- Principal Investigator
- Independent Junior Research Group Leader
Sven Marcel Stefan is the Principal Investigator and Leader of the Medicinal Chemistry and Systems Polypharmacology Group at the Lübecker Institute of Experimental Dermatology (LIED), University of Lübeck (UzL) and University Medical Center Schleswig-Holstein (UKSH). He is also University Professor at the Medical University of Lublin, Poland, and leader of two large collaborative networks, PANABC (www.panabc.info) and PANSLC (www.panslc.info).
He is a pharmacist by training and focused in his Master’s (2011–2012) and Doctoral Studies (2012–2017) in Pharmaceutical Biology and Pharmaceutical Chemistry the extraction, isolation, and structural characterization of natural compounds as well as the organic synthesis of bioactive agents and structure-activity relationships. He conducted his postdoctoral research and teaching at the Universities of Bonn (2017 – 2019), Sydney (2019–2020), and Oslo (2020–2023) focusing on bioinformatics, structural biology, and novel drug discovery approaches. Since 2022, he is co-leader of the PANABC and PANSLC consortia.
Dr. Stefan is a pioneer in the area of ‘Medicinal Polypharmacology’ focusing on mapping of polypharmacological landscapes and complex bioactivity networks of multitarget agents. The differentiation between selectivity and promiscuity and the elucidation of structure-activity relationships is a major focus of his research group. The development of innovative pattern-based computational models for virtual screening approaches to discover bioactive polypharmacological agents is emphasized. These agents are used for the exploration and potential exploitation of under-studied drug targets, particularly ATP-binding cassette (ABC) and solute carrier (SLC) transporters associated with malignant, metabolic, or neurological diseases. The group has extensive expertise in the functional assessment of drug transporters and high-throughput screenings (HTS) of large physical compound libraries, as well as in hit-to-lead optimization via organic synthesis.