Collaborative Development of Predictive Toxicology Applications

I enclose here an abstract and copy of the presentation for the Plenary Lecture "Collaborative Development of Predictive Toxicology Applications" that I presented in Istanbul on 6 July 2009 at the Fifth International Symposium on Computational Methods in Toxicology and Pharmacology Integrating Internet Resources (CMTPI 2009).

Presentation

Download OpenTox-CMTPI 2009 Presentation 90706

Abstract

Collaborative Development of Predictive Toxicology Applications

Barry Hardy*^a, Christoph Helma^b, Nina Jeliazkova^c, Romualdo Benigni^d, Stefan Kramer^e, Andreas Karwath^f, Haralambos Sarimveis^g, David Gallagher^h, Vladimir Poroikovⁱ, Sunil Chawla^j, Sylvia Escher^k

This lecture will provide a perspective on the growing significance of community and collaboration approaches in predictive toxicology.  In part these challenges are technical and involve progressing issues related to cross-organisational, enterprise and application interoperability. Additional challenges include the development and application of best practices related to knowledge management, culture, organizational and industry development.

The EC-funded FP7 project “OpenTox” (www.opentox.org) is developing an Open Source-based predictive toxicology framework that provides a unified access to toxicological data and (Quantitative) Structure-Activity Relationship i.e., (Q)SAR models. OpenTox provides tools for the integration of data, for the generation and validation of (Q)SAR models for toxic effects, libraries for the development and integration of (Q)SAR algorithms, and scientifically sound validation routines. OpenTox will support the development of applications for non-computational specialists in addition to interfaces for risk assessors, toxicological experts and model and algorithm developers.

OpenTox is relevant for the implementation of REACH as it allows risk assessors to access experimental data, (Q)SAR models and toxicological information from a unified interface that adheres to European and international regulatory requirements including OECD Guidelines for validation and reporting.  The OpenTox framework is being populated initially with data and models for chronic, genotoxic and carcinogenic effects. These are the endpoints where computational methods promise the greatest potential reduction in animal testing required under REACH. Initial research has defined the essential components of the framework architecture, approach to data access, schema and management, use of controlled vocabularies and ontologies, web service and communications protocols, and selection and integration of algorithms for predictive modelling.  The initial results of this research and next steps will be discussed.

OpenTox has been initiated as a collaborative project involving a combination of 11 different enterprise, university and government research groups to design and build the initial framework.  Additionally numerous organizations with industry, regulatory or expert interests are being included from the start in providing guidance and direction.  The goal is to expand OpenTox as a community project enabling additional expert and user participants to be involved in developments in as timely a manner as possible. To this end, our agreed upon intention is to carry out developments in an open and transparent manner from the early days of the project, and to open up discussions and development to the global community at large, who may either participate in developments or provide user perspectives.  Cooperation on data standards, data integration, ontologies, integration of algorithm predictions from different methods, and testing and validation all have significant collaboration opportunities and benefits for the community.  Additionally, practices for building effective collaborations from the OpenTox community approach will be discussed.

About OpenTox

OpenTox - An Open Source Predictive Toxicology Framework, www.opentox.org, is funded under the EU Seventh Framework Program: HEALTH-2007-1.3-3 Promotion, development, validation, acceptance and implementation of QSARs (Quantitative Structure-Activity Relationships) for toxicology, Project Reference Number Health-F5-2008-200787 (2008-2011).

Project Partners

Douglas Connect^a, In Silico Toxicology^b, Ideaconsult^c, Istituto Superiore di Sanita'^d, Technical University of Munich^e, Albert Ludwigs University Freiburg^f, National Technical University of Athens^g, David Gallagher^h, Institute of Biomedical Chemistry of the Russian Academy of Medical Sciencesⁱ, Seascape Learning^j and the Fraunhofer Institute for Toxicology & Experimental Medicine^k

Advisory Board
European Centre for the Validation of Alternative Methods, European Chemicals Bureau, U.S Environmental Protection Agency, U.S. Food & Drug Administration, Nestle, Roche, AstraZeneca, LHASA, Leadscope, University of North Carolina, EC Environment Directorate General, Organisation for Economic Co-operation & Development, CADASTER and Bayer Healthcare

*Contact Address: Dr. Barry Hardy, OpenTox Project Coordinator and Director, Community of Practice & Research Activities, Douglas Connect, Baermeggenweg 14, 4314 Zeiningen, Switzerland

 

Comments

[Mike Harwood]

You have a comprehensive list of data standards for toxicology data in your preentation. I notice that SEND is missing. This is the standard being developed by CDISC for electronic submission to FDA and that is attractig considerable interest and effort from a wide range of (principally) US organisations. It is currently the subject of a pilot project with FDA.
You may want to take a look at it as it will deliver both data interchange format standardisation and controlled terminology across regulatory submissions for preclinical toxicology. http://www.fda.gov/ForIndustry/DataStandards/CDISCDataStandards/ucm155320.htm