Research Interests
Our research is focused on advancing drug discovery and chemical safety assessment through the integration of computational modeling, artificial intelligence, and experimental pharmacology. We develop algorithms, predictive models, and automated laboratory systems that connect in silico predictions with in vitro experimentation, aiming to create data-driven and autonomous workflows for pharmaceutical research. Our long-term vision is to contribute to the development of virtual cells—computational models capable of simulating cellular behavior—and self-driving laboratories that can design, execute, and learn from experiments autonomously. Our work spans applications in precision medicine, environmental toxicology, and drug combination prediction, and we collaborate closely with academic, clinical, and industrial partners. By combining expertise in bioinformatics, machine learning, and laboratory automation, we strive to accelerate scientific discovery and improve decision-making in modern pharmacological research.
Group members
Jordi Carreras-Puigvert
Maris Lapins
Christa Ringers
Wesley Schaal
Jonathan Alvarsson
Malin Jarvius
Martin M Johansson
Anders Larsson
Ahmet Yildirim
Stefan Maak
Petter Byström
Patrick Hennig
Amelie Wenz
David Holmberg
Ebba Bergman
Jonne Rietdijk
Sofía Hernández
Taka Ariyaberg
Dinh Long
Ernst Ahlberg
Ulf Norinder
Filip Miljkovic