DrugLogics Systems Medicine Group
The DrugLogics group has members from the Department of Biology and the Department of Clinical and Molecular Medicine from NTNU. In collaboration with the Computational Systems Biology group at IBENS-ENS, we develop logical modeling approaches and cell specific logical models to aid in the analysis of drug synergies and other perturbation results in cancer and inflammatory diseases. Our main focus is to produce software tools and models to help in biological data analysis and network-based systems modeling (https://github.com/druglogics), as well as data that allows us to benchmark our tools and models (Flobak et al. 2019, Folkesson et al. 2020). Our model collection includes the CASCADE family (general cancer and colon cancer models), a macrophage/inflammation model and a psoriatic keratinocyte model.
The group is involved in the PRESORT project to test drug synergy prediction for colorectal cancer, the ONCOLOGICS ERA PerMed project, and the COVID-19 Disease Maps Consortium.
In the Norwegian Research Council-funded PRESORT project we aim to mature, tailor, benchmark and roll out a clinical decision support platform for prediction and validation of anti-cancer effects of drug therapies. The platform is based on our DrugLogics software pipeline using logical model ensembles and data from in vitro screening of cancer cell lines and ex vivo patient-derived spheroid cultures. The platform should become applicable for pharmaceutical industry and pre-clinical research, aiming to be a foundation for clinical decision support, by providing improved drug development and more effective design of clinical trials. Complementary approaches are pursued in the ERA PerMed project ONCOLOGICS, in an international setting with participants from Curie Institute, France; Charité, Berlin; Barcelona Supercomputing Center, Spain; Uppsala University, Sweden; and ProtAtOnce, Greece.
In the area of inflammation-based diseases we study the role of Macrophages in the onset of inflammation, and our macrophage model has been customised to represent major events related to COVID-19 infection (in the COVID-19 Disease Maps Consortium). We also study the inflammatory cues that underlie psoriatic keratinocytes, in our efforts to in silico test the effect of targeted drugs and drug combinations.