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Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling Kostas Marias, Foundation for Research and TechnologyHellas, Greece Stelios Sfakianakis, Foundation for Research and Technology-Hellas, Greece Aims of this talk • Discuss the clinical relevance of predictive oncology and in particular computational models. • Discuss their role in assisting the clinician in disease diagnosis and therapy decision making. • Introduce CRAF as an end result of CHIC project 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 2 Is progress in cancer clinical trial slowed down? • Increasing regulatory rigidity of clinical trials • More complexity • More bureaucracy • Increasing costs • Time from drug discovery to marketing • 8 years in 1960 12 - 15 years in 2002 • Costs per life year gained: $2.700.000 Stewart DJ et al.: Equipoise Lost: Ethics, Costs, and the regulation of Cancer Clinical Research. J Clin Oncol 17:2925-2935, 2010 Prof. Norbert Graf Kick-off Meeting p-medicine (270089) - February 14-15, 2011 - Homburg/Saar 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 3 Is progress in cancer clinical trial slowed down? Without improved mathematical and computer modeling (stochastic, Markov process modeling among others) we will fall short of progress! 100 % Cure rate Stephen M. Pribut, Professor of Surgery, George Washington University School of Medicine 0% 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling timeline 4 Medicine is expanding • Preventive • Predictive • Personalized • Participative • Psycho-cognitive 12/8/2016 In Silico Modeling provides opportunities “Through modeling, researchers can now predict the behavior of some of the toughest cancers” http://www.nature.com/nature/journal/v491/n7425_supp/full/491S66a.html 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 6 What about populations and clinical trials? “Mathematical modelling is also helping to speed up the clinical trials that test those drugs. Testing all the possible permutations of drugs and doses to determine the best course of therapy might take millions of clinical trials — and there are nowhere near enough patients or resources for that” http://www.nature.com/nature/journal/v491/n7425_supp/full/491S66a.html In the period 2008-2011, the Office of Clinical Pharmacology at the US Food and Drug Administration (FDA) received up to 25 submissions containing in silico clinical trials (through PBPK analyses) Zhao, P., L. Zhang, J. A. Grillo, Q. Liu, J. M. Bullock, Y. J. Moon, P. Song, S. S. Brar, R. Madabushi, T. C. Wu, B. P. Booth, N. A. Rahman, K. S. Reynolds, E. Gil Berglund, L. J. Lesko and S. M. Huang (2011). "Applications of physiologically based pharmacokinetic (PBPK) modeling and simulation during regulatory review." Clin Pharmacol Ther 89(2): 259-67. 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 7 The EC Virtual Physiological Human effort Virtual • Sophisticated computer models; usually complex workflows Physiological • • Function of living systems Biology, biochemistry, biophysics… Human • • Focus is human healthcare, ‘business’ is medicine …the modelling process is relevant to other species, disciplines Initiative with significant funding from the EC Community of over 2000 European researchers Purpose: To improve diagnosis/treatment by physics simulations 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 8 VPH Integration strategy Spatial 1m… 1mm… 1ns… …1s… 1m… 1nm… Temporal …70 years Organs & Systems http://bodybrowser.googlelabs.com 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 9 Microscopic to Macroscopic cancer modelling strategies Organ ECOSYSTEM LEVEL Treatment planning POPULATION LEVEL ORGANISM LEVEL Tissue Top-down Bottom -up Cell SYSTEM LEVEL ORGAN LEVEL TISSUE LEVEL CELLULAR LEVEL Molecules SUBCELLULAR LEVEL MOLECULAR LEVEL Drugs research ATOMIC LEVEL G.Stamatakos "In Silico Oncology Part I: Clinically Oriented Cancer Multilevel Modeling Based on Discrete Event Simulation" In T.Deisboeck and G. Stamatakos Eds 407-436 2011-01-01 CRC Press, Print ISBN: 978-1-4398-1440-6 eBook ISBN: 978-1-4398-1442-0 DOI: 10.1201/b10407-19 Boca Raton, Florida, USA, 2010 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 10 What about predictions? In Silico Predictive models Predict the optimal treatment/ therapy outcome 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 11 ContraCancrum project Clinical Workflows http://contracancrum.eu/ Schema of the Glioblastoma workflow Schematic for New GBM Sensitivity Evaluation based on TCGA glioblastoma subtypes. Subtype sensitivity was independently validated by Ducray et al. 2010. This was applied to classify the repository of ContraCancrum patients where microarray data was available. G.S.Stamatakos, In Silico Oncology Group Leader, ICCS-NTUA 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 12 Novel approach in multiscale Predictive Oncology Clinical Decision Support Multi-scale predictive oncology start Molecular level models Drug-binding evaluation Drug-sensitivity evaluation Informs on drug ranking Informs on patient sensitivity molecular data clinical data Tissue level models treatment data Oncosimulator imaging data Clinical Decision Support Layer Prediction: Is treatment ( i ) beneficial? Simulate ( i+1) line treatment no yes Predictive Oncology Optimization Layer Optimize modeling components no Is response to treatment as predicted? yes Predictive Oncology Decision Confirmed The envisaged use of CC environment, introducing a new paradigm in designing multi-scale predictive oncology clinical decision support protocols http://contracancrum.eu/ 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 13 What about validation of cancer models? Tumor change Tumor is in fact regressing! Tumor must be shrinking! Diagnosis and start of treatment MRI Follow up MRI time Illustrating the difficulties in validating predictive models with limited time points (which is normally the case in the clinical setting). This limitation was discussed-introduced by Norbert Graf, Director of Pediatric oncology at the University of Saarland. 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 14 What about validation of cancer models? • If it is to be used in clinical practice In silico modelling should be validated so as to prove the clinical relevance • The use of animal models (mice) is an attractive alternative for conducting initial validation experiments of models • Validation using retrospective hospital data is very difficult (if not impossible) mainly due to the lack of temporal cancer data needed to test the accuracy of the model predictions • CHIC project developed a dedicated environment for demonstrating the clinical relevance of multiscale cancer modeling. Employing in-vivo Molecular Imaging in Simulating and Validating Tumor Growth Eleftheria Tzamali, Rosy Favicchio, Alexandros Roniotis, Georgios Tzedakis, Giorgos Grekas, Jorge Ripoll, Kostas Marias, Giannis Zacharakis, and Vangelis Sakkalis , IEEE EMBC 2013. 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 15 Evolution of cancer modelling projects-priorities Development of cancer models and proof of concept 12/8/2016 Demonstration of the Clinically-driven cancer modelling applications and clinical relevance of cancer international collaboration hyper-modelling Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 16 The CHIC Clinical Research Application Framework • Computational modelling can play a pivotal role in the translation of research to clinical practice. • It can link patient related data and biological and disease specific information to provide key insights for the benefit of cancer patients. • The “Clinical Research Application Framework” (CRAF) of the CHIC Project provides the bridging between the Computational Modelling Research and the Clinical practice. 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 17 The CHIC Clinical Research Application Framework • CRAF is the entrance to the CHIC platform for the clinicians • Effectively hiding the complexity of the platform • Allowing the clinical users to take advantage of the CHIC outcomes • A comprehensive suite of technical components that bridge the gap between the computational work in CHIC and the delivery of care and research in the clinical setting. 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 18 The CHIC Clinical Research Application Framework High Level view Model Building & Experimentation Model Repository Hyper modelling Editor Model Execution Computational Modeller Model Model Model CHIC Research Domain Model Patient Specific Data Clinical Practice CRAF Answer Clinical Domain 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling Clinician 19 The CHIC Clinical Research Application Framework Conceptual model • We consider 3 dimensions when a Clinician interacts with CRAF: • Models: the computational and simulation artefacts of the CHIC research platform • Data: patient specific information coming from the clinical domain • ”Hypotheses”: Clinical questions to be answered by concrete models for a given patient 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 20 The CHIC Clinical Research Application Framework Login • Required for authorizing patient data access to the users 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 21 The CHIC Clinical Research Application Framework Welcome page • Select a type of Cancer or a specific patient 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 22 The CHIC Clinical Research Application Framework Selection of Cancer Type • Depending on the availability of Models, a few select cancer types are shown: 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 23 The CHIC Clinical Research Application Framework Selecting a Clinical Question • A Clinical Question correspond to a specific hypothesis or treatment plan the Clinician may present • Example: the efficacy of pre-operative chemotherapy for a given patient 12/8/2016 24 The CHIC Clinical Research Application Framework Select a Patient • Shows the list of Patients that the Clinician has access to • For each patient, the set of available data are also shown 12/8/2016 26 The CHIC Clinical Research Application Framework Selection of the Model to run • The selection of Clinical Question and/or the Patient specifies the set of applicable models: 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 27 The CHIC Clinical Research Application Framework Set the Input parameters • Patient data are automatically set • Some parameters, e.g. the drug administration plan, can be specified by the user 12/8/2016 28 The CHIC Clinical Research Application Framework Monitor execution progress • The currently running models as well as the previous executions are shown in the History page: 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 29 The CHIC Clinical Research Application Framework Results • When the run completes, full details of the execution are shown: 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 30 The CHIC Clinical Research Application Framework Report generation • A PDF report, to be put in the clinical record of the patient, is produced: • Contains all the details, graphs, inputs, and outputs of the execution 12/8/2016 Integrating CHIC technologies into a clinical research application framework (“CRAF”) for cancer modeling 31