediately show that something is wrong.

Discrepancies between data and fitting can have many origins:

• the system used is not working properly
• the experimental conditions were ill choosen
• the ligand or analyte are not what is expected
• the applied model is wrong

It is clear that only the best data will be obtained by the best system used, the best experimental conditions and the best defined interactants. This section will discuss the possible origins of and the solution to minimize disturbances in the sensorgrams.