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Ninomiya Y, Watanabe H, Yamagishi T, Maruyama-Komoda T, Yamada T, Yamamoto H. Prediction of chronic toxicity of pharmaceuticals in Daphnia magna by combining ortholog prediction, pharmacological effects, and quantitative structure-activity relationship. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 282:116737. [PMID: 39047365 DOI: 10.1016/j.ecoenv.2024.116737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 06/26/2024] [Accepted: 07/12/2024] [Indexed: 07/27/2024]
Abstract
To develop a method for predicting chronic toxicity of pharmaceuticals in Daphnia, we investigated the feasibility of combining the presence of drug-target orthologs in Daphnia magna, classification based on pharmacological effects, and ecotoxicity quantitative structure-activity relationship (QSAR) prediction. We established datasets on the chronic toxicity of pharmaceuticals in Daphnia, including information on therapeutic categories, target proteins, and the presence or absence of drug-target orthologs in D. magna, using literature and databases. Chronic toxicity was predicted using ecotoxicity prediction QSAR (Ecological Structure Activity Relationship and Kashinhou Tool for Ecotoxicity), and the differences between the predicted and measured values and the presence or absence of drug-target orthologs were examined. For pharmaceuticals without drug-target orthologs in D. magna or without expected specific actions, the ecotoxicity prediction QSAR analysis yielded acceptable predictions of the chronic toxicity of pharmaceuticals. In addition, a workflow model to assess the chronic toxicity of pharmaceuticals in Daphnia was proposed based on these evaluations and verified using an additional dataset. The addition of biological aspects such as drug-target orthologs and pharmacological effects would support the use of QSARs for predicting the chronic toxicity of pharmaceuticals in Daphnia.
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Affiliation(s)
- Yoshikazu Ninomiya
- Department of Natural Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba 277-8563, Japan
| | - Haruna Watanabe
- Department of Natural Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba 277-8563, Japan; Health and Environmental Risk Division, National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
| | - Takahiro Yamagishi
- Department of Natural Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba 277-8563, Japan; Health and Environmental Risk Division, National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
| | - Taeko Maruyama-Komoda
- Division of Risk Assessment, Center for Biological and Safety Research, National Institute of Health Science (NIHS), 3-25-26, Tonomachi, Kawasaki-ku, Kawasaki, Kanagawa 210-9501, Japan
| | - Takashi Yamada
- Division of Risk Assessment, Center for Biological and Safety Research, National Institute of Health Science (NIHS), 3-25-26, Tonomachi, Kawasaki-ku, Kawasaki, Kanagawa 210-9501, Japan
| | - Hiroshi Yamamoto
- Department of Natural Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba 277-8563, Japan; Health and Environmental Risk Division, National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
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2
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Xu Z, Zhang L, Wang T, Zhang M, Kang G, Wu S, Liu B. Photocatalytic degradation of organophosphorus flame retardants in aqueous solutions: a review and future prospects. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:52707-52723. [PMID: 39190251 DOI: 10.1007/s11356-024-34766-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 08/16/2024] [Indexed: 08/28/2024]
Abstract
The widespread use of organophosphorus flame retardants (OPFRs) in industrial and household products increases the risk of their environmental exposure, posing a serious threat to ecosystems and human health. Photocatalytic technology has been widely used in wastewater treatment due to its high efficiency, mild reaction conditions, and robustness. This review summarizes the current status of research on photocatalytic degradation of OPFRs, focusing on the effect of different types of catalysts on the degradation efficiency, the effects of pH, and co-existing inorganic and organic ions. And pH and co-existing inorganic mainly affect the active oxygen and the active surface sites of the catalyst. In addition, toxicological calculations of the intermediates of the degradation pathway using T.E.S.T. and ECOSAR showed that photocatalysis could effectively reduce the toxicity of OPFRs. Development of new photocatalytic materials, in-depth study of the degradation mechanism of different catalysts and flame retardants, and attention to practical applications and toxicity issues can be the development direction of future research.
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Affiliation(s)
- Zihui Xu
- School of Environment and Spatial Informatics, China University of Mining & Technology, Xuzhou, 221116, China
| | - Lucheng Zhang
- School of Environment and Spatial Informatics, China University of Mining & Technology, Xuzhou, 221116, China
| | - Tingting Wang
- School of Environment and Spatial Informatics, China University of Mining & Technology, Xuzhou, 221116, China
| | - Mingqing Zhang
- School of Environment and Spatial Informatics, China University of Mining & Technology, Xuzhou, 221116, China.
| | - Gang Kang
- School of Environment and Spatial Informatics, China University of Mining & Technology, Xuzhou, 221116, China
| | - Shilong Wu
- School of Environment and Spatial Informatics, China University of Mining & Technology, Xuzhou, 221116, China
| | - Bingfeng Liu
- School of Environment and Spatial Informatics, China University of Mining & Technology, Xuzhou, 221116, China
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Liu Y, Wang X, Sun Q, Yuan M, Sun Z, Chen L, Zhang Y, Xia S, Zhao J. Enhanced activation of peroxymonosulfate by a floating FeMo 3O x/C 3N 4 photocatalyst under visible-light assistance for oxytetracycline degradation: Performance, mechanisms and comparison with H 2O 2 activation. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 316:120668. [PMID: 36400139 DOI: 10.1016/j.envpol.2022.120668] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 10/20/2022] [Accepted: 11/13/2022] [Indexed: 06/16/2023]
Abstract
In this study, a floating FeMo3Ox/C3N4-EP (FM-C-P) composite with highly stability and reusability was synthesized by an impregnation/calcination process and used to activate peroxymonosulfate (PMS) for oxytetracycline (OTC) degradation under visible light irradiation. The results demonstrated that 98.1% of OTC (50 mg/L) removal can be achieved by the activation of PMS (5 mM) using FM-C-P (1 g/L) in 30 min under visible light irradiation. The pseudo-first-order rate constant was calculated to be 0.181 min-1. The degradation process with PMS was hardly affected by pH (3-11) and co-existing substance. ·SO4-, ·OH, ·O2- and 1O2 were produced in the Vis/PMS/FM-C-P system and 1O2 was determined to be the main reactive oxygen species (ROSs). The high efficiency of ROSs production mainly contributed to two mechanisms. Firstly, via the combination of ≡Fe (II)-·SO5- and free state ·SO5-, 1O2 could be generated on the Fe-Nx site. Secondly, photo-induced electrons in the FeMo3Ox/g-C3N4 heterojunction could react with Fe (III) and Mo (VI) to form catalytically active species Fe (II) and Mo (IV). Moreover, the proposed degradation pathway and the toxicity of intermediated products was analyzed. Overall, this study was expected to deepen the understanding of the photo-assisted PMS activation and the generation of 1O2 with the presence of metal-oxide/C3N4 heterojunction.
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Affiliation(s)
- Yiyang Liu
- State Key Laboratory of Pollution Control and Resource Reuse, Shanghai Institute of Pollution Control and Ecological Security, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China
| | - Xuejiang Wang
- State Key Laboratory of Pollution Control and Resource Reuse, Shanghai Institute of Pollution Control and Ecological Security, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China.
| | - Qiunan Sun
- State Key Laboratory of Pollution Control and Resource Reuse, Shanghai Institute of Pollution Control and Ecological Security, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China
| | - Meng Yuan
- State Key Laboratory of Pollution Control and Resource Reuse, Shanghai Institute of Pollution Control and Ecological Security, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China
| | - Zhenhua Sun
- State Key Laboratory of Pollution Control and Resource Reuse, Shanghai Institute of Pollution Control and Ecological Security, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China
| | - Liuyu Chen
- State Key Laboratory of Pollution Control and Resource Reuse, Shanghai Institute of Pollution Control and Ecological Security, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China
| | - Yanan Zhang
- College of Chemical Science and Engineering, Tongji University, Shanghai, 200092, PR China
| | - Siqing Xia
- State Key Laboratory of Pollution Control and Resource Reuse, Shanghai Institute of Pollution Control and Ecological Security, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China
| | - Jianfu Zhao
- State Key Laboratory of Pollution Control and Resource Reuse, Shanghai Institute of Pollution Control and Ecological Security, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, PR China
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Liigand P, Liigand J, Kaupmees K, Kruve A. 30 Years of research on ESI/MS response: Trends, contradictions and applications. Anal Chim Acta 2020; 1152:238117. [PMID: 33648645 DOI: 10.1016/j.aca.2020.11.049] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Revised: 11/27/2020] [Accepted: 11/28/2020] [Indexed: 11/29/2022]
Abstract
The variation of ionization efficiency for different compounds has puzzled researchers since the invention of the electrospray mass spectrometry (ESI/MS). Ionization depends on the properties of the compound, eluent, matrix, and instrument. Despite significant research, some aspects have remained unclear. For example, research groups have reached contradicting conclusions regarding the ionization processes. One of the best-known is the significance of the logP value for predicting the ionization efficiency. In this tutorial review, we analyse the methodology used for ionization efficiency measurements as well as the most important trends observed in the data. Additionally, we give suggestions regarding the measurement methodology and modelling strategies to yield meaningful and consistent ionization efficiency data. Finally, we have collected a wide range of ionization efficiency values from the literature and evaluated the consistency of these data. We also make this collection available for everyone for downloading as well as for uploading additional and new ionization efficiency data. We hope this GitHub based ionization efficiency repository will allow a joined community effort to collect and unify the current knowledge about the ionization processes.
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Affiliation(s)
- Piia Liigand
- Institute of Chemistry, Faculty of Science and Technology, University of Tartu, Ravila 14A, 50411, Tartu, Estonia
| | - Jaanus Liigand
- Institute of Chemistry, Faculty of Science and Technology, University of Tartu, Ravila 14A, 50411, Tartu, Estonia; Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada
| | - Karl Kaupmees
- Institute of Chemistry, Faculty of Science and Technology, University of Tartu, Ravila 14A, 50411, Tartu, Estonia
| | - Anneli Kruve
- Institute of Chemistry, Faculty of Science and Technology, University of Tartu, Ravila 14A, 50411, Tartu, Estonia; Department of Materials and Environmental Chemistry, Stockholm University, Svante Arrhenius Väg 16, 106 91, Stockholm, Sweden.
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5
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Yang H, Lou C, Li W, Liu G, Tang Y. Computational Approaches to Identify Structural Alerts and Their Applications in Environmental Toxicology and Drug Discovery. Chem Res Toxicol 2020; 33:1312-1322. [DOI: 10.1021/acs.chemrestox.0c00006] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Hongbin Yang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Chaofeng Lou
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Weihua Li
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Guixia Liu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Yun Tang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
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Burns EE, Carter LJ, Snape J, Thomas-Oates J, Boxall ABA. Application of prioritization approaches to optimize environmental monitoring and testing of pharmaceuticals. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART B, CRITICAL REVIEWS 2018; 21:115-141. [PMID: 29714645 DOI: 10.1080/10937404.2018.1465873] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Pharmaceuticals are ubiquitous in the natural environment with concentrations expected to rise as human population increases. Environmental risk assessments are available for a small portion of pharmaceuticals in use, raising concerns over the potential risks posed by other drugs that have little or no data. With >1900 active pharmaceutical ingredients in use, it would be a major task to test all of the compounds with little or no data. Desk-based prioritization studies provide a potential solution by identifying those substances that are likely to pose the greatest risk to the environment and which, therefore, need to be considered a priority for further study. The aim of this review was to (1) provide an overview of different prioritization exercises performed for pharmaceuticals in the environment and the results obtained; and (2) propose a new holistic risk-based prioritization framework for drugs in the environment. The suggested models to underpin this framework are discussed in terms of validity and applicability. The availability of data required to run the models was assessed and data gaps identified. The implementation of this framework may harmonize pharmaceutical prioritization efforts and ensure that, in the future, experimental resources are focused on molecules, endpoints, and environmental compartments that are biologically relevant.
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Affiliation(s)
- Emily E Burns
- a Chemistry Department , University of York , Heslington , UK
| | - Laura J Carter
- b Environment Department , University of York , Heslington , UK
| | - Jason Snape
- c AstraZeneca AstraZeneca UK, Global Environment , Cheshire , UK
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7
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The utility of QSARs in predicting acute fish toxicity of pesticide metabolites: A retrospective validation approach. Regul Toxicol Pharmacol 2016; 80:241-6. [DOI: 10.1016/j.yrtph.2016.05.032] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Revised: 05/20/2016] [Accepted: 05/22/2016] [Indexed: 11/23/2022]
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8
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Craig EA, Wang NC, Zhao QJ. Using quantitative structure-activity relationship modeling to quantitatively predict the developmental toxicity of halogenated azole compounds. J Appl Toxicol 2013; 34:787-94. [PMID: 24122872 DOI: 10.1002/jat.2940] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2013] [Revised: 09/05/2013] [Accepted: 09/06/2013] [Indexed: 11/10/2022]
Abstract
Developmental toxicity is a relevant endpoint for the comprehensive assessment of human health risk from chemical exposure. However, animal developmental toxicity data remain unavailable for many environmental contaminants due to the complexity and cost of these types of analyses. Here we describe an approach that uses quantitative structure-activity relationship modeling as an alternative methodology to fill data gaps in the developmental toxicity profile of certain halogenated compounds. Chemical information was obtained and curated using the OECD Quantitative Structure-Activity Relationship Toolbox, version 3.0. Data from 35 curated compounds were analyzed via linear regression to build the predictive model, which has an R(2) of 0.79 and a Q(2) of 0.77. The applicability domain (AD) was defined by chemical category and structural similarity. Seven halogenated chemicals that fit the AD but are not part of the training set were employed for external validation purposes. Our model predicted lowest observed adverse effect level values with a maximal threefold deviation from the observed experimental values for all chemicals that fit the AD. The good predictability of our model suggests that this method may be applicable to the analysis of qualifying compounds whenever developmental toxicity information is lacking or incomplete for risk assessment considerations.
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Affiliation(s)
- Evisabel A Craig
- Oak Ridge Institute for Science and Education, Oak Ridge, TN, USA; National Center for Environmental Assessment, Office of Research Development, U.S. Environmental Protection Agency, Cincinnati, OH, USA
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Claeys L, Iaccino F, Janssen CR, Van Sprang P, Verdonck F. Development and validation of a quantitative structure-activity relationship for chronic narcosis to fish. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2013; 32:2217-2225. [PMID: 23775559 DOI: 10.1002/etc.2301] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2013] [Revised: 03/11/2013] [Accepted: 06/07/2013] [Indexed: 06/02/2023]
Abstract
Vertebrate testing under the European Union's regulation on Registration, Evaluation, Authorisation and Restriction of Chemical substances (REACH) is discouraged, and the use of alternative nontesting approaches such as quantitative structure-activity relationships (QSARs) is encouraged. However, robust QSARs predicting chronic ecotoxicity of organic compounds to fish are not available. The Ecological Structure Activity Relationships (ECOSAR) Class Program is a computerized predictive system that estimates the acute and chronic toxicity of organic compounds for several chemical classes based on their log octanol-water partition coefficient (K(OW)). For those chemical classes for which chronic training data sets are lacking, acute to chronic ratios are used to predict chronic toxicity to aquatic organisms. Although ECOSAR reaches a high score against the Organisation for Economic Co-operation and Development (OECD) principles for QSAR validation, the chronic QSARs in ECOSAR are not fully compliant with OECD criteria in the framework of REACH or CLP (classification, labeling, and packaging) regulation. The objective of the present study was to develop a chronic ecotoxicity QSAR for fish for compounds acting via nonpolar and polar narcosis. These QSARs were built using a database of quality screened toxicity values, considering only chronic exposure durations and relevant end points. After statistical multivariate diagnostic analysis, literature-based, mechanistically relevant descriptors were selected to develop a multivariate regression model. Finally, these QSARs were tested for their acceptance for regulatory purposes and were found to be compliant with the OECD principles for the validation of a QSAR.
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Benigni R, Battistelli CL, Bossa C, Colafranceschi M, Tcheremenskaia O. Mutagenicity, carcinogenicity, and other end points. Methods Mol Biol 2013; 930:67-98. [PMID: 23086838 DOI: 10.1007/978-1-62703-059-5_4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2023]
Abstract
Aiming at understanding the structural and physical chemical basis of the biological activity of chemicals, the science of structure-activity relationships has seen dramatic progress in the last decades. Coarse-grain, qualitative approaches (e.g., the structural alerts), and fine-tuned quantitative structure-activity relationship models have been developed and used to predict the toxicological properties of untested chemicals. More recently, a number of approaches and concepts have been developed as support to, and corollary of, the structure-activity methods. These approaches (e.g., chemical relational databases, expert systems, software tools for manipulating the chemical information) have dramatically expanded the reach of the structure-activity work; at present, they are powerful and inescapable tools for computer chemists, toxicologists, and regulators. This chapter, after a general overview of traditional and well-known approaches, gives a detailed presentation of the latter more recent support tools freely available in the public domain.
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Affiliation(s)
- Romualdo Benigni
- Environment and Health Department, Istitituto Superiore di Sanita', Rome, Italy.
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11
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Benigni R, Bossa C, Tcheremenskaia O. Nongenotoxic carcinogenicity of chemicals: mechanisms of action and early recognition through a new set of structural alerts. Chem Rev 2013; 113:2940-57. [PMID: 23469814 DOI: 10.1021/cr300206t] [Citation(s) in RCA: 79] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Romualdo Benigni
- Istituto Superiore di Sanita' Environment and Health Department, Viale Regina Elena 299, 00161 Rome, Italy.
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12
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Furuhama A, Hasunuma K, Aoki Y, Yoshioka Y, Shiraishi H. Application of chemical reaction mechanistic domains to an ecotoxicity QSAR model, the KAshinhou Tool for Ecotoxicity (KATE). SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2011; 22:505-523. [PMID: 21604231 DOI: 10.1080/1062936x.2011.569944] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
The validity of chemical reaction mechanistic domains defined by skin sensitisation in the Quantitative Structure-Activity Relationship (QSAR) ecotoxicity system, KAshinhou Tools for Ecotoxicity (KATE), March 2009 version, has been assessed and an external validation of the current KATE system carried out. In the case of the fish end-point, the group of chemicals with substructures reactive to skin sensitisation always exhibited higher root mean square errors (RMSEs) than chemicals without reactive substructures under identical C- or log P-judgements in KATE. However, in the case of the Daphnia end-point this was not so, and the group of chemicals with reactive substructures did not always have higher RMSEs: the Schiff base mechanism did not function as a high error detector. In addition to the RMSE findings, the presence of outliers suggested that the KATE classification rules needs to be reconsidered, particularly for the amine group. Examination of the dependency of the organism on the toxic action of chemicals in fish and Daphnia revealed that some of the reactive substructures could be applied to the improvement of the KATE system. It was concluded that the reaction mechanistic domains of toxic action for skin sensitisation could provide useful complementary information in predicting acute aquatic ecotoxicity, especially at the fish end-point.
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Affiliation(s)
- A Furuhama
- Research Center for Environmental Risk, National Institute for Environmental Studies (NIES), Tsukuba, Japan
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de Haas EM, Eikelboom T, Bouwman T. Internal and external validation of the long-term QSARs for neutral organics to fish from ECOSAR™. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2011; 22:545-559. [PMID: 21732893 DOI: 10.1080/1062936x.2011.569949] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
This study concentrates on the external validation of an existing Quantitative Structure-Activity Relationship (QSAR) model widely used for long-term aquatic toxicity to fish. In the context of the REACH legislation, QSARs are used as an alternative for experimental data to achieve a complete environmental assessment without the need for animal testing. The predictivity of the model was evaluated in order to increase the reliability of the model. We assessed whether the model met all of the OECD principles. The model was adapted to become more robust, and predictions were made with an external validation set collected from several databases. For the internal validation of the QSAR, the r², Q²(Loo) and Q²(LMO) were used as validation criteria, and for the external validation r², Q²(ext), h and the validation ratio were used. A few substances were classified as outliers and therefore the applicability domain of the QSAR had to be adjusted. The QSAR passed all validation criteria and met all the OECD principles for QSAR validation, and the long-term toxicity QSAR for fish can be applied with high certainty of a correct prediction within the limits of the inherent uncertainty of the model in cases where the substance falls within the applicability domain.
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Affiliation(s)
- E M de Haas
- Chemical Risk Analysis, TNO Triskelion BV, Zeist, The Netherlands.
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14
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Ellison CM, Sherhod R, Cronin MTD, Enoch SJ, Madden JC, Judson PN. Assessment of Methods To Define the Applicability Domain of Structural Alert Models. J Chem Inf Model 2011; 51:975-85. [DOI: 10.1021/ci1000967] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- C. M. Ellison
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, England
| | - R. Sherhod
- Department of Information Studies, University of Sheffield, Regent Court, Sheffield S1 4DP, England
| | - M. T. D. Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, England
| | - S. J. Enoch
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, England
| | - J. C. Madden
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, England
| | - P. N. Judson
- Lhasa Limited, 22-23 Blenheim Terrace, Woodhouse Lane, Leeds LS2 9HD, England
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15
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Bhhatarai B, Teetz W, Liu T, Öberg T, Jeliazkova N, Kochev N, Pukalov O, Tetko IV, Kovarich S, Papa E, Gramatica P. CADASTER QSPR Models for Predictions of Melting and Boiling Points of Perfluorinated Chemicals. Mol Inform 2011; 30:189-204. [DOI: 10.1002/minf.201000133] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2010] [Accepted: 02/03/2011] [Indexed: 11/06/2022]
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Devillers J, Mombelli E, Samsera R. Structural alerts for estimating the carcinogenicity of pesticides and biocides. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2011; 22:89-106. [PMID: 21391143 DOI: 10.1080/1062936x.2010.548349] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
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.
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Benigni R, Bossa C. Mechanisms of Chemical Carcinogenicity and Mutagenicity: A Review with Implications for Predictive Toxicology. Chem Rev 2011; 111:2507-36. [PMID: 21265518 DOI: 10.1021/cr100222q] [Citation(s) in RCA: 239] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Romualdo Benigni
- Istituto Superiore di Sanita’, Environment and Health Department, Viale Regina Elena, 299 00161 Rome, Italy
| | - Cecilia Bossa
- Istituto Superiore di Sanita’, Environment and Health Department, Viale Regina Elena, 299 00161 Rome, Italy
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Abstract
Expert systems offer the facility to predict a toxicity endpoint, as well sometimes as additional relevant information, simply by inputting the chemical structure of a compound. There is now a number of expert systems available, mostly on a commercial basis although a few are free to use or download. This chapter discusses nineteen currently available expert systems, and their performances (if known). Published studies of consensus predictions with these expert systems indicate that these give better results than do individual expert systems.
A test set of compounds with Tetrahymena pyriformis toxicities has been run through the two expert systems known to predict these toxicities; the predictions were quite good, with standard errors of prediction of 0.395 and 0.433 log unit. A further test set of compounds with local lymph node assay skin sensitisation data has been run through seven expert systems, and it was found that consensus predictions were better than were those from any individual expert system.
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Affiliation(s)
- J. C. Dearden
- School of Pharmacy and Chemistry, Liverpool John Moores University Byrom Street Liverpool L3 3AF UK
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Furuhama A, Toida T, Nishikawa N, Aoki Y, Yoshioka Y, Shiraishi H. Development of an ecotoxicity QSAR model for the KAshinhou Tool for Ecotoxicity (KATE) system, March 2009 version. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2010; 21:403-13. [PMID: 20818579 PMCID: PMC2946238 DOI: 10.1080/1062936x.2010.501815] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2008] [Accepted: 04/28/2010] [Indexed: 05/14/2023]
Abstract
The KAshinhou Tool for Ecotoxicity (KATE) system, including ecotoxicity quantitative structure-activity relationship (QSAR) models, was developed by the Japanese National Institute for Environmental Studies (NIES) using the database of aquatic toxicity results gathered by the Japanese Ministry of the Environment and the US EPA fathead minnow database. In this system chemicals can be entered according to their one-dimensional structures and classified by substructure. The QSAR equations for predicting the toxicity of a chemical compound assume a linear correlation between its log P value and its aquatic toxicity. KATE uses a structural domain called C-judgement, defined by the substructures of specified functional groups in the QSAR models. Internal validation by the leave-one-out method confirms that the QSAR equations, with r(2 )> 0.7, RMSE 5, give acceptable q(2) values. Such external validation indicates that a group of chemicals with an in-domain of KATE C-judgements exhibits a lower root mean square error (RMSE). These findings demonstrate that the KATE system has the potential to enable chemicals to be categorised as potential hazards.
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Affiliation(s)
- A Furuhama
- Research Center for Environmental Risk, National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba 305-8506, Japan.
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Gramatica P. Chemometric Methods and Theoretical Molecular Descriptors in Predictive QSAR Modeling of the Environmental Behavior of Organic Pollutants. CHALLENGES AND ADVANCES IN COMPUTATIONAL CHEMISTRY AND PHYSICS 2010. [DOI: 10.1007/978-1-4020-9783-6_12] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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Ellison CM, Enoch SJ, Cronin MT, Madden JC, Judson P. Definition of the Applicability Domains of Knowledge-based Predictive Toxicology Expert Systems by Using a Structural Fragment-based Approach. Altern Lab Anim 2009; 37:533-45. [DOI: 10.1177/026119290903700510] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The applicability domain of a (quantitative) structure–activity relationship ([Q]SAR) must be defined, if a model is to be used successfully for toxicity prediction, particularly for regulatory purposes. Previous efforts to set guidelines on the definition of applicability domains have often been biased toward quantitative, rather than qualitative, models. As a result, novel techniques are still required to define the applicability domains of structural alert models and knowledge-based systems. By using Derek for Windows as an example, this study defined the domain for the skin sensitisation structural alert rule-base. This was achieved by fragmenting the molecules within a training set of compounds, then searching the fragments for those created from a test compound. This novel method was able to highlight test chemicals which differed from those in the training set. The information was then used to designate chemicals as being either within or outside the domain of applicability for the structural alert on which that training set was based.
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Affiliation(s)
- Claire M. Ellison
- School of Pharmacy and Chemistry, Liverpool John Moores University, Liverpool, UK
| | - Steven J. Enoch
- School of Pharmacy and Chemistry, Liverpool John Moores University, Liverpool, UK
| | - Mark T.D. Cronin
- School of Pharmacy and Chemistry, Liverpool John Moores University, Liverpool, UK
| | - Judith C. Madden
- School of Pharmacy and Chemistry, Liverpool John Moores University, Liverpool, UK
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Hammerling U, Tallsjö A, Grafström R, Ilbäck NG. Comparative Hazard Characterization in Food Toxicology. Crit Rev Food Sci Nutr 2009; 49:626-69. [DOI: 10.1080/10408390802145617] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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Zvinavashe E, Murk AJ, Rietjens IM. On the number of EINECS compounds that can be covered by (Q)SAR models for acute toxicity. Toxicol Lett 2009; 184:67-72. [DOI: 10.1016/j.toxlet.2008.10.030] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2008] [Revised: 10/30/2008] [Accepted: 10/30/2008] [Indexed: 10/21/2022]
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Marchant CA, Briggs KA, Long A. In Silico Tools for Sharing Data and Knowledge on Toxicity and Metabolism: Derek for Windows, Meteor, and Vitic. Toxicol Mech Methods 2008; 18:177-87. [DOI: 10.1080/15376510701857320] [Citation(s) in RCA: 178] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Reuschenbach P, Silvani M, Dammann M, Warnecke D, Knacker T. ECOSAR model performance with a large test set of industrial chemicals. CHEMOSPHERE 2008; 71:1986-1995. [PMID: 18262586 DOI: 10.1016/j.chemosphere.2007.12.006] [Citation(s) in RCA: 106] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2007] [Revised: 12/07/2007] [Accepted: 12/14/2007] [Indexed: 05/25/2023]
Abstract
The widely used ECOSAR computer programme for QSAR prediction of chemical toxicity towards aquatic organisms was evaluated by using large data sets of industrial chemicals with varying molecular structures. Experimentally derived toxicity data covering acute effects on fish, Daphnia and green algae growth inhibition of in total more than 1,000 randomly selected substances were compared to the prediction results of the ECOSAR programme in order (1) to assess the capability of ECOSAR to correctly classify the chemicals into defined classes of aquatic toxicity according to rules of EU regulation and (2) to determine the number of correct predictions within tolerance factors from 2 to 1,000. Regarding ecotoxicity classification, 65% (fish), 52% (Daphnia) and 49% (algae) of the substances were correctly predicted into the classes "not harmful", "harmful", "toxic" and "very toxic". At all trophic levels about 20% of the chemicals were underestimated in their toxicity. The class of "not harmful" substances (experimental LC/EC(50)>100 mg l(-1)) represents nearly half of the whole data set. The percentages for correct predictions of toxic effects on fish, Daphnia and algae growth inhibition were 69%, 64% and 60%, respectively, when a tolerance factor of 10 was allowed. Focussing on those experimental results which were verified by analytically measured concentrations, the predictability for Daphnia and algae toxicity was improved by approximately three percentage points, whereas for fish no improvement was determined. The calculated correlation coefficients demonstrated poor correlation when the complete data set was taken, but showed good results for some of the ECOSAR chemical classes. The results are discussed in the context of literature data on the performance of ECOSAR and other QSAR models.
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Abstract
A range of good quality, local QSARs for mutagenicity and carcinogenicity have been assessed and challenged for their predictivity in respect to real external test sets (i.e., chemicals never considered by the authors while developing their models). The QSARs for potency (applicable only to toxic chemicals) generated predictions 30-70% correct, whereas the QSARs for discriminating between active and inactive chemicals were 70-100% correct in their external predictions: thus the latter can be used with good reliability for applicative purposes. On the other hand internal, statistical validation methods, which are often assumed to be good diagnostics for predictivity, did not correlate well with the predictivity of the QSARs when challenged in external prediction tests. Nonlocal models for noncongeneric chemicals were considered as well, pointing to the critical role of an adequate definition of the applicability domain.
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Affiliation(s)
- Romualdo Benigni
- Environment and Health Department, Istituto Superiore di Sanita', Viale Regina Elena 299, 00161 Rome, Italy.
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Rosenkranz HS, Cunningham SL, Mermelstein R, Cunningham AR. The challenge of testing chemicals for potential carcinogenicity using multiple short-term assays: An analysis of a proposed test battery for hair dyes. MUTATION RESEARCH-GENETIC TOXICOLOGY AND ENVIRONMENTAL MUTAGENESIS 2007; 633:55-66. [PMID: 17625954 DOI: 10.1016/j.mrgentox.2007.05.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2007] [Accepted: 05/14/2007] [Indexed: 11/26/2022]
Abstract
Recent reports of the association of hair dyes usage with increased bladder cancer risk in women with the slow NAT-2 acetylator phenotype have resulted both in attempts to identify the putative carcinogen as well as in devising batteries of tests that could be used to screen for such putative carcinogens in hair dye formulations, their intermediates and final products. Analytical studies have reported the presence of traces ( approximately 0.5 ppm) of the carcinogen 4-aminobiphenyl in some hair dye preparations. In parallel, SCCNFP (Scientific Committee on Cosmetic and Non-Food Products Intended for Consumers) has suggested the deployment of a battery of six in vitro assays followed by an in vivo assay. The practicality of deploying and interpreting such a battery is analyzed herein as it is expected to result in 64 and 128 possible test results and SCCNFP does not provide detailed guidance of how the test results are to be interpreted. In this study we have applied a previously described Bayesian approach which takes advantage of the known predictive performances of individual assays, to analyze the possible outcomes of the 6-7 test batteries. While the SCCNFP battery is clearly risk-averse, it is shown that performing all of the assays is not always necessary and moreover it does not necessarily improve predictive performance. Finally, based upon the reported mutagenicity of 4-aminobiphenyl, it is doubtful that this "impurity" would be detected by the test battery.
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28
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Introducing Spectral Structure Activity Relationship (S-SAR) Analysis. Application to Ecotoxicology. Int J Mol Sci 2007. [DOI: 10.3390/i8050363] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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Matthews EJ, Kruhlak NL, Daniel Benz R, Ivanov J, Klopman G, Contrera JF. A comprehensive model for reproductive and developmental toxicity hazard identification: II. Construction of QSAR models to predict activities of untested chemicals. Regul Toxicol Pharmacol 2007; 47:136-55. [DOI: 10.1016/j.yrtph.2006.10.001] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2006] [Indexed: 11/28/2022]
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SAKAMOTO K, YAMAUCHI A, SASAKI M, CHUMAN H. A Structural Similarity Evaluation by SimScore in a Teratogenicity Information Sharing System. JOURNAL OF COMPUTER CHEMISTRY-JAPAN 2007. [DOI: 10.2477/jccj.6.117] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Crettaz P, Benigni R. Prediction of the rodent carcinogenicity of 60 pesticides by the DEREKfW expert system. J Chem Inf Model 2006; 45:1864-73. [PMID: 16309294 DOI: 10.1021/ci050150z] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The two-year rodent bioassay represents the golden standard for evaluating the carcinogenicity of chemicals. Because of practical and ethical reasons, alternative approaches have been investigated for many years. Among these approaches, the (quantitative) structure-activity relationships [(Q)SARs] offer promising perspectives for quickly screening a large number of chemicals. To increase the acceptance of (Q)SARs among the regulators, their predictive power needs to be scientifically validated. In this article, we tested the capacity of the DEREKfW expert system to qualitatively predict the rodent carcinogenicity and the genotoxic potential of 60 pesticides recently registered in Switzerland. The percentage of false negatives was found to be 31% for carcinogenicity. The associated sensitivity of 69% indicates that most of the pesticides with positive rodent bioassay results were detected by DEREKfW. On the other hand, the low specificity of 47% indicates that many pesticides may be flagged as carcinogenic while rodent bioassays would not confirm this potential. This may lead to unnecessary testing or the unnecessary restriction of a chemical.
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Affiliation(s)
- Pierre Crettaz
- Swiss Federal Office of Public Health, 3003 Bern, Switzerland.
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33
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Combes R, Balls M. Intelligent testing strategies for chemicals testing -- a case of more haste, less speed? Altern Lab Anim 2005; 33:289-97. [PMID: 16180981 DOI: 10.1177/026119290503300302] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The prospects for using (Q)SAR modelling, read-across (chemical) and other non-animal approaches as part of integrated testing strategies for chemical risk assessment, within the framework of the EU REACH legislation, are considered. The potential advantages and limitations of (Q)SAR modelling and read-across methods for chemical regulatory risk assessment are reviewed. It is concluded that it would be premature to base a testing strategy on chemical-based computational modelling approaches, until such time as criteria to validate them for their reliability and relevance by using independent and transparent procedures, have been agreed. This is mainly because of inherent problems in validating and accepting (Q)SARs for regulatory use in ways that are analogous to those that have been developed and applied for in vitro tests. Until this issue has been resolved, it is recommended that testing strategies should be developed which comprise the integrated use of computational and read-across approaches. These should be applied in a cautious and judicious way, in association with available tissue culture methods, and in conjunction with metabolism and biokinetic studies. Such strategies should be intelligently applied by being driven by exposure information (based on bioavailability, not merely on production volume) and hazard information needs, in preference to a tick-box approach. In the meantime, there should be increased efforts to develop improved (Q)SARs, expert systems and new in vitro methods, and, in particular, ways to expedite their validation and acceptance must be found and prospectively agreed with all major stakeholders.
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Hulzebos E, Sijm D, Traas T, Posthumus R, Maslankiewicz L. Validity and validation of expert (Q)SAR systems. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2005; 16:385-401. [PMID: 16234178 DOI: 10.1080/10659360500204426] [Citation(s) in RCA: 18] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
At a recent workshop in Setubal (Portugal) principles were drafted to assess the suitability of (quantitative) structure-activity relationships ((Q)SARs) for assessing the hazards and risks of chemicals. In the present study we applied some of the Setubal principles to test the validity of three (Q)SAR expert systems and validate the results. These principles include a mechanistic basis, the availability of a training set and validation. ECOSAR, BIOWIN and DEREK for Windows have a mechanistic or empirical basis. ECOSAR has a training set for each QSAR. For half of the structural fragments the number of chemicals in the training set is >4. Based on structural fragments and log Kow, ECOSAR uses linear regression to predict ecotoxicity. Validating ECOSAR for three 'valid' classes results in predictivity of > or = 64%. BIOWIN uses (non-)linear regressions to predict the probability of biodegradability based on fragments and molecular weight. It has a large training set and predicts non-ready biodegradability well. DEREK for Windows predictions are supported by a mechanistic rationale and literature references. The structural alerts in this program have been developed with a training set of positive and negative toxicity data. However, to support the prediction only a limited number of chemicals in the training set is presented to the user. DEREK for Windows predicts effects by 'if-then' reasoning. The program predicts best for mutagenicity and carcinogenicity. Each structural fragment in ECOSAR and DEREK for Windows needs to be evaluated and validated separately.
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Affiliation(s)
- E Hulzebos
- Expert Centre for Substances, PO Box 1, 3720 BA Bilthoven, RIVM, Netherlands.
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35
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Benigni R. Structure-activity relationship studies of chemical mutagens and carcinogens: mechanistic investigations and prediction approaches. Chem Rev 2005; 105:1767-800. [PMID: 15884789 DOI: 10.1021/cr030049y] [Citation(s) in RCA: 106] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Romualdo Benigni
- Istituto Superiore di Sanita', Experimental and Computational Carcinogenesis, Department of Environment and Primary Prevention, Viale Regina Elena 299-00161 Rome, Italy.
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36
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Rosenkranz HS, Cunningham AR. Lack of predictivity of the rat lethality (LD50) test for ecological and human health effects. Altern Lab Anim 2005; 33:9-19. [PMID: 15804213 DOI: 10.1177/026119290503300104] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The relationship between acute toxicity in rats (LD50 values) and indicators of potential health hazards in humans was investigated, based on a chemical population-based paradigm (i.e. the "chemical diversity approach"). These structure-activity relationship-based analyses indicate that high toxicity in rats (i.e. a low LD50 value) is not a good predictor of health effects in humans. In fact, it was found that high acute toxicity to minnows, as well as toxicity to cultured cells, showed significantly greater associations with the potential for health effects than rat LD50 values.
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Affiliation(s)
- Herbert S Rosenkranz
- Department of Biomedical Sciences, Florida Atlantic University, 777 Glades Road, P.O. Box 3091, Boca Raton, FL 33431-0991, USA
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37
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Tunkel J, Mayo K, Austin C, Hickerson A, Howard P. Practical considerations on the use of predictive models for regulatory purposes. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2005; 39:2188-99. [PMID: 15871254 DOI: 10.1021/es049220t] [Citation(s) in RCA: 36] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Interest in the use of quantitative structure-activity relationships (QSARs) for regulatory purposes has been growing steadily over the years, and many models have been evaluated under the guidance and acceptability criteria defined at the Setubal workshop held in March 2002. This work explores some of the practical issues related to the use of QSARs for regulatory purposes using results obtained from rat oral lethality and fish acute toxicity estimates generated from computational models (including TOPKAT, MCASE, OASIS, and ECOSAR). Using data submitted under the Environmental Protection Agency's (EPA's) High Production Volume (HPV) Challenge Program, the results on the quality of the estimations are compared using a standard statistical review and an additional classification approach in which the hazard predictions were grouped using well-defined regulatory criteria (those used in EPA's New Chemical Program). Our results indicate that an evaluation of a model's regulatory applicability and predictive power is ultimately dependent on the specific criteria used in the assessment process. This work also discusses the practical difficulties associated with defining the domain of a predictive model using the estimates of four different ready biodegradation models and experimental data submitted under the EPA's New Chemical program. Our results suggest that the method a model employs for its predictions is as important as the training set in determining its domain of applicability. Together, these results highlight the challenges associated with developing reliable and easily applied acceptability criteria for the regulatory use of QSAR models.
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Affiliation(s)
- Jay Tunkel
- Syracuse Research Corporation, Environmental Science Center, Syracuse, New York 13212, USA.
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Hulzebos E, Walker J, Gerner I, Schlegel K. Use of structural alerts to develop rules for identifying chemical substances with skin irritation or skin corrosion potential. ACTA ACUST UNITED AC 2005. [DOI: 10.1002/qsar.200430905] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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39
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Benigni R. Computational prediction of drug toxicity: the case of mutagenicity and carcinogenicity. DRUG DISCOVERY TODAY. TECHNOLOGIES 2004; 1:457-463. [PMID: 24981627 DOI: 10.1016/j.ddtec.2004.09.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
The removal of pharmaceuticals from the market is a dramatic demonstration of the urgency of implementing better approaches for the early detection of drug toxicity. This paper summarizes the attempts to predict mutagenicity and carcinogenicity from the chemical structure. The limitations of the available commercial systems are pointed out and the urgency of integrating higher levels of chemical knowledge is stressed.:
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Affiliation(s)
- Romualdo Benigni
- Laboratory of Comparative Toxicology, Environment and Health Department, Istituto Superiore di Sanita, Viale Regina Elena 299, 00161 Rome, Italy.
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40
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Abstract
A comprehensive, multidisciplinary approach is proposed here for the development of a drug with an acceptable safety profile. Key parameters to be considered for drug safety evaluation based on this comprehensive approach include the following: (1) Pharmacology: Possible toxicity due to drug-target interactions, including interactions with unintended molecular targets, or with molecular targets in unintended organs. (2) Chemistry: Chemical scaffolding and side-chains with safety concerns. (3) Toxicology: Toxicity in animals in vivo, and in relevant animal and human cells in culture. (4) Drug metabolism and pharmacokinetics: Safety concerns due to toxification or detoxification, organ distribution, clearance and pharmacokinetic drug-drug interactions. (5) RISK FACTORS: Physiological, environmental and genetic factors that may enhance a patient's susceptibility. It is proposed that this integrated, multidisciplinary approach to safety evaluation may enhance the accuracy of the prediction of drug safety and thereby the efficiency of drug development.
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Affiliation(s)
- Albert P Li
- Advanced Pharmaceutical Sciences, Inc., PMB #146, 6400 Baltimore National Pike, Baltimore, MD 21228, USA.
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41
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Gerner I, Schlegel K, Walker J, Hulzebos E. Use of Physicochemical Property Limits to Develop Rules for Identifying Chemical Substances with no Skin Irritation or Corrosion Potential. ACTA ACUST UNITED AC 2004. [DOI: 10.1002/qsar.200430880] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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42
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Affiliation(s)
- Albert P Li
- Advanced Pharmaceutical Sciences, PMB#146, 6400 Baltimore National Pike, Baltimore, MD 21228, USA
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Höfer T, Gerner I, Gundert-Remy U, Liebsch M, Schulte A, Spielmann H, Vogel R, Wettig K. Animal testing and alternative approaches for the human health risk assessment under the proposed new European chemicals regulation. Arch Toxicol 2004; 78:549-64. [PMID: 15170526 DOI: 10.1007/s00204-004-0577-9] [Citation(s) in RCA: 158] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2004] [Accepted: 04/08/2004] [Indexed: 12/01/2022]
Abstract
During the past 20 years the EU legislation for the notification of chemicals has focussed on new chemicals and at the same time failed to cover the evaluation of existing chemicals in Europe. Therefore, in a new EU chemicals policy (REACH, Registration, Evaluation and Authorization of Chemicals) the European Commission proposes to evaluate 30,000 chemicals within a period of 15 years. We are providing estimates of the testing requirements based on our personal experiences during the past 20 years. A realistic scenario based on an in-depth discussion of potential toxicological developments and an optimised "tailor-made" testing strategy shows that to meet the goals of the REACH policy, animal numbers may be significantly reduced below 10 million if industry would use in-house data from toxicity testing, which are confidential, if non-animal tests would be used, and if information from quantitative structure activity relationships (QSARs) would be applied in substance-tailored testing schemes. The procedures for evaluating the reproductive toxicity of chemicals have the strongest impact on the total number of animals bred for testing under REACH. We are assuming both an active collaboration with our colleagues in industry and substantial funding of the development and validation of advanced non-animal methods by the EU Commission, specifically in reproductive and developmental toxicity.
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Affiliation(s)
- Thomas Höfer
- Bundesinstitut für Risikobewertung (BfR), Thielallee 88-92, 14195, Berlin, Germany.
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Rosenkranz HS. SAR modeling of genotoxic phenomena: the consequence on predictive performance of deviation from a unity ratio of genotoxicants/non-genotoxicants. MUTATION RESEARCH-GENETIC TOXICOLOGY AND ENVIRONMENTAL MUTAGENESIS 2004; 559:67-71. [PMID: 15066575 DOI: 10.1016/j.mrgentox.2003.12.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2003] [Revised: 12/23/2003] [Accepted: 12/23/2003] [Indexed: 11/28/2022]
Abstract
SAR approaches to the study of genotoxic phenomena are finding increased applications. However, the data being modeled are frequently not considered optimal due to the small size of the dataset and an uneven distribution of genotoxicants and non-genotoxicants in the dataset. The effects of such imbalances on the performance of one SAR approach were investigated with respect to the modeling of the induction of unscheduled DNA synthesis in rat hepotocytes and of sister chromatid exchanges and chromosomal aberrations in cultural CHO cells. The analyses indicate that if genotoxicants exceed non-genotoxicants, the performance of the SAR model can be improved if the dataset is supplemented with physiological chemicals which are assumed to be non-genotoxicants. On the other hand, if non-genotoxicants exceed genotoxicants, it was found that the predictive performance of the resulting SAR model is not improved by removal of genotoxicants from the dataset to achieve a ratio of genotoxicants/genotoxicants of unity. Overall, the present analyses did not result in the development of SAR models of greatly increased predictivity. Conceivably, for the particular datasets and SAR paradigm the limit of predictivity has been reached. The possibility of investigating the use of a "battery" of SAR paradigms should be considered.
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Affiliation(s)
- Herbert S Rosenkranz
- Department of Biomedical Sciences, Florida Atlantic University, 777 Glades Rd., P.O. Box 3091, Boca Raton, FL 33431, USA.
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