High-throughput phenotypic screening, based on high content imaging, is increasingly often used as a tool in the context of drug discovery. Compound screens are used to find hits that produce the desired phenotypes in relevant cellular assays. Genomic screens are used to elucidate the underlying molecular pathways and identify suitable drug targets. Since a wealth of data is produced in the process of high- content screening, data science approaches such as statistics, machine learning and neural networks can play an important role in making the most of the collected data. Much like virtual screening can be performed in more classical chemoinformatic settings by, e.g., learning predictive models for QSAR (quantitative structure-activity relations) from data obtained through compound screens, similar approaches can be taken in the context of high-throughput phenotypic screening.

The ICGEB-TRAIN event will bring together a diverse group of experts covering the different topics of high-content screening, image analysis, chemoinformatics and machine learning. This will allow graduate students, as well as researchers from academia and industry, to familiarize themselves with these highly modern and important topics.

This will be the first event of its kind on this set of hot topics in the region of Slovenia and Friuli-Venezia- Giulia. There is ample potential audience in the region, both in terms of graduate students and researchers from academia and industry. The event will have an impact both on the academic and industrial sector in the region, as there are many biotech companies, both large and small, in the region. The INTERREG V-A Italy-Slovenia 2014-2020 project TRAIN (Big Data and Disease Models: A Cross- border Platform for Validated Biotech Industry Kits) brings together some of the academic and industrial players from the region and demonstrates interest in the topic.