The Experts below are selected from a list of 2298 Experts worldwide ranked by ideXlab platform
Joseph F Contrera - One of the best experts on this subject based on the ideXlab platform.
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a comprehensive model for Reproductive and developmental Toxicity hazard identification i development of a weight of evidence qsar database
Regulatory Toxicology and Pharmacology, 2007Co-Authors: Edwin J Matthews, Naomi L Kruhlak, Daniel R Benz, Joseph F ContreraAbstract:A weight of evidence (WOE) Reproductive and developmental toxicology (reprotox) database was constructed that is suitable for quantitative structure-activity relationship (QSAR) modeling and human hazard identification of untested chemicals. The database was derived from multiple publicly available reprotox databases and consists of more than 10,000 individual rat, mouse, or rabbit reprotox tests linked to 2134 different organic chemical structures. The reprotox data were classified into seven general classes (male Reproductive Toxicity, Female Reproductive Toxicity, fetal dysmorphogenesis, functional Toxicity, mortality, growth, and newborn behavioral Toxicity), and 90 specific categories as defined in the source reprotox databases. Each specific category contained over 500 chemicals, but the percentage of active chemicals was low, generally only 0.1-10%. The mathematical WOE model placed greater significance on confirmatory observations from repeat experiments, chemicals with multiple findings within a category, and the categorical relatedness of the findings. Using the weighted activity scores, statistical analyses were performed for specific data sets to identify clusters of categories that were correlated, containing similar profiles of active and inactive chemicals. The analysis revealed clusters of specific categories that contained chemicals that were active in two or more mammalian species (trans-species). Such chemicals are considered to have the highest potential risk to humans. In contrast, some specific categories exhibited only single species-specific activities. Results also showed that the rat and mouse were more susceptible to dysmorphogenesis than rabbits (6.1- and 3.6-fold, respectively).
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a comprehensive model for Reproductive and developmental Toxicity hazard identification ii construction of qsar models to predict activities of untested chemicals
Regulatory Toxicology and Pharmacology, 2007Co-Authors: Edwin J Matthews, Naomi L Kruhlak, Daniel R Benz, Julian M Ivanov, Gilles Klopman, Joseph F ContreraAbstract:Abstract This report describes the construction, optimization and validation of a battery of quantitative structure–activity relationship (QSAR) models to predict Reproductive and developmental (reprotox) hazards of untested chemicals. These models run with MC4PC software to predict seven general reprotox classes: male and Female Reproductive Toxicity, fetal dysmorphogenesis, functional Toxicity, mortality, growth, and newborn behavioral Toxicity. The reprotox QSARs incorporate a weight of evidence paradigm using rats, mice, and rabbit reprotox study data and are designed to identify trans-species reprotoxicants. The majority of the reprotox QSARs exhibit good predictive performance properties: high specificity (>80%), low false positives ( 2.00), and high coverage (>80%) in 10% leave-many-out validation experiments. The QSARs are based on 627–2023 chemicals and exhibited a wide applicability domain for FDA regulated organic chemicals for which they were designed. Experiments were also performed using the MC4PC multiple module prediction technology, and ROC statistics, and adjustments to the ratio of active to inactive ( A / I ratio) chemicals in training data sets were made to optimize the predictive performance of QSAR models. Results revealed that an A / I ratio of ∼40% was optimal for MC4PC. We discuss specific recommendations for the application of the reprotox QSAR battery.
Edwin J Matthews - One of the best experts on this subject based on the ideXlab platform.
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a comprehensive model for Reproductive and developmental Toxicity hazard identification i development of a weight of evidence qsar database
Regulatory Toxicology and Pharmacology, 2007Co-Authors: Edwin J Matthews, Naomi L Kruhlak, Daniel R Benz, Joseph F ContreraAbstract:A weight of evidence (WOE) Reproductive and developmental toxicology (reprotox) database was constructed that is suitable for quantitative structure-activity relationship (QSAR) modeling and human hazard identification of untested chemicals. The database was derived from multiple publicly available reprotox databases and consists of more than 10,000 individual rat, mouse, or rabbit reprotox tests linked to 2134 different organic chemical structures. The reprotox data were classified into seven general classes (male Reproductive Toxicity, Female Reproductive Toxicity, fetal dysmorphogenesis, functional Toxicity, mortality, growth, and newborn behavioral Toxicity), and 90 specific categories as defined in the source reprotox databases. Each specific category contained over 500 chemicals, but the percentage of active chemicals was low, generally only 0.1-10%. The mathematical WOE model placed greater significance on confirmatory observations from repeat experiments, chemicals with multiple findings within a category, and the categorical relatedness of the findings. Using the weighted activity scores, statistical analyses were performed for specific data sets to identify clusters of categories that were correlated, containing similar profiles of active and inactive chemicals. The analysis revealed clusters of specific categories that contained chemicals that were active in two or more mammalian species (trans-species). Such chemicals are considered to have the highest potential risk to humans. In contrast, some specific categories exhibited only single species-specific activities. Results also showed that the rat and mouse were more susceptible to dysmorphogenesis than rabbits (6.1- and 3.6-fold, respectively).
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a comprehensive model for Reproductive and developmental Toxicity hazard identification ii construction of qsar models to predict activities of untested chemicals
Regulatory Toxicology and Pharmacology, 2007Co-Authors: Edwin J Matthews, Naomi L Kruhlak, Daniel R Benz, Julian M Ivanov, Gilles Klopman, Joseph F ContreraAbstract:Abstract This report describes the construction, optimization and validation of a battery of quantitative structure–activity relationship (QSAR) models to predict Reproductive and developmental (reprotox) hazards of untested chemicals. These models run with MC4PC software to predict seven general reprotox classes: male and Female Reproductive Toxicity, fetal dysmorphogenesis, functional Toxicity, mortality, growth, and newborn behavioral Toxicity. The reprotox QSARs incorporate a weight of evidence paradigm using rats, mice, and rabbit reprotox study data and are designed to identify trans-species reprotoxicants. The majority of the reprotox QSARs exhibit good predictive performance properties: high specificity (>80%), low false positives ( 2.00), and high coverage (>80%) in 10% leave-many-out validation experiments. The QSARs are based on 627–2023 chemicals and exhibited a wide applicability domain for FDA regulated organic chemicals for which they were designed. Experiments were also performed using the MC4PC multiple module prediction technology, and ROC statistics, and adjustments to the ratio of active to inactive ( A / I ratio) chemicals in training data sets were made to optimize the predictive performance of QSAR models. Results revealed that an A / I ratio of ∼40% was optimal for MC4PC. We discuss specific recommendations for the application of the reprotox QSAR battery.
Janneche Utne Skaare - One of the best experts on this subject based on the ideXlab platform.
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Reproductive and developmental Toxicity of phthalates
Journal of Toxicology and Environmental Health-part B-critical Reviews, 2009Co-Authors: Jan Ludvig Lyche, Arno C Gutleb, Ake Bergman, Gunnar Sundstol Eriksen, Albertinka J Murk, Erik Ropstad, Margaret Saunders, Janneche Utne SkaareAbstract:The purposes of this review are to (1) evaluate human and experimental evidence for adverse effects on reproduction and development in humans, produced by exposure to phthalates, and (2) identify knowledge gaps as for future studies. The widespread use of phthalates in consumer products leads to ubiquitous and constant exposure of humans to these chemicals. Phthalates were postulated to produce endocrine-disrupting effects in rodents, where fetal exposure to these compounds was found to induce developmental and Reproductive Toxicity. The adverse effects observed in rodent models raised concerns as to whether exposure to phthalates represents a potential health risk to humans. At present, di(2-ethylhexyl) phthalate (DEHP), di-n-butyl phthalate (DBP), and butyl benzyl phthalate (BBP) have been demonstrated to produce Reproductive and developmental Toxicity; thus, this review focuses on these chemicals. For the general population, DEHP exposure is predominantly via food. The average concentrations of phthalates are highest in children and decrease with age. At present, DEHP exposures in the general population appear to be close to the tolerable daily intake (TDI), suggesting that at least some individuals exceed the TDI. In addition, specific high-risk groups exist with internal levels that are several orders of magnitude above average. Urinary metabolites used as biomarkers for the internal levels provide additional means to determine more specifically phthalate exposure levels in both general and high-risk populations. However, exposure data are not consistent and there are indications that secondary metabolites may be more accurate indicators of the internal exposure compared to primary metabolites. The present human Toxicity data are not sufficient for evaluating the occurrence of Reproductive effects following phthalate exposure in humans, based on existing relevant animal data. This is especially the case for data on Female Reproductive Toxicity, which are scarce. Therefore, future research needs to focus on developmental and Reproductive endpoints in humans. It should be noted that phthalates occur in mixtures but most toxicological information is based on single compounds. Thus, it is concluded that it is important to improve the knowledge of toxic interactions among the different chemicals and to develop measures for combined exposure to various groups of phthalates.
Naomi L Kruhlak - One of the best experts on this subject based on the ideXlab platform.
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a comprehensive model for Reproductive and developmental Toxicity hazard identification i development of a weight of evidence qsar database
Regulatory Toxicology and Pharmacology, 2007Co-Authors: Edwin J Matthews, Naomi L Kruhlak, Daniel R Benz, Joseph F ContreraAbstract:A weight of evidence (WOE) Reproductive and developmental toxicology (reprotox) database was constructed that is suitable for quantitative structure-activity relationship (QSAR) modeling and human hazard identification of untested chemicals. The database was derived from multiple publicly available reprotox databases and consists of more than 10,000 individual rat, mouse, or rabbit reprotox tests linked to 2134 different organic chemical structures. The reprotox data were classified into seven general classes (male Reproductive Toxicity, Female Reproductive Toxicity, fetal dysmorphogenesis, functional Toxicity, mortality, growth, and newborn behavioral Toxicity), and 90 specific categories as defined in the source reprotox databases. Each specific category contained over 500 chemicals, but the percentage of active chemicals was low, generally only 0.1-10%. The mathematical WOE model placed greater significance on confirmatory observations from repeat experiments, chemicals with multiple findings within a category, and the categorical relatedness of the findings. Using the weighted activity scores, statistical analyses were performed for specific data sets to identify clusters of categories that were correlated, containing similar profiles of active and inactive chemicals. The analysis revealed clusters of specific categories that contained chemicals that were active in two or more mammalian species (trans-species). Such chemicals are considered to have the highest potential risk to humans. In contrast, some specific categories exhibited only single species-specific activities. Results also showed that the rat and mouse were more susceptible to dysmorphogenesis than rabbits (6.1- and 3.6-fold, respectively).
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a comprehensive model for Reproductive and developmental Toxicity hazard identification ii construction of qsar models to predict activities of untested chemicals
Regulatory Toxicology and Pharmacology, 2007Co-Authors: Edwin J Matthews, Naomi L Kruhlak, Daniel R Benz, Julian M Ivanov, Gilles Klopman, Joseph F ContreraAbstract:Abstract This report describes the construction, optimization and validation of a battery of quantitative structure–activity relationship (QSAR) models to predict Reproductive and developmental (reprotox) hazards of untested chemicals. These models run with MC4PC software to predict seven general reprotox classes: male and Female Reproductive Toxicity, fetal dysmorphogenesis, functional Toxicity, mortality, growth, and newborn behavioral Toxicity. The reprotox QSARs incorporate a weight of evidence paradigm using rats, mice, and rabbit reprotox study data and are designed to identify trans-species reprotoxicants. The majority of the reprotox QSARs exhibit good predictive performance properties: high specificity (>80%), low false positives ( 2.00), and high coverage (>80%) in 10% leave-many-out validation experiments. The QSARs are based on 627–2023 chemicals and exhibited a wide applicability domain for FDA regulated organic chemicals for which they were designed. Experiments were also performed using the MC4PC multiple module prediction technology, and ROC statistics, and adjustments to the ratio of active to inactive ( A / I ratio) chemicals in training data sets were made to optimize the predictive performance of QSAR models. Results revealed that an A / I ratio of ∼40% was optimal for MC4PC. We discuss specific recommendations for the application of the reprotox QSAR battery.
Daniel R Benz - One of the best experts on this subject based on the ideXlab platform.
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a comprehensive model for Reproductive and developmental Toxicity hazard identification i development of a weight of evidence qsar database
Regulatory Toxicology and Pharmacology, 2007Co-Authors: Edwin J Matthews, Naomi L Kruhlak, Daniel R Benz, Joseph F ContreraAbstract:A weight of evidence (WOE) Reproductive and developmental toxicology (reprotox) database was constructed that is suitable for quantitative structure-activity relationship (QSAR) modeling and human hazard identification of untested chemicals. The database was derived from multiple publicly available reprotox databases and consists of more than 10,000 individual rat, mouse, or rabbit reprotox tests linked to 2134 different organic chemical structures. The reprotox data were classified into seven general classes (male Reproductive Toxicity, Female Reproductive Toxicity, fetal dysmorphogenesis, functional Toxicity, mortality, growth, and newborn behavioral Toxicity), and 90 specific categories as defined in the source reprotox databases. Each specific category contained over 500 chemicals, but the percentage of active chemicals was low, generally only 0.1-10%. The mathematical WOE model placed greater significance on confirmatory observations from repeat experiments, chemicals with multiple findings within a category, and the categorical relatedness of the findings. Using the weighted activity scores, statistical analyses were performed for specific data sets to identify clusters of categories that were correlated, containing similar profiles of active and inactive chemicals. The analysis revealed clusters of specific categories that contained chemicals that were active in two or more mammalian species (trans-species). Such chemicals are considered to have the highest potential risk to humans. In contrast, some specific categories exhibited only single species-specific activities. Results also showed that the rat and mouse were more susceptible to dysmorphogenesis than rabbits (6.1- and 3.6-fold, respectively).
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a comprehensive model for Reproductive and developmental Toxicity hazard identification ii construction of qsar models to predict activities of untested chemicals
Regulatory Toxicology and Pharmacology, 2007Co-Authors: Edwin J Matthews, Naomi L Kruhlak, Daniel R Benz, Julian M Ivanov, Gilles Klopman, Joseph F ContreraAbstract:Abstract This report describes the construction, optimization and validation of a battery of quantitative structure–activity relationship (QSAR) models to predict Reproductive and developmental (reprotox) hazards of untested chemicals. These models run with MC4PC software to predict seven general reprotox classes: male and Female Reproductive Toxicity, fetal dysmorphogenesis, functional Toxicity, mortality, growth, and newborn behavioral Toxicity. The reprotox QSARs incorporate a weight of evidence paradigm using rats, mice, and rabbit reprotox study data and are designed to identify trans-species reprotoxicants. The majority of the reprotox QSARs exhibit good predictive performance properties: high specificity (>80%), low false positives ( 2.00), and high coverage (>80%) in 10% leave-many-out validation experiments. The QSARs are based on 627–2023 chemicals and exhibited a wide applicability domain for FDA regulated organic chemicals for which they were designed. Experiments were also performed using the MC4PC multiple module prediction technology, and ROC statistics, and adjustments to the ratio of active to inactive ( A / I ratio) chemicals in training data sets were made to optimize the predictive performance of QSAR models. Results revealed that an A / I ratio of ∼40% was optimal for MC4PC. We discuss specific recommendations for the application of the reprotox QSAR battery.
