Biological mechanisms provide a link between anti cancer compounds and therapy responses. Insight to biological mechanisms is central for tomorrow’s clinical decision support systems and personalised cancer therapy. I will present the NTNU DrugLogics software that combines cancer signalling prior knowledge and data measurements to provide models that can predict therapy responses. We combine in silico-generated predictions with in vitro observations in the PRESORT project where patient-derived cancer cultures are subjected to drugs and drug combinations predicted for the given patient, to appreciate the efficacy for individual patients. Together with Institut Curie, Charité, BSC, Uppsala University and ProtAtOnce, we test integrated computational and experimental pipelines on historic cohorts of patients treated at the molecular tumour boards at Institut Curie and Charité. Current precision medicine trials, including the nation-wide trial IMPRESS-Norway, typically rely on individual and static biomarkers like DNA mutations for prediction of drug responses. For future iterations of clinical decision support, computer simulations taking in a number of data points and analyzed together, combined with validation in patient-derived tumour samples, will be paramount.

About the speaker

Dr. Åsmund Flobak works in clinical oncology and research at the St Olavs University hospital and at the Norwegian University of Science and Technology. He is Project leader for the ERA PerMed project OncoLogics and for the RCN project PRESORT.
His work combines both experiments in the wet-lab (cell lines, drug screening, xenograft experiments), and in the dry-lab (building logical models for drug combination response prediction, development of a pipeline in Java for drug synergy studies).
Dr. Flobak is the lead developer of the DrugLogics pipeline for drug synergy and resistance predictions. The pipeline produces models tailored to single samples for drug synergy simulation and prediction.

Who is this course for?

This webinar is part of PerMedCoE webinar series and is open for anyone interested in simulation of metabolic models, in applications of single cell and machine learning technologies, and in PerMedCoE tools and activities. The goal of PerMedCoE is to provide an efficient and sustainable entry point to the HPC/Exascale-upgraded methodology to translate omics analyses into actionable models of cellular functions of medical relevance. No prior knowledge is required.

Outcomes

By the end of this webinar, you will be able to:

• Describe how DrugLogics can predict cancer therapy responses

This webinar took place on 01 June 2022. Please click the 'Watch video' button to view the recording