Academic journal article Environmental Health Perspectives

Summary of a Workshop on Regulatory Acceptance of (Q)SARs for Human Health and Environmental Endpoints

Academic journal article Environmental Health Perspectives

Summary of a Workshop on Regulatory Acceptance of (Q)SARs for Human Health and Environmental Endpoints

Article excerpt

The "Workshop on Regulatory Use of (Q)SARs for Human Health and Environmental Endpoints," organized by the European Chemical Industry Council and the International Council of Chemical Associations, gathered more than 60 human health and environmental experts from industry, academia, and regulatory agencies from around the world. They agreed, especially industry and regulatory authorities, that the workshop initiated great potential for the further development and use of predictive models, that is, quantitative structure-activity relationships [Q)SARs], for chemicals management in a much broader scope than is currently the case. To increase confidence in (Q)SAR predictions and minimization of their misuse, the workshop aimed to develop proposals for guidance and acceptability criteria. The workshop also described the broad outline of a system that would apply that guidance and acceptability criteria to a (Q)SAR when used for chemical management purposes, including priority setting, risk assessment, and classification and labeling. Key words: quantitative structure-activity relationships, regulatory acceptance.

**********

A 3-day scientific workshop titled "Regulatory Acceptance of (Q)SARs for Human Health and Environmental Endpoints," hosted by the European Centre for Ecotoxicology and Toxicology of Chemicals and organized by the International Council of Chemical Associations (ICCA) and the European Chemical Industry Council (CEFIC; as part of their long-range research initiative) was held 4-6 March 2002 in Setubal, near Lisbon, Portugal, Participants of the Setubal workshop had a diverse background both in human and environmental safety and in associations with academic institutions, government bodies, or industry from Europe, North America, and Japan. Participants agreed that the workshop initiated great potential for the further development of predictive models and their application for chemicals management, including priority setting, risk assessment, and classification and labeling.

One of the key messages during the workshop was that both industry and regulatory authorities share the same goal, that is, to use quantitative structure-activity relationships [Q)SARs] in a much broader scope than currently practiced for safety evaluation and chemicals management. Consequently, there was a clear agreement on the need to continue dialogue and cooperation.

(Q)SARs are simplified mathematical representations of complex chemical-biological interactions. They can be divided into two major types, QSARs and SARs. QSARs are all quantitative models yielding a continuous or categorical result. The most common techniques for developing QSARs are regression analysis, neural nets, and classification methods. Examples of regression models include ordinary least squares and partial least squares, whereas for neural nets back-propagation methods would be commonly used. Examples of classification methods are discriminant analysis, decision trees, and distance-based similarity analysis. SARs are qualitative relationships in the form of structural alerts that incorporate molecular substructures or fragments related to the presence or absence of activity.

(Q)SAR predictions have the potential to save time and money and minimize the use of animal testing. However, to fulfill this potential, the predictions, especially those considered for regulatory decision making, need to be scientifically valid, appropriate for the purpose intended, reliable, and accepted by decision makers. Approaches to determine the acceptability of (Q)SARs have been developed in the past [e.g., guidance from the Organisation for Economic Development (OECD)], but because of their breadth and generality, they have not been widely applied or respected by either (Q)SAR users or developers. As a consequence, decision making with the help of existing models must be done with care and considerable knowledge. The workshop in Setubal aimed at reopening the debate to develop more specific guidance and acceptability criteria and a system that would support the use of (Q)SARs such that the guidance and acceptability criteria were actually applied when a (Q)SAR was used for chemicals management purposes. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.