Deliverables
The result "Data of pesticide toxicity, structures and chemical descriptors: Dietary Toxicity for Bobwhite Quail (Colinus virginianus) - 38665" is composed by the complete series of compounds used to build the result named A combined QSAR model for pesticides to predict Dietary Toxicity for Bobwhite Quail (Colinus virginianus) 38658. Within this result a complete description of the compounds is given. The description provided can be divided into three levels: chemical, revised structures of the pesticides; mathematical, represented by the molecular descriptors which are the projection of the chemical space into a mathematical space; toxicological, we present a highly accurate set of toxicity values related to the compounds described.
We supply this result for the whole set of 98 pesticides selected to build the result 38658- in the more common format for store such a kind of information. The available files are one of single text with sdf extension, providing both chemical and toxicological information, and one excel file containing several worksheets for the mathematical representation.
The most suitable sources of toxicological data to be collected in this project were the EPA-OPP, SEEM and BBA databases.
In practice we used U.S. EPA-OPP data. During the project OECD published criteria for the validation of QSAR; one of these criteria states that components of the model have to be given, which includes the toxicity data.
A first essential characteristic regards the number of chemical with toxicity data available. Among the available databases the EPA-OPP was the one with more data and was selected as primarily source for the data.
Additionally several sources of ecotoxicological data have been identified and taken into account to produce the datasets. Only high quality data have been used and compared between databases, as a further check. We defined a procedure to identify a single toxicity value in a reproducible way when multiple values were available. We adopted a conservative approach using the lowest value since this choice is typically preferred in the E.U.
We conclude that the selected values are reliable, with low internal variability as we eliminated compounds with a toxicity range exceeding a factor of four.
We have identified as potential users for this result the very owners of the databases employed within this project. Indeed this result can be employed as an external audit of the results, allowing them to provide more accurate information. Besides, the data has been collected and stored in a systematic way that might be useful for regulatory bodies and industries, granting them a fast and easy source of data related with rainbow trout toxicity for pesticides.
A third kind of potential users are academic researches working in modelling. For such a kind of research a reliable source of data is of the outmost importance, this result grants an outstanding set of data useful for assessing the validity on brand new approaches, allowing the calibration of material and methodologies for researchers not only working in pesticides toxicity. Since the data must be public available this result is an obvious benefit for the social welfare.
The dissemination of this result is oriented in two directions. We have presented the result during the European workshop. The attendants of this workshop are placed in key institutions related with pesticides development.
We have sent this result to different challenges in QSAR modelling and therefore it has started to be used by other researchers, allowing the public the download of this result in the DEMETRA web site.
As we have mentioned there are available several databases, which contains similar information. But the data is not always comparable, rationally structured or exact. A thorough revision of the data with a strict filtering was necessary in order to assure the goodness of the data to be employed. Precisely a big deal of the work performed within DEMETRA project has been directed to collect and verify the integrity of the data, providing to third parties a reliable source of information rationally structured.
This result can not give a material benefit in economical terms, but it is a useful hint for those organizations involved in the pesticide development. This result provides a reliable source of data that can be used in several ways. It is a ready-to-use source of data, for evaluation of the state of the art about pesticide environmental toxicity for Rainbow trout. There are other applications like the development of new QSAR models useful to complement the models presented as results 38655, 38656, 38657, 38658 and 38659.
It is as well a source of reliable data ready to be employed within the developing of new QSAR approaches.
The result "Data of pesticide toxicity, structures and chemical descriptors: Acute Toxicity for Water Flea (Daphnia magna) - 38663" is composed by the complete series of compounds used to build the result named A combined QSAR model for pesticides to predict Acute Toxicity for Water Flea (Daphnia magna) 38656. Within this result a complete description of the compounds is given. The description provided can be divided into three levels: chemical, revised structures of the pesticides; mathematical, represented by the molecular descriptors which are the projection of the chemical space into a mathematical space; toxicological, we present a highly accurate set of toxicity values related to the compounds described.
We supply this result for the whole set of 220 pesticides selected to build the result 38656- in the more common format for store such a kind of information. The available files are one of single text with sdf extension, providing both chemical and toxicological information, and one excel file containing several worksheets for the mathematical representation.
The most suitable sources of toxicological data to be collected in this project were the EPA-OPP, SEEM and BBA databases.
In practice we used U.S. EPA-OPP data. During the project OECD published criteria for the validation of QSAR; one of these criteria states that components of the model have to be given, which includes the toxicity data.
A first essential characteristic regards the number of chemical with toxicity data available. Among the available databases the EPA-OPP was the one with more data and was selected as primarily source for the data.
Additionally several sources of ecotoxicological data have been identified and taken into account to produce the datasets. Only high quality data have been used and compared between databases, as a further check. We defined a procedure to identify a single toxicity value in a reproducible way when multiple values were available. We adopted a conservative approach using the lowest value since this choice is typically preferred in the E.U.
We conclude that the selected values are reliable, with low internal variability as we eliminated compounds with a toxicity range exceeding a factor of four.
We have identified as potential users for this result the very owners of the databases employed within this project. Indeed this result can be employed as an external audit of the results, allowing them to provide more accurate information. Besides, the data has been collected and stored in a systematic way that might be useful for regulatory bodies and industries, granting them a fast and easy source of data related with rainbow trout toxicity for pesticides.
A third kind of potential users are academic researches working in modelling. For such a kind of research a reliable source of data is of the outmost importance, this result grants an outstanding set of data useful for assessing the validity on brand new approaches, allowing the calibration of material and methodologies for researchers not only working in pesticides toxicity. Since the data must be public available this result is an obvious benefit for the social welfare.
The dissemination of this result is oriented in two directions. We have presented the result during the European workshop. The attendants of this workshop are placed in key institutions related with pesticides development.
We have sent this result to different challenges in QSAR modelling and therefore it has started to be used by other researchers, allowing the public the download of this result in the DEMETRA web site.
As we have mentioned there are available several databases, which contains similar information. But the data is not always comparable, rationally structured or exact. A thorough revision of the data with a strict filtering was necessary in order to assure the goodness of the data to be employed. Precisely a big deal of the work performed within DEMETRA project has been directed to collect and verify the integrity of the data, providing to third parties a reliable source of information rationally structured.
This result cannot give a material benefit in economical terms, but it is a useful hint for those organizations involved in the pesticide development. This result provides a reliable source of data that can be used in several ways. It is a ready-to-use source of data, for evaluation of the state of the art about pesticide environmental toxicity for Rainbow trout. There are other applications like the development of new QSAR models useful to complement the models presented as results 38655, 38656, 38657, 38658 and 38659.
It is as well a source of reliable data ready to be employed within the developing of new QSAR approaches.
The result "A combined QSAR model for pesticides to predict Acute Contact Toxicity for Honey Bee (Apis Mellifera) - 38659" is given in the form of a fully predictive QSAR model built by means the combination of two individual QSAR models. The acute contact toxicity for honey bee hybrid has been obtained with the ruled based approach (a non continuous function that merges different individual models). Inputs for this model were a Partial Least Squares and a Artificial Neural Networks individual model.
The basic idea of the hybrid model, which merges different points of view and combines the capabilities of different algorithms, is that different models can be more or less powerful in one or another aspect, and that they can be improved by combining positive performances of individual models. The target of the combined model is to cover as much as possible the space of the chemicals it has to model, reducing the mistakes.
These individual models were built using 88 pesticides as training set whose toxicity values were obtained from the more trustworthy pesticide databases (see TIP corresponding to Data of pesticide toxicity, structures and chemical descriptors: Acute Contact Toxicity for Honey Bee (Apis Mellifera) - 38666.
This result is implemented as a part of a Java applet, also able to run as standalone version, whose only input is the molecular descriptors of the new pesticide to be predicted.
The present result fulfils completely the quality checkpoints marked by OECD and offers a good alternative for supporting the progressive reduction of animal experimentation covering the lack of proper QSAR models for regulatory purposes in the pesticide risk assessment. Being one of the first successful approaches in this area, this model currently has an advantageous position to successfully start to be used by regulatory bodies.
The combined QSAR model for acute contact toxicity, honey bee is in line with the recent EU legislative initiative REACH on the possible use of QSAR models as an alternative animal experimentation.
The main idea that underlies in the whole development of this model is creating a tool to be used (not only formally, but in practice) within the Pesticide Directive 91/414, thus a crucial point of the project involved a deep evaluation of criteria for its use.
QSAR models, eventually evaluated for regulatory purposes, that have been developed so far use common QSAR criteria not specific for regulatory purposes. This places the present model in an advantageous position due to its correct timing to the legislation, and makes of it a desirable tool for all the agents involved in risk assessment.
The major user category we have identified within the DEMETRA project is regulatory body.
Non-governmental agencies are also major potential users of the models, for issues similar to those of regulators.
Another important category is industry in the field of plan protection products.
Another major category of users is academy and research institutes.
The first steps in result dissemination has been already taken organizing an European workshop. Members of key institutions have been invited to this meeting covering most of the regulatory bodies and industries dealing with pesticides at European level.
From the ethical point of view this result can help to reduce the suffering derived to the exposure of rainbow trouts to non tested compounds. The use of our free model is cheaper than performing animal experimentation and there is a social concern that can be fulfilled by our model.
It helps to reduce the time in assessing the environmental risk of new pesticides/chemicals, the budget foreseen for experimentation and the material, energy and space necessary to perform the experimental assays. Additionally these animal assays need big infrastructures since it is necessary to maintain complete beehive, and additional material for the proper care of the animals. Since the QSAR model reduces the number of experimental tests this results in a significance reduction of the expenses.
Additionally this model can help to boost the research in new pesticides. This model allows the evaluation of environmental risks in a prognostic way, therefore it is not necessary to perform the syntheses of the compound. This fact allows to the industries to deal with a higher amount of chemicals candidates to become a pesticide in the market. Also it might help to evaluate metabolites, allowing a more precise knowledge of the mechanistic features of the environmental risks.
The result "Data of pesticide toxicity, structures and chemical descriptors: Acute Contact Toxicity for Honey Bee (Apis Mellifera) - 38666" is composed by the complete series of compounds used to build the result named A combined QSAR model for pesticides to predict Acute Contact Toxicity for Honey Bee (Apis Mellifera) 38659. Within this result a complete description of the compounds is given. The description provided can be divided into three levels: chemical, revised structures of the pesticides; mathematical, represented by the molecular descriptors which are the projection of the chemical space into a mathematical space; toxicological, we present a highly accurate set of toxicity values related to the compounds described.
We supply this result for the whole set of 86 pesticides selected to build the result 38659- in the more common format for store such a kind of information. The available files are one of single text with sdf extension, providing both chemical and toxicological information, and one excel file containing several worksheets for the mathematical representation.
The most suitable sources of toxicological data to be collected in this project were the EPA-OPP, SEEM and BBA databases.
In practice we used U.S. EPA-OPP data. During the project OECD published criteria for the validation of QSAR; one of these criteria states that components of the model have to be given, which includes the toxicity data.
A first essential characteristic regards the number of chemical with toxicity data available. Among the available databases the EPA-OPP was the one with more data and was selected as primarily source for the data.
Additionally several sources of ecotoxicological data have been identified and taken into account to produce the datasets. Only high quality data have been used and compared between databases, as a further check. We defined a procedure to identify a single toxicity value in a reproducible way when multiple values were available. We adopted a conservative approach using the lowest value since this choice is typically preferred in the E.U.
We conclude that the selected values are reliable, with low internal variability as we eliminated compounds with a toxicity range exceeding a factor of four.
We have identified as potential users for this result the very owners of the databases employed within this project. Indeed this result can be employed as an external audit of the results, allowing them to provide more accurate information. Besides, the data has been collected and stored in a systematic way that might be useful for regulatory bodies and industries, granting them a fast and easy source of data related with rainbow trout toxicity for pesticides.
A third kind of potential users are academic researches working in modelling. For such a kind of research a reliable source of data is of the outmost importance, this result grants an outstanding set of data useful for assessing the validity on brand new approaches, allowing the calibration of material and methodologies for researchers not only working in pesticides toxicity. Since the data must be public available this result is an obvious benefit for the social welfare.
The dissemination of this result is oriented in two directions. We have presented the result during the European workshop. The attendants of this workshop are placed in key institutions related with pesticides development.
We have sent this result to different challenges in QSAR modelling and therefore it has started to be used by other researchers, allowing the public the download of this result in the DEMETRA web site.
As we have mentioned there are available several databases, which contains similar information. But the data is not always comparable, rationally structured or exact. A thorough revision of the data with a strict filtering was necessary in order to assure the goodness of the data to be employed. Precisely a big deal of the work performed within DEMETRA project has been directed to collect and verify the integrity of the data, providing to third parties a reliable source of information rationally structured.
This result cannot give a material benefit in economical terms, but it is a useful hint for those organizations involved in the pesticide development. This result provides a reliable source of data that can be used in several ways. It is a ready-to-use source of data, for evaluation of the state of the art about pesticide environmental toxicity for Rainbow trout. There are other applications like the development of new QSAR models useful to complement the models presented as results 38655, 38656, 38657, 38658 and 38659.
It is as well a source of reliable data ready to be employed within the developing of new QSAR approaches.
The result "A combined QSAR model for pesticides to predict Dietary Toxicity for Bobwhite Quail (Colinus virginianus) - 38658" is given in the form of a fully predictive QSAR model built by means the combination of two individual QSAR models. The acute oral quail toxicity hybrid model has been obtained with GMDH (a self-organizative methodology of function fitting). Inputs for this model were one Partial Least Squares and four Artificial Neural Networks individual models.
The basic idea of the hybrid model, which merges different points of view and combines the capabilities of different algorithms, is that different models can be more or less powerful in one or another aspect, and that they can be improved by combining positive performances of individual models. The target of the combined model is to cover as much as possible the space of the chemicals it has to model, reducing the mistakes.
These individual models were built using 98 pesticides as training set whose toxicity values were obtained from the more trustworthy pesticide databases (see TIP corresponding to Data of pesticide toxicity, structures and chemical descriptors: Dietary Toxicity for Bobwhite Quail (Colinus virginianus) - 38665.
This result is implemented as a part of a Java applet, also able to run as standalone version, whose only input is the molecular descriptors of the new pesticide to be predicted.
The present result fulfils completely the quality checkpoints marked by OECD and offers a good alternative for supporting the progressive reduction of animal experimentation covering the lack of proper QSAR models for regulatory purposes in the pesticide risk assessment. Being one of the first successful approaches in this area, this model currently has an advantageous position to successfully start to be used by regulatory bodies.
The combined QSAR model for dietary toxicity, bobwhite quail is in line with the recent EU legislative initiative REACH on the possible use of QSAR models as an alternative animal experimentation.
The main idea that underlies in the whole development of this model is creating a tool to be used (not only formally, but in practice) within the Pesticide Directive 91/414, thus a crucial point of the project involved a deep evaluation of criteria for its use.
QSAR models, eventually evaluated for regulatory purposes, that have been developed so far use common QSAR criteria not specific for regulatory purposes. This places the present model in an advantageous position due to its correct timing to the legislation, and makes of it a desirable tool for all the agents involved in risk assessment.
The major user category we have identified within the DEMETRA project is regulatory body.
Non-governmental agencies are also major potential users of the models, for issues similar to those of regulators.
Another important category is industry in the field of plan protection products.
Another major category of users is academy and research institutes.
The first steps in result dissemination has been already taken organizing an European workshop. Members of key institutions have been invited to this meeting covering most of the regulatory bodies and industries dealing with pesticides at European level.
From the ethical point of view this result can help to reduce the suffering derived to the exposure of rainbow trouts to non tested compounds. The use of our free model is cheaper than performing animal experimentation and there is a social concern that can be fulfilled by our model.
It helps to reduce the time in assessing the environmental risk of new pesticides/chemicals, the budget foreseen for experimentation and the material, energy and space necessary to perform the experimental assays. Additionally these animal assays need big infrastructures since it is necessary to store a medium size vertebrate bird and the infrastructures to maintain them properly. Since the QSAR model reduces the number of experimental tests this results in a significance reduction of the expenses.
Additionally this model can help to boost the research in new pesticides. This model allows the evaluation of environmental risks in a prognostic way, therefore it is not necessary to perform the syntheses of the compound. This fact allows to the industries to deal with a higher amount of chemicals candidates to become a pesticide in the market. Also it might help to evaluate metabolites, allowing a more precise knowledge of the mechanistic features of the environmental risks.
The result "combined QSAR model for pesticides to predict Acute Toxicity for Rainbow Trout (Oncorhynchus myskiss) 38655" is given in the form of a fully predictive QSAR model built by means the combination of different individual QSAR models. The trout hybrid model has been obtained with GMDH (a self-organizative methodology of function fitting). Inputs for this model were a Partial Least Squares and two Artificial Neural Networks individual models. The basic idea of the hybrid model, which merges different points of view and combines the capabilities of different algorithms, is that different models can be more or less powerful in one or another aspect, and that they can be improved by combining positive performances of individual models. The target of the combined model is to cover as much as possible the space of the chemicals it has to model, reducing the mistakes.
These individual models were built using 229 pesticides as training set whose toxicity values were obtained from the more trustworthy pesticide databases (see TIP corresponding to Data of pesticide toxicity, structures and chemical descriptors: Acute Toxicity for Rainbow Trout (Oncorhynchus myskiss) 38662).
This result is implemented as a part of a Java applet, also able to run as standalone version, whose only input is the molecular descriptors of the new pesticide to be predicted.
The present result fulfils completely the quality checkpoints marked by OECD and offers a good alternative for supporting the progressive reduction of animal experimentation covering the lack of proper QSAR models for regulatory purposes in the pesticide risk assessment. Being one of the first successful approaches in this area, this model currently has an advantageous position to successfully start to be used by regulatory bodies.
The combined QSAR model for Rainbow Trout is in line with the recent EU legislative initiative REACH on the possible use of QSAR models as an alternative animal experimentation.
The main idea that underlies in the whole development of this model is creating a tool to be used (not only formally, but in practice) within the Pesticide Directive 91/414, thus a crucial point of the project involved a deep evaluation of criteria for its use.
QSAR models, eventually evaluated for regulatory purposes, that have been developed so far use common QSAR criteria not specific for regulatory purposes.
This places the present model in an advantageous position due to its correct timing to the legislation, and makes of it a desirable tool for all the agents involved in risk assessment.
The major user category we have identified within the DEMETRA project is regulatory body.
Non-governmental agencies are also major potential users of the models, for issues similar to those of regulators.
Another important category is industry in the field of plan protection products.
Another major category of users is academy and research institutes.
The first steps in result dissemination has been already taken organizing an European workshop. Members of key institutions have been invited to this meeting covering most of the regulatory bodies and industries dealing with pesticides at European level.
From the ethical point of view this result can help to reduce the suffering derived to the exposure of rainbow trouts to non tested compounds. The use of our free model is cheaper than performing animal experimentation and there is a social concern that can be fulfilled by our model.
It helps to reduce the time in assessing the environmental risk of new pesticides/chemicals, the budget foreseen for experimentation and the material, energy and space necessary to perform the experimental assays. Additionally these animal assays need big infrastructures since it is necessary to store big tanks refilled with fresh water and with high amounts of energy for maintenance of oxygen and temperature. Since the QSAR model reduces the number of experimental tests this results in a significance reduction of the expenses.
Additionally this model can help to boost the research in new pesticides. This model allows the evaluation of environmental risks in a prognostic way, therefore it is not necessary to perform the syntheses of the compound. This fact allows to the industries to deal with a higher amount of chemicals candidates to become a pesticide in the market. Also it might help to evaluate metabolites, allowing a more precise knowledge of the mechanistic features of the environmental risks.
The result "The NIKE tool for QSAR modelling 38667" is a software tool tailored for toxicity prediction of molecules of pesticides and related compounds.
The software provides functions for integration of the knowledge acquired in Demetra project in a homogeneous manner using the best algorithms obtained as the basis for hybrid combinative models to be used for predictive purposes.
The prototype NIKE allows processing of chemical compounds one by one for prediction of toxicity against five endpoints: acute toxicity for Rainbow Trout (Oncorhynchus mykiss): LC50 96-hours exposure; acute toxicity for Water Flea (Daphnia Magna): LC50 48-hours exposure; acute oral toxicity for Bobwhite Quail (Colinus virginianus): LD50 14-days exposure; dietary toxicity for Bobwhite Quail (Colinus virginianus): LD50 8-days exposure; acute contact toxicity for Honey Bee (Apis melifera): LD50 48-hours of exposure.
The input is the chemical structure of the molecule, characterized by a list of numerical chemical descriptors. The algorithms, as Quantitative Structure-Activity Relationships (QSARs), output the estimated toxicity value. The values outside the expertise domain of the predictive models are also indicated.
The software tool is written in JavaTM, it can run on any machine supplying Java or Java 2 runtime environment (JRE) v. 1.4 or later. The prototype is available and provided both as downloadable, stand-alone Java application and Java applet, running within a web browser using the Java Plug-in (Microsoft ® Internet Explorer, Netscape Navigator ®, Mozilla, Opera, etc.). The software package can be downloaded from the Demetra official web portal: http://www.demetra-tox.net
The result "A combined QSAR model for pesticides to predict Acute Oral Toxicity for Bobwhite Quail (Colinus virginianus) - 38657" is given in the form of a fully predictive QSAR model built by means the combination of two individual QSAR models. The acute oral quail toxicity hybrid model has been obtained with the ruled based approach (a non continuous function that merges different individual models). Inputs for this model were a Partial Least Squares and an in-house model based on molecular invariants presence.
The basic idea of the hybrid model, which merges different points of view and combines the capabilities of different algorithms, is that different models can be more or less powerful in one or another aspect, and that they can be improved by combining positive performances of individual models. The target of the combined model is to cover as much as possible the space of the chemicals it has to model, reducing the mistakes.
These individual models were built using 96 pesticides as training set whose toxicity values were obtained from the more trustworthy pesticide databases (see TIP corresponding to Data of pesticide toxicity, structures and chemical descriptors: Acute Oral Toxicity for Bobwhite Quail (Colinus virginianus) - 38664.
This result is implemented as a part of a Java applet, also able to run as standalone version, whose only input is the molecular descriptors of the new pesticide to be predicted.
The present result fulfils completely the quality checkpoints marked by OECD and offers a good alternative for supporting the progressive reduction of animal experimentation covering the lack of proper QSAR models for regulatory purposes in the pesticide risk assessment. Being one of the first successful approaches in this area, this model currently has an advantageous position to successfully start to be used by regulatory bodies.
The combined QSAR model for Acute oral toxicity, bobwhite quail is in line with the recent EU legislative initiative REACH on the possible use of QSAR models as an alternative animal experimentation.
The main idea that underlies in the whole development of this model is creating a tool to be used (not only formally, but in practice) within the Pesticide Directive 91/414, thus a crucial point of the project involved a deep evaluation of criteria for its use.
QSAR models, eventually evaluated for regulatory purposes, that have been developed so far use common QSAR criteria not specific for regulatory purposes. This places the present model in an advantageous position due to its correct timing to the legislation, and makes of it a desirable tool for all the agents involved in risk assessment.
The major user category we have identified within the DEMETRA project is regulatory body.
Non-governmental agencies are also major potential users of the models, for issues similar to those of regulators.
Another important category is industry in the field of plan protection products.
Another major category of users is academy and research institutes.
The first steps in result dissemination has been already taken organizing an European workshop. Members of key institutions have been invited to this meeting covering most of the regulatory bodies and industries dealing with pesticides at European level.
From the ethical point of view this result can help to reduce the suffering derived to the exposure of rainbow trouts to non tested compounds. The use of our free model is cheaper than performing animal experimentation and there is a social concern that can be fulfilled by our model.
It helps to reduce the time in assessing the environmental risk of new pesticides/chemicals, the budget foreseen for experimentation and the material, energy and space necessary to perform the experimental assays. Additionally these animal assays need big infrastructures since it is necessary to store a medium size vertebrate and the infrastructures to maintain them in good health and fed properly. Since the QSAR model reduces the number of experimental tests this results in a significance reduction of the expenses.
Additionally this model can help to boost the research in new pesticides. This model allows the evaluation of environmental risks in a prognostic way, therefore it is not necessary to perform the syntheses of the compound. This fact allows to the industries to deal with a higher amount of chemicals candidates to become a pesticide in the market. Also it might help to evaluate metabolites, allowing a more precise knowledge of the mechanistic features of the environmental risks.
The result "Data of pesticide toxicity, structures and chemical descriptors: Acute Oral Toxicity for Bobwhite Quail (Colinus virginianus) - 38664" is composed by the complete series of compounds used to build the result named A combined QSAR model for pesticides to predict Acute Oral Toxicity for Bobwhite Quail (Colinus virginianus) 38657. Within this result a complete description of the compounds is given. The description provided can be divided into three levels: chemical, revised structures of the pesticides; mathematical, represented by the molecular descriptors which are the projection of the chemical space into a mathematical space; toxicological, we present a highly accurate set of toxicity values related to the compounds described.
We supply this result for the whole set of 96 pesticides selected to build the result 38657- in the more common format for store such a kind of information. The available files are one of single text with sdf extension, providing both chemical and toxicological information, and one excel file containing several worksheets for the mathematical representation.
The most suitable sources of toxicological data to be collected in this project were the EPA-OPP, SEEM and BBA databases.
In practice we used U.S. EPA-OPP data. During the project OECD published criteria for the validation of QSAR; one of these criteria states that components of the model have to be given, which includes the toxicity data.
A first essential characteristic regards the number of chemical with toxicity data available. Among the available databases the EPA-OPP was the one with more data and was selected as primarily source for the data.
Additionally several sources of ecotoxicological data have been identified and taken into account to produce the datasets. Only high quality data have been used and compared between databases, as a further check. We defined a procedure to identify a single toxicity value in a reproducible way when multiple values were available. We adopted a conservative approach using the lowest value since this choice is typically preferred in the E.U.
We conclude that the selected values are reliable, with low internal variability as we eliminated compounds with a toxicity range exceeding a factor of four.
We have identified as potential users for this result the very owners of the databases employed within this project. Indeed this result can be employed as an external audit of the results, allowing them to provide more accurate information. Besides, the data has been collected and stored in a systematic way that might be useful for regulatory bodies and industries, granting them a fast and easy source of data related with rainbow trout toxicity for pesticides.
A third kind of potential users are academic researches working in modelling. For such a kind of research a reliable source of data is of the outmost importance, this result grants an outstanding set of data useful for assessing the validity on brand new approaches, allowing the calibration of material and methodologies for researchers not only working in pesticides toxicity. Since the data must be public available this result is an obvious benefit for the social welfare.
The dissemination of this result is oriented in two directions. We have presented the result during the European workshop. The attendants of this workshop are placed in key institutions related with pesticides development.
We have sent this result to different challenges in QSAR modelling and therefore it has started to be used by other researchers, allowing the public the download of this result in the DEMETRA web site.
As we have mentioned there are available several databases, which contains similar information. But the data is not always comparable, rationally structured or exact. A thorough revision of the data with a strict filtering was necessary in order to assure the goodness of the data to be employed. Precisely a big deal of the work performed within DEMETRA project has been directed to collect and verify the integrity of the data, providing to third parties a reliable source of information rationally structured.
This result cannot give a material benefit in economical terms, but it is a useful hint for those organizations involved in the pesticide development. This result provides a reliable source of data that can be used in several ways. It is a ready-to-use source of data, for evaluation of the state of the art about pesticide environmental toxicity for Rainbow trout. There are other applications like the development of new QSAR models useful to complement the models presented as results 38655, 38656, 38657, 38658 and 38659.
It is as well a source of reliable data ready to be employed within the developing of new QSAR approaches.
The result "A combined QSAR model for pesticides to predict Acute Toxicity for Water Flea (Daphnia magna) - 38656" is given in the form of a fully predictive QSAR model built by means the combination of different individual QSAR models. The Daphnia hybrid model has been obtained with the ruled based approach (a non continuous function that merges different individual models). Inputs for this model were a Partial Least Squares and two Artificial Neural Networks individual models.
The basic idea of the hybrid model, which merges different points of view and combines the capabilities of different algorithms, is that different models can be more or less powerful in one or another aspect, and that they can be improved by combining positive performances of individual models. The target of the combined model is to cover as much as possible the space of the chemicals it has to model, reducing the mistakes.
These individual models were built using 220pesticides as training set whose toxicity values were obtained from the more trustworthy pesticide databases (see TIP corresponding to Data of pesticide toxicity, structures and chemical descriptors: Acute Toxicity for Water Flea (Daphnia magna) - 38663.
This result is implemented as a part of a Java applet, also able to run as standalone version, whose only input is the molecular descriptors of the new pesticide to be predicted.
The present result fulfils completely the quality checkpoints marked by OECD and offers a good alternative for supporting the progressive reduction of animal experimentation covering the lack of proper QSAR models for regulatory purposes in the pesticide risk assessment. Being one of the first successful approaches in this area, this model currently has an advantageous position to successfully start to be used by regulatory bodies.
The combined QSAR model for Daphnia Magna is in line with the recent EU legislative initiative REACH on the possible use of QSAR models as an alternative animal experimentation.
The main idea that underlies in the whole development of this model is creating a tool to be used (not only formally, but in practice) within the Pesticide Directive 91/414, thus a crucial point of the project involved a deep evaluation of criteria for its use.
QSAR models, eventually evaluated for regulatory purposes, that have been developed so far use common QSAR criteria not specific for regulatory purposes. This places the present model in an advantageous position due to its correct timing to the legislation, and makes of it a desirable tool for all the agents involved in risk assessment.
The major user category we have identified within the DEMETRA project is regulatory body.
Non-governmental agencies are also major potential users of the models, for issues similar to those of regulators.
Another important category is industry in the field of plan protection products.
Another major category of users is academy and research institutes.
The first steps in result dissemination has been already taken organizing an European workshop. Members of key institutions have been invited to this meeting covering most of the regulatory bodies and industries dealing with pesticides at European level.
From the ethical point of view this result can help to reduce the suffering derived to the exposure of rainbow trouts to non tested compounds. The use of our free model is cheaper than performing animal experimentation and there is a social concern that can be fulfilled by our model.
It helps to reduce the time in assessing the environmental risk of new pesticides/chemicals, the budget foreseen for experimentation and the material, energy and space necessary to perform the experimental assays. Additionally these animal assays need big infrastructures since it is necessary to store big tanks refilled with fresh water and with high amounts of energy for maintenance of oxygen and temperature. Since the QSAR model reduces the number of experimental tests this results in a significance reduction of the expenses.
Additionally this model can help to boost the research in new pesticides. This model allows the evaluation of environmental risks in a prognostic way, therefore it is not necessary to perform the syntheses of the compound. This fact allows to the industries to deal with a higher amount of chemicals candidates to become a pesticide in the market. Also it might help to evaluate metabolites, allowing a more precise knowledge of the mechanistic features of the environmental risks.
The result "Data of pesticide toxicity, structures and chemical descriptors: Acute Toxicity for Rainbow Trout (Oncorhynchus myskiss) 38662" is composed by the complete series of compounds used to build the result named A combined QSAR model for pesticides to predict Acute Toxicity for Rainbow Trout (Oncorhynchus myskiss) - 38655. Within this result a complete description of the compounds is given. The description provided can be divided into three levels: chemical, revised structures of the pesticides; mathematical, represented by the molecular descriptors which are the projection of the chemical space into a mathematical space; toxicological, we present a highly accurate set of toxicity values related to the compounds described.
We supply this result for the whole set of 229 pesticides selected to build the result 38655- in the more common format for store such a kind of information. The available files are one of single text with sdf extension, providing both chemical and toxicological information, and one excel file containing several worksheets for the mathematical representation.
The most suitable sources of toxicological data to be collected in this project were the EPA-OPP, SEEM and BBA databases.
In practice we used U.S. EPA-OPP data. During the project OECD published criteria for the validation of QSAR; one of these criteria states that components of the model have to be given, which includes the toxicity data.
A first essential characteristic regards the number of chemical with toxicity data available. Among the available databases the EPA-OPP was the one with more data and was selected as primarily source for the data.
Additionally several sources of ecotoxicological data have been identified and taken into account to produce the datasets. Only high quality data have been used and compared between databases, as a further check. We defined a procedure to identify a single toxicity value in a reproducible way when multiple values were available. We adopted a conservative approach using the lowest value since this choice is typically preferred in the E.U.
We conclude that the selected values are reliable, with low internal variability as we eliminated compounds with a toxicity range exceeding a factor of four.
We have identified as potential users for this result the very owners of the databases employed within this project. Indeed this result can be employed as an external audit of the results, allowing them to provide more accurate information. Besides, the data has been collected and stored in a systematic way that might be useful for regulatory bodies and industries, granting them a fast and easy source of data related with rainbow trout toxicity for pesticides.
A third kind of potential users are academic researches working in modelling. For such a kind of research a reliable source of data is of the outmost importance, this result grants an outstanding set of data useful for assessing the validity on brand new approaches, allowing the calibration of material and methodologies for researchers not only working in pesticides toxicity. Since the data must be public available this result is an obvious benefit for the social welfare.
The dissemination of this result is oriented in two directions. We have presented the result during the European workshop. The attendants of this workshop are placed in key institutions related with pesticides development.
We have sent this result to different challenges in QSAR modelling and therefore it has started to be used by other researchers, allowing the public the download of this result in the DEMETRA web site.
As we have mentioned there are available several databases, which contains similar information. But the data is not always comparable, rationally structured or exact. A thorough revision of the data with a strict filtering was necessary in order to assure the goodness of the data to be employed. Precisely a big deal of the work performed within DEMETRA project has been directed to collect and verify the integrity of the data, providing to third parties a reliable source of information rationally structured.
This result cannot give a material benefit in economical terms, but it is a useful hint for those organizations involved in the pesticide development. This result provides a reliable source of data that can be used in several ways. It is a ready-to-use source of data, for evaluation of the state of the art about pesticide environmental toxicity for Rainbow trout. There are other applications like the development of new QSAR models useful to complement the models presented as results 38655, 38656, 38657, 38658 and 38659.
It is as well a source of reliable data ready to be employed within the developing of new QSAR approaches.
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