International Conference and Exhibition on Pediatric Oncology and Clinical Pediatrics August 11-13, 2016 Toronto, Canada

Biography:

Prof. Dr. Norbert Graf is Professor of Paediatrics and Director of the Clinic for Paediatric Oncology and Haematology and a Dean for students at the Faculty of Medicine of Saarland University in Germany. He is the chairman of the Renal Tumour Study Group of the International Society of Paediatric Oncology (SIOP-RTSG). He is an Associate Member of COG (Children’s Oncology Group, North America) and closely collaborating with the COG Renal Study Group. He was the coordinator of the EU funded project p-medicine and is enrolled in several other ongoing European projects. Norbert Graf has more than 25 years of experience with clinical trials.

Abstract:

Medicine is undergoing a paradigm shift from phenotyping to genotyping. This is supported by systems approaches to disease, modeling and visualization technologies, and new computational and mathematical tools. An open, modular architectural framework for tools, models and services needs to be provided to design and develop hypermodels This includes:

• to share and handle efficiently the enormous personalized data sets

• to ensure that policies for privacy, non-discrimination, and access to data, services, tools and models are implemented to maximize data protection and data security

• to enable standardization and semantic data interoperability

• to integrate models from system biology with VPH models

• to guarantee that tools, services and models are clinically driven and do enhance decision support

• to provide tools for large-scale, privacy-preserving data mining, and literature mining

• to enhance patient empowerment In addition all tools and models need to be evaluated and validated by end-users. Feedback loops to developers for continuous improvements have to be integrated. Such an innovative architecture should promote the principle of open source. All tools, models and services have to be tested in concrete advanced clinical research projects and clinical trials that target urgent topics of the medical research community. Maintenance and further developments of the framework need to be addressed. To sustain such a self-supporting infrastructure realistic use cases have to offer tangible results for end-users in their daily practice. Teaching and educational programs for end-users have to be implemented to facilitate the access to the platform and the use of tools, models and services.

Biography:

Georgios Stamatakos received the Diploma degree in electrical engineering from the National Technical University of Athens (NTUA), Greece, the M.Sc. degree in bioengineering from the University of Strathclyde, Glasgow, U.K., and the Ph.D. degree in physics from NTUA. He is a Research Professor at the Institute of Communication and Computer Systems (ICCS), NTUA. He is the Founder and Director of the In Silico Oncology and In Silico Medicine Group. Dr Stamatakos is the coordinator of the EU-US large scale integrating research project “CHIC: Computational Horizons in Cancer: Developing Meta- and Hyper-Multiscale Models and Repositories for In Silico Oncology” FP7-ICT-2011-9, (600841).

Abstract:

Developing robust, reproducible, interoperable and collaborative hyper-models of diseases and normal physiology is a sine qua non necessity if rational, coherent and comprehensive exploitation of the invaluable information hidden within human multiscale biological data is envisaged. Responding to this imperative in the context of both the broad Virtual Physiological Human (VPH) initiative and the paradigmatic cancer domain, the large scale integrating transatlantic CHIC project (http://www.chic-vph.eu/ ) develops a suite of tools, services and secure infrastructure that supports accessibility and reusability of VPH mathematical and computational hypermodels. These include a hypermodelling infrastructure consisting primarily of a hypermodelling editor and a hypermodelling execution environment, an infrastructure for semantic metadata management, a hypermodel repository, a hypermodel-driven clinical data repository, a distributed metadata repository and an in silico trial repository for the storage of executed simulation scenarios. Multiscale models and data are semantically annotated using ontological and annotating tools. An image processing and visualization toolkit, and cloud and virtualization services are also being developed. In order to ensure clinical relevance and foster clinical acceptance of hypermodelling, the whole endeavour is driven by the clinical partners of the consortium. Innovative cancer hypermodels are collaboratively developed by the consortium cancer modellers and provide the framework and the testbed for the development of the CHIC technologies. Clinical adaptation and partial clinical validation of hypermodels and hypermodel Oncosimulators are under way. Indicative strategies, algorithms, systems, results as well as the outcome of clinical adaptation and partial clinical validation of hypermodels are presented.

Biography:

Marc Stauch; Dr jur (Göttingen), MA (Oxon) gained his legal training in the UK, qualifying as a Solicitor, before lecturing law for several years at English Universities; he is co-author of a popular English law student text and materials on Medical Law and Ethics, now in its 5th edition. After moving to Germany in 2003 he wrote his doctoral thesis comparing medical malpractice law in England and Germany. As a research associate at the Institute for Legal Informatics in Hannover, a principal focus of his current work is data protection law.

Abstract:

The law should aim to support new technologies with potential for benefiting mankind, but also needs to protect relevant individual interests – especially where these are embodied in longstanding ethical principles. In the context of health law, the regulatory focus has been on avoiding harm to individual patients and research subjects; the paradox is that, if research and/or care is made harder or delayed by legal or professional ethical restrictions, patients also stand to be harmed, by being denied better treatments. Against this background, this paper assesses how the law is faring in regulating the field of health informatics, with particular reference to in silico developments in research and care, as exemplified by the EU FP7 project ‘Computational Horizons in Cancer’ (CHIC). Two main areas are addressed where (IT and medical) researches might complain the law is over-cautious, and has failed to balance risks and benefits appropriately. The first concerns restrictions on use of patient health data to evolve and validate new clinical approaches – here data protection law, particularly the EU regime, but also the rules in North America (under HIPAA and PIPEDA) is considered. The second issue concerns the onerous validation requirements to which innovative health care products, including data-driven in silico solutions, are subject prior to clinical deployment. Here it is suggested there are indeed reasons to favor a lighter regulatory approach than in relation to the licensing of traditional medical products and devices.

Biography:

Ravi Radhakrishnan is a Professor of Bioengineering, Biochemistry & Biophysics, and Chemical and Biomolecular Engineering at the University of Pennsylvania. His expertise is in chemical physics, statistical mechanics, and computational biology his laboratory is currently funded primarily by grants from US National Science Foundation, National Institutes of Health, and European Commission and focuses its research on the biophysics of single molecules and cell membranes and signaling mechanisms in cancer. Through his work, he has pioneered novel discovery platforms in in silico oncology and in silico pharmacology. Radhakrishnan and has authored over 100 articles in leading peer reviewed Journals and serves as a referee for over 50 leading journals, publishers, and federal funding agencies. He also serves as an editorial board member and associate editor for 5 journals, and also regularly serves as a Panelist and Study Section member for National Science Foundation, National Institutes of Health, and several Federal Science Foundations in the EU. Radhakrishnan is a Fellow of the American Institute of Medical and Biological Engineering.

Abstract:

We have developed a multi scale platform for predictions of the effects of mutations on oncogene activation through a combination of molecular, biophysical, and cellular models. We combine the specificity of molecular modeling with the power of network models to predict the molecular mechanisms that lead to activation of pathways. We also employ spatial and stochastic models to describe how the effects of the tumor microenvironment can lead to oncogenic signals through non-canonical pathways. We will describe the applications of these models in the clinical contexts of non-small-cell lung cancer, neuroblastoma, and hepatocellular carcinoma. This work is funded by the US National Institutes of Health and the EU.)

Biography:

Daniel Abler is currently a post-doctoral researcher at the Institute for Surgical Technology and Biomechanics at the University of Bern. He has been Marie Curie Fellow working for the European Centre for Nuclear Research and at the Particle Therapy Cancer Research Institute in Oxford. Daniel received his PhD degree from the University of Oxford in 2014, a Diploma in physics from the Friedrich-Alexander University, Germany, and followed studies at Imperial College London, UK. He has contributed to feasibility studies and research prototypes in physics and information technologies for medical applications, in particular related to cancer research.

Abstract:

Access to high-quality clinical data is a prerequisite for medical data analysis and in-silico medicine. Data drives the development of research questions, feeds computational algorithms, and provides the evidence base for validating complex disease models which form the basis for personalized simulations in the future. However, provision of uniform access to, and secondary use of, clinical treatment or study data is hampered by the data's intrinsic characteristics: its confidential nature, and its heterogeneity in terms of sources, quality and information.
The clinical data repository (CDR) has been designed to address these critical issues by providing a unique access-point to clinical data in compliance with the European medico-legal framework. CDR has been initiated as an exchange platform for medical images, but was quickly extended to other health-related data, in particular clinical treatment & follow-up, histological and genetic information. Data access is granted based on a role-based policy within a single-sign-on security framework. CDR also supports the (pseudo-)anonymization process and provides facilities for semantic annotation of data during and after the upload process, enabling semantically mediated queries for improved data discovery.
CDR has been developed by SICAS (http://www.si-cas.com) and the University of Bern (http://www.istb.unibe.ch/) with support from the EU CHIC (http://chic-vph.eu/) and Co-Me (http://co-me.ch) projects.
This presentation will outline the principal requirements and the main challenges related to the sharing of heterogeneous clinical data for research purposes, discuss properties of a generic solution, and detail implementation and application in the CHIC context.

Biography:

Kostas Marias is Principal Researcher at the Computational Biomedicine Laboratory at the Institute of Computer Science of the Foundation for Research and Technology Hellas and Head of the Computational Biomedicine Laboratory. He completed his PhD at the University College London Medical School and has previously worked at the University of Oxford and the University of Crete. He works primarily in medical image processing and modeling for personalized medicine. He is the author or co-author of more than 30 published journal papers and has presented at 80 conferences and serves on the technical program committees of a number of international conferences.

Abstract:

The CHIC project will deliver an integrated environment that will allow the creation of multi-scale cancer hyper-models from a plethora of elementary models shared by the global cancer modeling community. Due to the high complexity of the modeling work and especially its computational demands, this multi-scale modeling environment takes advantage of state of the art “cloud” technologies, which are provisioned outside the clinical setting. In order to make this a truly functional framework for accelerating the clinical translation of multi-scale cancer models a Clinical Research Application Framework (“CRAF”) has been developed to support a unified and simple user experience and provide a “CHIC-in-a-box” abstraction for the clinicians to use in clinical research performed in their premises. To this end, its user interface is designed to be simple and smooth by hiding the complexity of the CHIC platform while, at the same time, demonstrating its full potential for clinical research and empowering the clinician to use the underlying technologies for the benefit of the cancer patient. At the same time, CRAF coordinates the functionality of other CHIC components that are also highly important for the clinicians to gain access to the CHIC services, such as the Data Upload tool for uploading patient data to the CHIC cloud, and the Visualization and image processing tools (e.g. Dr-Eye). In this presentation, the CRAF will be presented with emphasis in the integration with all the necessary software components addressing the hyper-modeling composition and execution needs.

Biography:

Raushan Kurmasheva has completed her PhD at the age of 29 years at Kazakh State National University, and her postdoctoral studies at University of Arkansas for Medical Sciences and St. Jude Children’s Research Hospital. She is an Assistant Professor at the Greehey Children’s Cancer Research Institute, UTHSC San Antonio. To date, she has published 46 peer-reviewed papers in reputed journals and has been serving as an AdHoc reviewer on MCT journal.

Abstract:

Eighty-five percent of all Ewing sarcomas, the fourth most common highly malignant childhood cancer, is defined by a tumor-specific chromosomal translocation t(11;22)(q24;q12) between the EWSR1 and FLI1 genes. DNA damage induced by expression of EWSR1-FLI1 fusion gene is potentiated by PARP1 inhibition in Ewing cells, where EWSR1-FLI1 genes act in a positive feedback loop to maintain the expression of PARP1. As single agents, PARP1 inhibitors have shown promising activity in-vitro, but only modest activity in in-vivo models. In our previous work (in PPTP), we showed that low level DNA damage by temozolomide (TMZ) can be potentiated up-to 40-fold through inhibition of PARP1 by talazoparib, leading to dramatic tumor regressions in half of the Ewing sarcoma xenograft models. We are currently investigating the biochemical differences between Ewing cell lines where there is synergy in xenograft models in mice, and those where the combination is inactive; we hypothesize that resistance of Ewing sarcoma xenografts to the synergy of the drug combination is a consequence of intrinsic resistance to either or both talazoparib or TMZ. The combination talazoparib-TMZ in Ewing sarcoma xenografts is the most dramatic synergy between two drugs to be reported. Determining the mechanism(s) of resistance to combination therapy will allow potentially identify biomarkers that will allow identification of patients likely to benefit from such treatment, and spare toxicity for those unlikely to respond.

Biography:

Dr. Samaan is a Pediatric Endocrinologist at McMaster Children’s Hospital, and an Assistant Professor at the Department of Pediatrics, McMaster University. His program of research is in Translational Immunometabolism, with specific focus on childhood obesity and diabetes. This program is focused on defining the determinants of immune-metabolic crosstalk in high-risk pediatric populations, and to design interventions to manage obesity and diabetes.

Abstract:

More than 5,000 children are diagnosed annually with brain tumors in North America. Despite significant breakthroughs in tumor biology and in therapy, survivors of childhood brain tumors (SCBT) have significant comorbidities that shorten their lifespan and affect their quality of life. Survivors of childhood cancer are at risk of cardiovascular and diabetes, but this is less well studied in brain tumor survivors. The Canadian Study of the Determinants of Endometabolic health in Children (CanDECIDE) was designed to investigate the risk factors of cardiometabolic disorders in SCBT, and compare them to a non-caner control group. In recent analyses, female SCBT were found to have enhanced visceral adiposity compared to controls. The presence of a major cardiometabolic risk factor within few years post surviving a brain tumor is an important determinant of long-term outcomes in SCBT. We discuss the implications of these findings, potential explanations and future directions.

Biography:

Dr. Soad K. Al Jaouni is a Professor & Consultant of Hematology and Professor/Consultant of Pediatric Hematology/Oncology, Senior Researcher at Hematology Department, Faculty of Medicine, King Abdulaziz University Hospital (KAUH) a tertiary care medical center, King Abdulaziz University (KAU), Jeddah, Kingdom of Saudi Arabia.

Abstract:

This study was to evaluate the efficacy and safety of Saudi honey as integrative approach in prophylaxis and treatment of chemo-radiotherapy induced mucositis among pediatric cancer patients at King Abdulaziz University Hospital at King Abdulaziz University during October 2004 to October 2005. Forty patients were randomized into two groups: receiving chemo/radiotherapy with the additional Saudi honey and control group receiving treatment without the use of honey. All patients were evaluated clinically, mouth ulcers were evaluated. Cultures were done.

Biography:

Abdulqader Al-Hebshi has completed his Jordanian and Arab Board in general Pediatrics in 2010 then he did a Clinical Fellowship in Pediatric Hematology Oncology for three years from King Hussein Cancer Centre in Jordan after that he joined The Hospital For Sick Children in Toronto to do one Year Clinical Fellowship 2014-2015, Currently he is a consultant of Hematology & Oncology and the clinical supervisor of medical interns at Prince Mohammed Bin Abulaziz Hospital - National Guard Health Affairs in Saudia Arabia. He is an active member in ASPHO American Society Of Hematology & Oncology.

Abstract:

Association of osteosarcoma with certain syndromes is well known, but the incidence varies from one report to another, and from one syndrome to another, Ruthmond syndrome is the most common syndrome reported to be associated while others like Blackfan Diamond anemia and Osteogenesis imperfect are very rarely associated, and others like Osteopoikelosis are never reported to be associated with Osteosarcoma.
Our aim from this review is to report our experience and frequency of association of osteosarcoma with syndromatic features, and to try to see if these syndromes have effects in the prognosis of Osteosarcoma.

Biography:

Prof. Dr. Norbert Graf is Professor of Paediatrics and Director of the Clinic for Paediatric Oncology and Haematology and a Dean for students at the Faculty of Medicine of Saarland University in Germany. He is the chairman of the Renal Tumour Study Group of the International Society of Paediatric Oncology (SIOP-RTSG). He is an Associate Member of COG (Children’s Oncology Group, North America) and closely collaborating with the COG Renal Study Group. He was the coordinator of the EU funded project p-medicine and is enrolled in several other ongoing European projects. Norbert Graf has more than 25 years of experience with clinical trials.

Abstract:

Medicine is undergoing a paradigm shift from phenotyping to genotyping. This is supported by systems approaches to disease, modeling and visualization technologies, and new computational and mathematical tools. An open, modular architectural framework for tools, models and services needs to be provided to design and develop hypermodels This includes: • to share and handle efficiently the enormous personalized data sets • to ensure that policies for privacy, non-discrimination, and access to data, services, tools and models are implemented to maximize data protection and data security • to enable standardization and semantic data interoperability • to integrate models from system biology with VPH models • to guarantee that tools, services and models are clinically driven and do enhance decision support • to provide tools for large-scale, privacy-preserving data mining, and literature mining • to enhance patient empowerment In addition all tools and models need to be evaluated and validated by end-users. Feedback loops to developers for continuous improvements have to be integrated. Such an innovative architecture should promote the principle of open source. All tools, models and services have to be tested in concrete advanced clinical research projects and clinical trials that target urgent topics of the medical research community. Maintenance and further developments of the framework need to be addressed. To sustain such a self-supporting infrastructure realistic use cases have to offer tangible results for end-users in their daily practice. Teaching and educational programs for end-users have to be implemented to facilitate the access to the platform and the use of tools, models and services.