Dr. Assia Kovatcheva graduated as a pharmacist from the University of Vienna where she received also a conferral of a doctorate in natural sciences with a focus on the development of 2D and 3D QSAR methodologies for chiral substances such as fragrance compounds. This approach was later applied to endocrine disruptors during a post-doctoral collaboration at the John Moores University, Liverpool. During her post-academic career she worked with multiple corporations as an advisor in the domain of scientific and regulatory affairs and innovation applicable to food (safety, quality and toxicology), pharmaceuticals (dossier registrations, dossier life cycle, pharmacovigilance incl. materiovigilance), chemicals (REACH, CLP, toxicovigilance) as well as related fields such as functional ingredients for the Cosmetic industry. Dr. Assia Kovatcheva was involved in a number of EU projects such as FP5 “EasyRing”, FP6 “Sens-it-iv”, FP7 “FoodTrain” and “Satin” as well as industrial platforms such as ILSI activities on Nutrition and mental performance and Quantitative risk assessment.
OpenTox Session 5: Integrated Testing Methods
The principles of OpenTox to provide with a community based framework on toxicological assessment will be presented through examples of different dimension starting with a knowledge infrastructure platform supported by the ACEnano project under the EU Horizon 2020. Major charactertistic of this platform is to ensure FAIR (Findable, Accessible, Interoperable, and Reusable) data principles characterising the physicochemical behaviour of nanomaterials.
At national level, the scientific and regulatory expertise on the safe handling of synthetic nanomaterials in Switzerland will be promoted via the independent national contact point “contactpointnano.ch”. The purpose of this focal point is to accelarate innovation by efficiently conveying tailored high-quality information to companies, SMEs and start-ups.
Further, a data integration tool GENEVESTIGATOR® consisting of an analysis tool and database with over 120’000 samples from important data sources will be proposed to overcome challenges associated with the heterogeneity and quality of gene expression data in published studies. GENEVESTIGATOR® will make use of controlled vocabularies and global normalization procedures that should allow on-the fly calculations which will produce results compatible for use in downstream AI.
In this session, it is demonstrated that the progress of collaboration in integrated testing can be achieved via high quality data, standardised methods and a broad network of tools and expertise that is stored in a reusable format and easily accessible to services, testing, and analysis.