J Devillers

CTIS Inc., Maryland, United States

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Publications (97)156.05 Total impact

  • J Devillers, P Pandard, B Richard
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    ABSTRACT: Biodegradation is an important mechanism for eliminating xenobiotics by biotransforming them into simple organic and inorganic products. Faced with the ever growing number of chemicals available on the market, structure-biodegradation relationship (SBR) and quantitative structure-biodegradation relationship (QSBR) models are increasingly used as surrogates of the biodegradation tests. Such models have great potential for a quick and cheap estimation of the biodegradation potential of chemicals. The Estimation Programs Interface (EPI) Suite™ includes different models for predicting the potential aerobic biodegradability of organic substances. They are based on different endpoints, methodologies and/or statistical approaches. Among them, Biowin 5 and 6 appeared the most robust, being derived from the largest biodegradation database with results obtained only from the Ministry of International Trade and Industry (MITI) test. The aim of this study was to assess the predictive performances of these two models from a set of 356 chemicals extracted from notification dossiers including compatible biodegradation data. Another set of molecules with no more than four carbon atoms and substituted by various heteroatoms and/or functional groups was also embodied in the validation exercise. Comparisons were made with the predictions obtained with START (Structural Alerts for Reactivity in Toxtree). Biowin 5 and Biowin 6 gave satisfactorily prediction results except for the prediction of readily degradable chemicals. A consensus model built with Biowin 1 allowed the diminution of this tendency.
    SAR and QSAR in environmental research 12/2013; 24(12):979-93. · 1.68 Impact Factor
  • J P Doucet, A Doucet-Panaye, J Devillers
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    ABSTRACT: The juvenile hormone esterase (JHE) regulates juvenile hormone titre in insect hemolymph during its larval development. It has been suggested that JHE could be targeted for use in insect control. This enzyme can also be considered as involved in the phenomenon of endocrine disruption by xenobiotics in beneficial insects. Consequently, there is a need to know the characteristics of the molecules able to act on the JHE. Trifluoromethylketones (TFKs) are the most potent JHE inhibitors found to date and different quantitative structure-activity relationships (QSARs) have been derived for this group of chemicals. In this context, a set of 181 TFKs (118 active and 63 inactive compounds), tested on Trichoplusia ni for their JHE inhibition activity and described by physico-chemical descriptors, was split into different training and test sets to derive structure-activity relationship (SAR) models from support vector classification (SVC). A SVC model including 88 descriptors and derived from a Gaussian kernel was selected for its predictive performances. Another model computed only with 13 descriptors was also selected due to its mechanistic interpretability. This study clearly illustrates the difficulty in capturing the essential structural characteristics of the TFKs explaining their JHE inhibitory activity.
    SAR and QSAR in environmental research 05/2013; · 1.68 Impact Factor
  • James Devillers
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    ABSTRACT: Structure-activity relationship (SAR) and quantitative structure-activity relationship (QSAR) models are increasingly used in toxicology, ecotoxicology, and pharmacology for predicting the activity of the molecules from their physicochemical properties and/or their structural characteristics. However, the design of such models has many traps for unwary practitioners. Consequently, the purpose of this chapter is to give a practical guide for the computation of SAR and QSAR models, point out problems that may be encountered, and suggest ways of solving them. Attempts are also made to see how these models can be validated and interpreted.
    Methods in molecular biology (Clifton, N.J.) 01/2013; 930:3-27. · 1.29 Impact Factor
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    ABSTRACT: A tight control of juvenile hormone (JH) titre is crucial during the life cycle of a holometabolous insect. JH metabolism is made through the action of enzymes, particularly the juvenile hormone esterase (JHE). Trifluoromethylketones (TFKs) are able to inhibit this enzyme to disrupt the endocrine function of the targeted insect. In this context, a set of 96 TFKs, tested on Trichoplusia ni for their JHE inhibition, was split into a training set (n = 77) and a test set (n = 19) to derive a QSAR model. TFKs were initially described by 42 CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) descriptors, but a feature selection process allowed us to consider only five descriptors encoding the structural characteristics of the TFKs and their reactivity. A classical and spline regression analysis, a three-layer perceptron, a radial basis function network and a support vector regression were experienced as statistical tools. The best results were obtained with the support vector regression (r(2) and r(test)(2) = 0.91). The model provides information on the structural features and properties responsible for the high JHE inhibition activity of TFKs.
    SAR and QSAR in environmental research 03/2012; 23(3-4):357-69. · 1.68 Impact Factor
  • J Devillers, E Mombelli, R Samsera
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    ABSTRACT: More than 20 years ago, Ashby and Tennant showed the interest of structural alerts for the prediction of the carcinogenicity of chemicals. These structural alerts are functional groups or structural features of various sizes that are linked to the level of carcinogenicity of chemicals. Since this pioneering work it has been possible to refine the alerts over time, as more experimental results have become available and additional mechanistic insights have been gained. To date, one of the most advanced lists of structural alerts for evaluating the carcinogenic potential of chemicals is the list proposed by Benigni and Bossa and that is implemented as a rule-based system in Toxtree and in the OECD QSAR Application Toolbox. In order to gain insight into the applicability of this system to the detection of potential carcinogens we screened about 200 pesticides and biocides showing a high structural diversity. Prediction results were compared with experimental data retrieved from an extensive bibliographical review. The prediction correctness was only equal to 60.14%. Attempts were made to analyse the sources of mispredictions.
    SAR and QSAR in environmental research 03/2011; 22(1-2):89-106. · 1.68 Impact Factor
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    ABSTRACT: Losses of foraging bees are sometimes attributed to altered flight pattern between a meliferous plant treated with an insecticide and the hive. Only a limited number of studies has investigated the impact of pesticides on homing flight due to the difficulty of measuring the flight time between the food source and the hive. Monitoring the flights of the foraging bees needs their individual identification. The number of bees monitored simultaneously and the time span during which observations can be made limit most of the monitoring techniques. However, techniques of automatic tracking and identification of individuals have the potential to revolutionize the study of the ecotoxicological effects of xenobiotics on the bee behaviors. Radio Frequency Identification (RFID) offer numerous advantages such as an unlimited number of codes, a large number of simultaneous recording, and a quick reading, especially through materials (e.g., wood). The aim of this study was to show how the RFID device can be used to study the effects of pesticides on both the behavioral traits and the lifespan of bees. In this context, we have developed a method under tunnel to automatically record the displacements of foragers individualized with RFID tags and to detect the alteration of the flight pattern between an artificial feeder and the hive. Fipronil was selected as test substance due to the lack of information on the effects of this insecticide on the foraging behavior of free-flying bees. We showed that oral treatment of 0.3 ng of fipronil per bee (LD50/20) reduced the number of foraging trips. The strengths of our approach were briefly discussed.
    Ecotoxicology 03/2011; 20(2):429-37. · 2.77 Impact Factor
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    ABSTRACT: Centre de localisation : Centre de Recherche PACA, 84914 AVIGNON CEDEX 9, FRA , Comité de lecture : false , Compléments : Reprise ProdINRA 1 : Langue du Titre de la monographie : fra Les auteurs monographiques : INRA - Réseau des Ecotoxicologues de l'INRA Les auteurs monographiques : INRA - Réseau Ecodynamique des Micropolluants , Cote de localisation : 11-Pub39 , Date de début de l'événement : 2011-11-07 , Date de fin de l'évenement : 2011-11-09 , Date de validation : Tue May 29 08:37:05 CEST 2012 , Identifiant : 50902 , Identifiant mot-clé : 11377, 21013, 2752, 89321, 1352, 1368, 9784, 10152, 2925, 74519, 58636, 42309 , Identifiant ProdInra1 : PROD2012c18e4011 , Langue du titre : fra , Mot-clé principal : maïs, zea mays, brassica napus var oleifera, semence, apidae, apis mellifera, hymenoptera, insecticide systémique, butineuse, thiamethoxam, comportement, marquage , Pays de l'éditeur : FRA , Pays de l'événement : FRA , Public visé : Scientifique , The following values have no corresponding Zotero field: Author Address: [DECOURTYE, Axel] UMT PrADE, UR 406 Abeilles et Environnement, Association de Coordination Technique Agricole, Avignon, FRA Author Address: [DECOURTYE, Axel; Béguin, Maxime; henry, Mickaël] UMR 0406 UR 0406 Abeilles et Environnement, AVIGNON CEDEX 9, Avignon, France Author Address: [Béguin, Maxime; Jourdan, Pascal] UMT PrADE, UR 406 Abeilles et Environnement, Association de développement de l'Apiculture Provençale, Avignon, FRA Author Address: [Odoux, Jean Francois; REQUIER, Fabrice; Aupinel, Pierrick] UE 1255 UE 1255 Unité expérimentale Entomologie, SURGERES, Saint-Pierre-D'Amilly Author Address: [Brun, François] UMR AGIR, Association de Coordination Technique Agricole, Castanet Tolosan, FRA Author Address: [Gauthier, Monique] CNRS, CRCA, Université Toulouse 3, Castanet Tolosan, FRA Author Address: [Devillers, James] Centre de Traitement de l'Information Scientifique, Rillieux-la-Pape, FRA<br/, Titre des actes : 4ème Séminaire d'Ecotoxicologie de l'INRA , Type de communication avec actes : Résumé , Type d'événement : Séminaire , Unité de localisation : UR 0406 Abeilles et Environnement
    4ème Séminaire d’Ecotoxicologie de l’INRA; 01/2011
  • E Mombelli, J Devillers
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    ABSTRACT: The OECD (Q)SAR Application Toolbox and Toxtree are software tools used in regulatory toxicology to fill gaps in (eco)toxicity data. They include different SAR and QSAR models for estimating (eco)toxicological endpoints. Among them, the Benigni/Bossa rule-based system is proposed to characterize the carcinogenic potential of chemicals. Our study evaluates the predictive performance that can be expected from the OECD (Q)SAR Toolbox and Toxtree when analysing chemicals by means of the structural alerts coded within the Benigni/Bossa rule-based system for carcinogenicity and the associated QSAR model (QSAR8). These evaluations have been carried out thanks to a large collection of chemicals retrieved from original publications and public databases. Overall, our findings confirm the performance of the system of structural alerts while suggesting that the sensitivity of QSAR8, as implemented in the two tools, is lower than what was previously reported. They also indicate that attention has to be paid when interpreting the output of the two tools because of possible malfunctions involving the coding of two-dimensional structures. A set of possible modulating factors for the structural alert identifying polycyclic aromatic hydrocarbons is also proposed together with candidates for putative new structural alerts not included in the tested tools.
    SAR and QSAR in environmental research 10/2010; 21(7-8):731-52. · 1.68 Impact Factor
  • J Devillers, E Mombelli
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    ABSTRACT: The OECD QSAR Application Toolbox versions 1.1.01 and 1.1.02 and Toxtree version 1.60, which were developed for facilitating the practical use of (Q)SAR approaches by regulators, include a mechanistic SAR model for predicting the mutagenicity of α-β unsaturated aliphatic aldehydes. The aim of this study was to estimate the interest and limitations of this model. First, the model was re-computed to check its transparency and to verify its statistical validity. Then, the model implemented in the two software tools was tested on 34 chemicals not previously used for its design and for which experimental mutagenic activity data were available in the literature. A critical analysis of the results was performed and the practical interest of the model was discussed.
    SAR and QSAR in environmental research 10/2010; 21(7-8):771-83. · 1.68 Impact Factor
  • J Devillers, E Mombelli
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    ABSTRACT: The Ames Salmonella typhimurium mutagenicity assay is a short-term bacterial reverse mutation test that was designed to detect mutagens. For several decades, it has been used in research laboratories and by regulatory agencies throughout the world for the detection and characterization of potential mutagens among natural products and man-made chemicals. Faced with the ever-growing number of chemicals available on the market, congeneric and non-congeneric (Q)SAR models have been designed from Ames test results obtained on specific S. typhimurium strains such as TA 100 or TA 98. Such models have great potential for a quick and cheap identification and classification of large numbers of potential chemical mutagens. The OECD QSAR Application Toolbox and Toxtree, which were developed for facilitating the practical use of (Q)SAR approaches in regulatory contexts, include two mechanistic SAR models for predicting the mutagenicity of aromatic amines and α-β unsaturated aliphatic aldehydes. The aim of this study was to estimate the interest and limitations of the former model. The model was first re-computed to check its transparency and to verify its statistical validity. Then, it was tested on about 150 chemicals not previously used for the design of the model but belonging to its domain of application. A critical analysis of the results was performed and proposals were made for increasing the model performances.
    SAR and QSAR in environmental research 10/2010; 21(7-8):753-69. · 1.68 Impact Factor
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    ABSTRACT: The use of agent-based models (ABMs) is steadily increasing in all the disciplines including environmental chemistry and toxicology. This growth is mainly driven by their ability to address problems that conventional modelling techniques cannot, such as the change of scale or the emergence of unanticipated phenomena resulting from interactions between their constitutive goal-directed agents. After a brief introduction on the basic principles of agent-based modelling and the presentation of selected case studies, the main software resources available on the Internet are presented. An attempt is made to estimate the complexity of these tools versus their potentialities and flexibility.
    SAR and QSAR in environmental research 04/2010; 21(3-4):337-50. · 1.68 Impact Factor
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    Axel Decourtye, James Devillers
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    ABSTRACT: This chapter reviews the available data on the toxicity of neonicotinoid insecticides to bees that are the prominent and the most economically important group of pollinators worldwide. Classical and new methods developed to take into account the characteristics and different types of effects of the neonicotinoid insecticides to bees are described. The available toxicity results are critically analyzed. Thus, the nitro-substituted compounds (clothianidin, dinotefuran, imidacloprid and its metabolites, thiamethoxam, nitenpyram) appear the most toxic to bees. The cyano-substituted neonicotinoids seem to exhibit a much lower toxicity (acetamiprid and thiacloprid). The chapter ends with suggestions for additional studies aiming at better assess the hazard of this important insecticide family to bees.
    Advances in experimental medicine and biology 01/2010; 683:85-95. · 1.83 Impact Factor
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    ABSTRACT: Centre de localisation : Centre de recherche de Poitou-Charentes, 86600 Lusignan, FRA , Comité de lecture : false , Cote de localisation : DOCLUS-TP10704 , Date de validation : Fri Jun 04 09:31:08 CEST 2010 , Identifiant : 34353 , Identifiant mot-clé : 1352, 7267, 58646, 47969, 33236 , Identifiant ProdInra1 : PROD20103469cf43 , ISSN : 0335-3710 , Langue du résumé : fra , Langue du titre : fra , Mot-clé principal : apidae, entrée, comportement animal, télédétection, ruche , Public visé : Scientifique , The following values have no corresponding Zotero field: Author Address: [Bagnis, Camille; Fourrier, Julie; Decourtye, Axel] Institut Claude Bourgelat, Association de Coordination Technique Agricole, Marcy-l’Etoile, FRA Author Address: [Brun, François] UMR 1248 UMR 1248 UMR INRA / ENSAT : AGrosystèmes et développement terrItoRial, CASTANET-TOLOSAN CEDEX, Auzeville, France Author Address: [Devillers, James] Centre Traitement Informatique Scientifique, Rillieux-La-Pape, FRA Author Address: [Aupinel, Pierrick] UE 1255 UE 1255 Unité expérimentale Entomologie, Saint-Pierre-D'Amilly Author Address: [Gauthier, Monique] UMR CRCA Centre de recherches sur la cognition animale, Centre National de la Recherche Scientifique, Toulouse, FRA , Unité de localisation : 0002 Documentation de centre
    Bull. Tech. Apic. 01/2010; 36:98-109.
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    ABSTRACT: LD50 tests on rat and mouse are commonly used to express the relative hazard associated with the acute toxicity of new and existing substances. These tests are expensive, time consuming, and actively fought by Animal Rightists. Consequently, there is a need to find alternative methods. If the design of QSAR models can be used as surrogate, the search for interspecies correlations also represents a valuable alternative to the classical mammalian laboratory tests. In this chapter, the different toxicity​ = ​ f(ecotoxicity) models available in the literature were first critically analyzed. In a second step, a strong bibliographical investigation was performed to collect oral, intraperitoneal, and intravenous rat and mouse LD50 data for a large collection of structurally diverse chemicals. In the meantime, EC50 data on Vibrio fischeri (MicrotoxTM test) and Daphnia magna were also retrieved from literature. Numerous oral, intraperitoneal, and intravenous rat and mouse toxicity models were derived using Vibrio fischeri and Daphnia magna as independent variables alone or together through a stepwise regression analysis. Most of the models on Daphnia magna were totally new and some of them presented acceptable quality. They outperformed the MicrotoxTM models. The usefulness of the 1-octanol/water partition coefficient (log P) as additional independent variable was also tested. The interest of nonlinear statistical tools for deriving toxicity​ = ​ f (ecotoxicity) models was also experienced. KeywordsInterspecies correlation–Mammalian toxicity– Vibrio fischeri – Daphnia magna –Regression analysis–Nonlinear methods
    08/2009: pages 85-115;
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    James Devillers
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    ABSTRACT: An artificial neural network (ANN) includes nonlinear computational elements called neurons, which are linked by weighted connections. Typically, a neuron receives an input information and performs a weighted summation, which is propagated by an activation function to other neurons through the ANN. Numerous ANN paradigms have been proposed for pattern classification, clustering, function approximation, prediction, optimization, and control. In this chapter, an attempt is made to review the main applications of ANNs in ecotoxicology. Our goal was not to catalog all the models in the field but only to show the diversity of the situations in which these nonlinear tools have proved their interest for modeling the environmental fate and effects of chemicals. KeywordsArtificial neural network–QSPR–QSAR–Environmental contamination–Nonlinear methods
    08/2009: pages 1-28;
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    ABSTRACT: It is now well admitted that a battery of ecotoxicity tests should be designed by accounting for the requirements of a specific scenario such as classification of wastes or remediation efficiency of contaminated soils. The development of a single battery of tests for all applications is thereafter recognized not to be relevant. The selection of tests for constituting a battery may be established according to expert judgments, decision criteria such as cost, ecological relevance, sensitivity of selected organisms, standardization of the methods, implementation of the test protocols or after statistical analysis of test results obtained on a large series of bioassays. In this chapter, a methodological framework, based on the combination of an original multicriteria method called SIRIS and multivariate analyses, is presented for selecting ecotoxicity tests for assessing the level of contamination of soils. The interest of this approach that simultaneously accounts for ecological, technical, and economical constraints is discussed. KeywordsMulticriteria analysis–SIRIS method–Test battery–a priori selection–Soil contamination
    08/2009: pages 117-143;
  • J Devillers, H Devillers
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    ABSTRACT: With the ever-growing number of xenobiotics that can potentially contaminate the environment, the determination of their mammalian toxicity is of prime importance. In this context, LD50 tests on rats and mice have been used for a long time to express the relative hazard associated with the acute toxicity of inorganic and organic chemicals. However, these laboratory tests encounter important hurdles. They are costly, time consuming and actively opposed by animal rights activists. Moreover, new legislation policies, such as REACH (Registration, Evaluation, Authorization and Restriction of Chemicals), aim at reducing the use of toxicity tests on vertebrates. Consequently, there is a need to find alternative methods for estimating the acute mammalian toxicity of chemicals. The quantitative structure-activity relationships (QSARs) and interspecies correlations appear particularly suited to reaching this goal. In this context, this paper reviews more than 150 models aiming at predicting rat and mouse LD50 values from molecular descriptors or (and) ecotoxicity data. The interest of these computational tools is discussed.
    SAR and QSAR in environmental research 07/2009; 20(5-6):467-500. · 1.68 Impact Factor
  • James Devillers
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    ABSTRACT: Artificial neural networks are increasingly used in environmental toxicology to find complex relationships between the ecotoxicity of xenobiotics and their structure or physicochemical properties. The raison d(être of these nonlinear tools is their ability to derive powerful QSARs for molecules presenting different mechanisms of action. In this chapter, the main QSAR models derived for aquatic and terrestrial species are reviewed. Their characteristics and modeling performances are deeply analyzed.
    Methods in molecular biology (Clifton, N.J.) 01/2009; 458:59-77. · 1.29 Impact Factor
  • James Devillers
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    ABSTRACT: Allergic contact dermatitis results for 259 compounds were used for deriving a qualitative structure-activity relationship (SAR) model. Chemicals were described by means of one physicochemical descriptor, one topological index, and twelve structural alerts (i.e., a value of 1 indicated the presence of the structural feature in a molecule, 0 the absence). A three-layer feed forward neural network trained by the back-propagation algorithm was used as statistical engine. The comparison of the simulation performances of the obtained model to those produced by a classical linear discriminant analysis clearly revealed the usefulness of the nonlinear methods of modeling skin sensitization.
    09/2008; 10(3):181-193.
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    ABSTRACT: With the current concern of limiting experimental assays, increased interest now focuses on in silico models able to predict toxicity of chemicals. Endocrine disruptors cover a large number of environmental and industrial chemicals which may affect the functions of natural hormones in humans and wildlife. Structure-activity models are now increasingly used for predicting the endocrine disruption potential of chemicals. In this study, a large set of about 200 chemicals covering a broad range of structural classes was considered in order to categorize their relative binding affinity (RBA) to the androgen receptor. Classification of chemicals into four activity groups, with respect to their log RBA value, was carried out in a cascade of recursive partitioning trees, with descriptors calculated from CODESSA software and encoding topological, geometrical and quantum chemical properties. The hydrophobicity parameter (log P), Balaban index, and descriptors relying on charge distribution (maximum partial charge, nucleophilic index on oxygen atoms, charged surface area, etc.) appear to play a major role in the chemical partitioning. Separation of strongly active compounds was rather straightforward. Similarly, about 90% of the inactive compounds were identified. More intricate was the separation of active compounds into subsets of moderate and weak binders, the task requiring a more complex tree. A comparison was made with support vector machine yielding similar results.
    SAR and QSAR in Environmental Research 01/2008; 19(1-2):129-51. · 1.67 Impact Factor

Publication Stats

1k Citations
156.05 Total Impact Points

Institutions

  • 1991–2013
    • CTIS Inc.
      Maryland, United States
  • 2010
    • Institut national de l'environnement industriel et des risques
      Verneuil, Picardie, France
  • 2003–2006
    • Université Bordeaux 1
      Talence, Aquitaine, France
  • 1987–1989
    • Institut Pasteur
      Lutetia Parisorum, Île-de-France, France
  • 1986–1988
    • Claude Bernard University Lyon 1
      Villeurbanne, Rhône-Alpes, France