TY - CHAP
T1 - Ecotoxicological QSARs of mixtures
AU - Khan, Pathan Mohsin
AU - Kar, Supratik
AU - Roy, Kunal
N1 - Publisher Copyright:
© Springer Science+Business Media, LLC, part of Springer Nature 2020.
PY - 2020
Y1 - 2020
N2 - In this era of advanced industrialization, all the living beings and environment are exposed to multicomponent mixtures of different classes of chemicals such as organics, pesticides, heavy metals, and pharmaceuticals which may cause direct or indirect hazards to humans, wildlife, aquatic systems, and ecosystems. The regulatory authorities have mostly relied on the single chemical risk assessment, instead of considering the impact of complex chemical mixtures. It is also well known that toxicity data for the individual components is available for a fraction of all existing chemicals in environment. The condition is much worse as there is minimal toxicity data for complex multicomponent chemical mixtures, and the nature of toxicity of a mixture (synergism and/or antagonism) will be entirely different from the toxicity of the single chemicals. A number of regulatory authorities have proposed several methodologies and guidance for the evaluation of hazardous effects of multicomponent chemical mixtures. However, a standard, significant, and reliable approach for evaluation of toxicity of chemical mixtures and their management across diverse monitoring sectors is lacking. In the present chapter, we have illustrated the basic concepts of mixture toxicity assessment, such as concentration addition, independent action, and interaction (synergism and/or antagonism), as well as focused on the computational approaches, such as quantitative structure-activity relationship (QSAR), which is already proven as an efficient alternative method for toxicity prediction of chemicals by regulatory authorities for decision making. Subsequently, we have also provided a brief detail on several ongoing research projects in the European Union (EU), funded by the current European Research and Innovation Programme Horizon 2020 or the Seventh Framework Programme for mixture toxicity prediction. The present chapter also explains the importance of evaluation of chemical mixture toxicity and essential steps in basic QSAR modelling in the context of mixtures. Additionally, we have reported the successful application of QSAR in the prediction of mixture toxicity of different classes of chemicals such as pharmaceuticals, pesticides, metals, and organic industrial chemicals.
AB - In this era of advanced industrialization, all the living beings and environment are exposed to multicomponent mixtures of different classes of chemicals such as organics, pesticides, heavy metals, and pharmaceuticals which may cause direct or indirect hazards to humans, wildlife, aquatic systems, and ecosystems. The regulatory authorities have mostly relied on the single chemical risk assessment, instead of considering the impact of complex chemical mixtures. It is also well known that toxicity data for the individual components is available for a fraction of all existing chemicals in environment. The condition is much worse as there is minimal toxicity data for complex multicomponent chemical mixtures, and the nature of toxicity of a mixture (synergism and/or antagonism) will be entirely different from the toxicity of the single chemicals. A number of regulatory authorities have proposed several methodologies and guidance for the evaluation of hazardous effects of multicomponent chemical mixtures. However, a standard, significant, and reliable approach for evaluation of toxicity of chemical mixtures and their management across diverse monitoring sectors is lacking. In the present chapter, we have illustrated the basic concepts of mixture toxicity assessment, such as concentration addition, independent action, and interaction (synergism and/or antagonism), as well as focused on the computational approaches, such as quantitative structure-activity relationship (QSAR), which is already proven as an efficient alternative method for toxicity prediction of chemicals by regulatory authorities for decision making. Subsequently, we have also provided a brief detail on several ongoing research projects in the European Union (EU), funded by the current European Research and Innovation Programme Horizon 2020 or the Seventh Framework Programme for mixture toxicity prediction. The present chapter also explains the importance of evaluation of chemical mixture toxicity and essential steps in basic QSAR modelling in the context of mixtures. Additionally, we have reported the successful application of QSAR in the prediction of mixture toxicity of different classes of chemicals such as pharmaceuticals, pesticides, metals, and organic industrial chemicals.
KW - Component-based approach
KW - EuroMix
KW - EUToxRisk
KW - Generalized concentration addition (GCA) models
KW - Human risk assessment (HRA)
KW - Interactions
KW - Mixture toxicity assessment
KW - QSAR of mixtures
UR - http://www.scopus.com/inward/record.url?scp=85078108737&partnerID=8YFLogxK
U2 - 10.1007/978-1-0716-0150-1_19
DO - 10.1007/978-1-0716-0150-1_19
M3 - Chapter
AN - SCOPUS:85078108737
T3 - Methods in Pharmacology and Toxicology
SP - 437
EP - 475
BT - Methods in Pharmacology and Toxicology
PB - Humana Press Inc.
ER -