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Abstract
A major issue in oncology is the high failure rate of translating preclinical results in successful clinical trials. Using a virtual clinical trial simulations approach, we present a mathematical framework to estimate the added value of combinatorial treatments in ovarian cancer. This approach was applied to identify effective targeted therapies that can be combined with the platinum-taxane regimen and overcome platinum resistance in high-grade serous ovarian cancer. We modeled and evaluated the effectiveness of three drugs that target the main platinum resistance mechanisms, which have shown promising efficacy in vitro, in vivo, and early clinical trials. Our results show that drugs resensitizing chemoresistant cells are superior to those aimed at triggering apoptosis or increasing the bioavailability of platinum. Our results further show that the benefit of using biomarker stratification in clinical trials is dependent on the efficacy of the drug and tumor composition. The mathematical framework presented herein is suitable for systematically testing various drug combinations and clinical trial designs in solid cancers.
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1 University of Helsinki, Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, Helsinki, Finland (GRID:grid.7737.4) (ISNI:0000 0004 0410 2071); Silesian University of Technology, Institute of Automatic Control, Gliwice, Poland (GRID:grid.6979.1) (ISNI:0000 0001 2335 3149)
2 Turku University Hospital, University of Turku, Department of Oncology and Radiotherapy, Turku, Finland (GRID:grid.6979.1)
3 Turku University Hospital, University of Turku, Department of Obstetrics and Gynecology, Turku, Finland (GRID:grid.6979.1)
4 University of Helsinki, Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, Helsinki, Finland (GRID:grid.7737.4) (ISNI:0000 0004 0410 2071); Harvard Medical School, Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Helsinki University Hospital, Department of Obstetrics and Gynecology, Helsinki, Finland (GRID:grid.15485.3d) (ISNI:0000 0000 9950 5666)
5 University of Helsinki, Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, Helsinki, Finland (GRID:grid.7737.4) (ISNI:0000 0004 0410 2071)