Mission Statement

Following a holistic pharmacoinformatic approach we combine structural modeling of proteins, structure-based drug design, chemometric and in silico chemogenomic methods, statistical modeling and machine learning approaches to develop predictive computational tools for drug discovery and development. Hereby, the main focus of our work comprise interaction of ligands with transmembrane transport proteins and prediction of toxicity. The validation and optimisation of the obtained in silico models by strong links to experimental groups is an integral part of these activities.

Furthermore, we aim at developing tools for in vitro to in vivo translation in the area of adverse drug event prediction, thereby leveraging integrated life science data. Research activities are complemented by strong educational activities, outlined in the doctoral program MolTag and in EUROPIN, a European PhD Program in Pharmacoinformatics.

Latest News

Project
 

InSilify DrugTox is amongst the seven projects that were granted by the Austrian Science Fund FWF to enable research on different possibilities to...

News
 

We warmly welcome Sharath to the Pharminfo group! His expertise includes AI-assisted drug discovery and cheminformatics. We look forward to working...

Project
 

We are excited that our project AI4Health - Using AI for detecting drug-drug interactions - was recently granted by the Vienna Business Agency.

Publication
 

In the past years the interest in Solute Carrier Transporters (SLC) has increased due to their potential as drug targets. At the same time,...

Open Access
 

In the context of pharmaceutical research, privacy-preserving decentralized approaches are crucial since they would allow for the enrichment of...

Open Access
 

The WikiPathways database continues to grow with contributions from the community, and has become widely adopted for pathway information and...