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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
The predictivity of the -alert performance- functionality of the OECD QSAR-Toolbox (c/w further issues on the
Jose D Suarez-Torres1, Carlos E Ciangherotti2, Fausto A Jimenez-Orozco3
1Department of Pharmacy, and Department of Toxicology. Universidad Nacional de Colombia, Bogota, D.C., Colombia; Institute of Pharmaceutical Research, School of Pharmacy, Universidad Central de Venezuela, Caracas, D.C., Venezuela.
Abstract:
The OECD QSAR-Toolbox can be considered a milestone in predictive toxicology. Because of the reliability of its supporting institutions (OECD and ECHA), its broadness in terms of feeder databases, and its predictive capacity, the QSAR-Toolbox is called to have a major role in regulatory toxicology. Recently, a novel functionality was built for the QSAR-Toolbox: the alert performance (AP). This prompted us to analyze the strengths, potentialities, and limitations of this new functionality, especially in the light of a pivotal framework recently discussed in the literature for the predictive use of nonclinical screening and testing. After meticulous analysis, and through some worked examples, high predictive capacity and applicability were found for the AP in both predictive and regulatory toxicology. For a specified chemical, the AP is useful in (a) anticipating its overall results in a given nonclinical test; (b) predicting its overall results regarding a selected toxicological endpoint in humans, and (c) facilitating post- to pre-test probabilities approaches that may support regulatory authorization for waiving the conduction of selected tests in laboratory animals. Furthermore, if a QSAR-Toolbox initiative is developed in or extended to pharmacology (e.g., safety pharmacology, drug abuse potential), it could represent another milestone; one that would give rise to the field of predictive pharmacology.
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