Drug discovery uses the major amount of its resources for the high throughput screening. Based on specific probabilistic calculation, large experiments in HTS are performed by pharmaceutical and biotech companies to identify some molecules that could become drug after further long analyses.

Robots are usually used in this complex process. It’s important that all data are generated in reliable and accurate manner in order to obtain useful results. Robots can execute some passages: from serial dilution to reaction buffer disposal. In each of these steps, errors could be generated and, giving the small volumes in which HTS is usually performed, robots must be well calibrated in order to exclude the possibility to have this kind of problems. A lot of data arises from an HTS. Data management and statistical analyses are other key- steps for the high throughput screening. Thus, IT systems have not only to control robots to correctly work, but also help scientists to produce meaningful results from raw data. This kind of experiments are highly expensive and can be repeated only strictly necessary times. However, it’s really important to plan the experiment in the correct way and set up robot ant other IT systems involved into the process to obtain more data as possible.