People

I did a PhD in Pharmaceutical Chemistry at the University of Vienna concentrating on QSAR and similarity-based descriptors with a focus on the multidrug efflux pump P-glycoprotein (supervisor: Gerhard F. Ecker). During this time I was lucky to spend some fantastic months in Barcelona to explore the work on similarity further together with Jordi Mestres. Later on, I moved to the lab of Hans-Dieter Höltje at the Heinrich-Heine University in Düsseldorf in order to conduct my first postdoctoral studies. These were mainly structure-based, with a focus on molecular dynamics simulations for the exploration of novel therapies for actinic keratosis based on the target DNA Polymerase alpha. Later I was recruited back to the University of Vienna, where I further applied all my skills in computational molecular design, especially in the framework of the FWF-funded special research focus SFB35 (“Transmembrane Transporters in Health and Disease”) . I was also involved in the projects Open PHACTS and eTOX which was quite inspiring since it allowed me to step into the worlds of large data integration and in silico toxicology predictions. During 2012-2016, most of my papers dealt with data integration and data annotation, including biomedical ontologies. I discovered that Open PHACTS and ChEMBL are great data sources and further used them for machine learning applications and predictive toxicology. In 2016, I also started to explore data that is incorporated in the corpus of Medicinal Chemistry literature in a time-wise manner. Together with Rajarshi Guha we recently published a paper on time-trends in scaffold popularity in the Journal of Medicinal Chemistry which also made it to Derek Lowe’s blog. Trying to unit all my skills in data science and computational molecular design, I am since 2017 leading a research group at the Department of Pharmaceutical Chemistry in Vienna. My current FWF project “Elucidating hepatic OATP ligand interactions and selectivity”, allows me to apply both ligand- and structure based modelling techniques, as well as integrative data mining. Experimental validation in this project is done by Gergely Szakacs (Medical University of Vienna) and Csilla Ozvegy-Laczka (Hungarian Academy of Sciences). I am also involved in the H2020 project EU-ToxRisk where I am currently applying machine learning techniques for in silico toxicology predictions and leading a task force on read across tool development.

Danilo Đokić is a student in the program “Drug Discovery and Development” at the University of Vienna. Since March 2020, he is working on his Master’s thesis performing Data Science approaches to study the current COVID-19 pandemics (by also making comparisons to SARS-CoV and MERS-CoV). Danilo obtained his  MSc  in Pharmacy  in  January  2018,  at the Department of Pharmacy,  Faculty  of  Medicine, University of Niš. His research work focused on the consequences of anticancer therapy on cognitive functions in patients with malignant tumor and resulted in the Master’s thesis on the topic: Effects of Chemotherapy and Hormone Therapy on the Cognitive Function in Cancer Patients: Potential Risks. The interests in immunology and pharmacology led Danilo to the internship at the Bandung Institute of Technology in Indonesia during August 2017 where he worked on the project of the immunomodulatory effect of the extract from Marchantia Paleacea. During the summer semester 2019 at the University of Vienna, he was a part of a team that was working on the case study related to development of the Novel STS Inhibitor for the treatment of breast cancer.