Research article
Collaborative development of predictive toxicology applications
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* Corresponding author: Barry Hardy barry.hardy@douglasconnect.com
1 Douglas Connect, Baermeggenweg 14, 4314 Zeiningen, Switzerland
2 In silico Toxicology, Altkircher Str. 4 CH-4052 Basel, Switzerland
3 Ideaconsult Ltd, A. Kanchev 4, Sofia 1000, Bulgaria
4 Istituto Superiore di Sanità, Environment and Health Department, Istituto Superiore di Sanita', Viale Regina Elena 299, Rome 00161, Italy
5 Technical University of Munich, Technische Universität München, Arcisstr. 21, 80333 München, Germany
6 Albert-Ludwigs University Freiburg, 79110 Freiburg i.Br., Germany
7 National Technical University of Athens, School of Chemical Engineering, Heroon Polytechneiou 9, 15780, Zographou, Athens, Greece
8 David Gallagher, Congresbury, Somerset, UK
9 Institute of Biomedical Chemistry of Russian Academy of Sciences, 119121 Moscow, Russia
10 Seascape Learning, 271 Double Story, New Rajinder Ngr., New Delhi 110060, India
11 Jawaharlal Nehru University, New Mehrauli Road, New Delhi 110067, India
12 Fraunhofer Institute for Toxicology & Experimental Medicine, Nikolai-Fuchs-Str. 1, 30625 Hannover, Germany
Journal of Cheminformatics 2010, 2:7 doi:10.1186/1758-2946-2-7
Published: 31 August 2010Abstract
OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying the chemical safety assessment requirements of the REACH legislation as it supports access to experimental data, (Quantitative) Structure-Activity Relationship models, and toxicological information through an integrating platform that adheres to regulatory requirements and OECD validation principles. Initial research defined the essential components of the Framework including the approach to data access, schema and management, use of controlled vocabularies and ontologies, architecture, web service and communications protocols, and selection and integration of algorithms for predictive modelling. OpenTox provides end-user oriented tools to non-computational specialists, risk assessors, and toxicological experts in addition to Application Programming Interfaces (APIs) for developers of new applications. OpenTox actively supports public standards for data representation, interfaces, vocabularies and ontologies, Open Source approaches to core platform components, and community-based collaboration approaches, so as to progress system interoperability goals.
The OpenTox Framework includes APIs and services for compounds, datasets, features, algorithms, models, ontologies, tasks, validation, and reporting which may be combined into multiple applications satisfying a variety of different user needs. OpenTox applications are based on a set of distributed, interoperable OpenTox API-compliant REST web services. The OpenTox approach to ontology allows for efficient mapping of complementary data coming from different datasets into a unifying structure having a shared terminology and representation.
Two initial OpenTox applications are presented as an illustration of the potential impact of OpenTox for high-quality and consistent structure-activity relationship modelling of REACH-relevant endpoints: ToxPredict which predicts and reports on toxicities for endpoints for an input chemical structure, and ToxCreate which builds and validates a predictive toxicity model based on an input toxicology dataset. Because of the extensible nature of the standardised Framework design, barriers of interoperability between applications and content are removed, as the user may combine data, models and validation from multiple sources in a dependable and time-effective way.