Presentation Dr Peter Szlosarek

A bioinformatic approach to mesothelioma therapeutics: from ADAM to TRAP

Arginine deprivation is a novel antimetabolite strategy for the treatment of arginine-dependent cancers that exploits differential expression and regulation of key urea cycle enzymes. Several studies have focused on inactivation of argininosuccinate synthetase 1 (ASS1) in a range of malignancies, including melanoma, hepatocellular carcinoma, and mesothelioma. Promoter methylation, in particular, has been identified as a mechanism for loss of the tumor suppressor role of ASS1 leading to tumoral dependence on exogenous arginine. Clinical trials of several arginine depletors are ongoing, including pegylated arginine deiminase (ADI-PEG20, Polaris Group, US) and bioengineered forms of human arginase. The challenge will be to identify tumors sensitive to arginine depletors, and integrate these agents into multimodality drug regimens using predictive biomarkers. Here, we have applied a bioinformatic approach to identify tractable pathways with ADI-PEG20 in the treatment of patients with mesothelioma. Recently, our phase 2 study of ADI-PEG20 in mesothelioma (ADAM) completed accrual and we are now launching a phase I combinatorial trial (TRAP) in the UK based on our bioinformatics studies.


Dr Peter Szlosarek (MBBS BSc MRCP PhD) is a Clinical Senior Lecturer at the Barts Cancer Institute, and Cancer Physician at St. Bartholomew’s Hospital, London. He studied Medicine and Pharmacology at King’s College, London and then specialised in Medical Oncology completing a PhD on the links between TNF-a, inflammation and cancer at the University of London. His clinical and lab research interests are in metabolic approaches to cancer therapy, particularly the role of arginine deprivation therapy in arginine-dependent cancers. This has led to clinical trials of the arginine-depleting agent ADI-PEG20 (Polaris Group, US) in mesothelioma (CTAAC grant) and small cell lung cancer, the latter a collaboration with the Ludwig Institute for Cancer Research in New York, US. He is funded by several grant bodies including Cancer Research UK, Barts and The London Charity, Medical Research Council and the British Lung Foundation. He maintains a research-orientated clinical practice at Barts in thoracic and cutaneous malignancy and is a member of the Royal College of Physicians, the Association of Cancer Physicians, the EORTC, AACR and ASCO.

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Presentation Dr. Marwane El Kharbili

Regulatory Compliance Management (RCM) is widely recognized as one of the main challenges still to be efficiently dealt with in Enterprise Models (EMs). In the discipline of Business Process Management (BPM) in particular, which plays a central role in modern management of enterprises, compliance is considered as an important driver of the efficiency, reliability and market value of companies. It consists of ensuring that enterprise systems behave according to some guidance provided in the form of regulations.
Existing approaches to RCM tackle this issue from two different perspectives: methodological and formal. The first category of a approaches is widely used in the industry and proposes several processes based on controls for compliance audit and governance. The second category of approaches seeks to construct complex formal languages and reasoning engines for automatically deciding on the state of compliance of a business process, but remains hardly accessible to practitioners who are not trained in formal methods. This work provides an approach for modeling and checking of regulatory compliance that profits from the power of complex formal languages and is specifically targeted at practitioners.
For this purpose, we introduce CoReL, a visual domain-specific modeling language for representing compliance requirements. The main objective behind CoReL is to bring the task of compliance modeling to the business user level where it  belongs. CoReL allows to leverage business process compliance modeling and checking, enhancing it with regard to, user-friendliness and coverage of various enterprise artifacts, as well as multiple types of regulatory constraints. Both informal and formal semantics of CoReL are introduced and its use for modeling and checking compliance regulations is shown on an example.
Dr. El Kharbili’s core fields of research are Enterprise Architectures/Business Process Management and Model Driven Engineering. His main area of research covers the development of procedures, languages and tools for the modelling, automated verification and analysis of regulatory compliance in information systems as well as the governance thereof.
Dr. El Kharbili is a graduate both the Grenoble Institute of Technology  (France) and the Karlsruhe Institute of Technology (Germany), and holds a M.Sc. from each university. He holds a Ph.D. in computer science from the University of Luxembourg and another Ph.D. degree also in computer science from the University of Osnabrueck (Germany). In his Ph.D. thesis he developed methods and languages for enterprise regulatory compliance management of enterprise models and business processes by applying and extending techniques form formal methods, security policies and software language engineering.
Prior to that he worked in the software industry and industrial research at both the IDS Scheer AG (inventors of the ARIS framework) and SAP AG. Dr. El Kharbili’s core fields of research are Enterprise Architectures/Business Process Management and Model Driven Engineering.

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