Chapter 2
Background, Tasks, Modeling Methods,
and Challenges for Computational
Toxicology
Zhongyu Wang and Jingwen Chen
Abstract Sound chemicals management requires scientific risk assessment schemes
capable of predicting physical–chemical properties, environmental behavior, and toxicological effects of vast number of chemicals. However, the current experimental
system cannot meet the need for risk assessment of the large and ever-increasing
number of chemicals. Meanwhile, current experimental approaches are not sufficient for toxicology to thrive in the era of information. Thus, an auxiliary yet critical field for complementing the experimental sector of chemicals risk assessment
has emerged: computational toxicology. Computational toxicology is an interdisciplinary field based especially on environmental chemistry, computational chemistry,
chemo-bioinformatics, and systems biology, etc., and it aims at facilitating efficient
simulation and prediction of environmental exposure, hazard, and risk of chemicals
through various in silico models. Computational toxicology has profoundly changed
the way people view and interpret basic concepts of toxicology. Meanwhile, this
field is continuously borrowing ideas from exterior fields, which greatly promotes
innovative development of toxicology. In this chapter, backgrounds and tasks of
computational toxicology are firstly introduced. Then, a variety of in silico models
linking key information of chemicals involved in the continuum of source to adverse
outcome, such as source emission, concentrations in environmental compartments,
exposure concentrations at biological target sites, and adverse efficacy or thresholds
are described and discussed. Finally, challenges in computational toxicology such
as parameterization for the proposed models, representation of complexity of living
systems, and modeling of interlinked chemicals as mixtures are also discussed.
Z. Wang · J. Chen (B)
Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education),
School of Environmental Science and Technology, Dalian University of Technology, Dalian,
China
e-mail: jwchen@dlut.edu.cn
Z. Wang
e-mail: wzy1989@mail.dlut.edu.cn
© Springer Nature Switzerland AG 2019
H. Hong (ed.), Advances in Computational Toxicology, Challenges and Advances
in Computational Chemistry and Physics 30,
https://doi.org/10.1007/978-3-030-16443-0_2
15
Background, Tasks, Modeling Methods,
and Challenges for Computational
Toxicology
Zhongyu Wang and Jingwen Chen
Abstract Sound chemicals management requires scientific risk assessment schemes
capable of predicting physical–chemical properties, environmental behavior, and toxicological effects of vast number of chemicals. However, the current experimental
system cannot meet the need for risk assessment of the large and ever-increasing
number of chemicals. Meanwhile, current experimental approaches are not sufficient for toxicology to thrive in the era of information. Thus, an auxiliary yet critical field for complementing the experimental sector of chemicals risk assessment
has emerged: computational toxicology. Computational toxicology is an interdisciplinary field based especially on environmental chemistry, computational chemistry,
chemo-bioinformatics, and systems biology, etc., and it aims at facilitating efficient
simulation and prediction of environmental exposure, hazard, and risk of chemicals
through various in silico models. Computational toxicology has profoundly changed
the way people view and interpret basic concepts of toxicology. Meanwhile, this
field is continuously borrowing ideas from exterior fields, which greatly promotes
innovative development of toxicology. In this chapter, backgrounds and tasks of
computational toxicology are firstly introduced. Then, a variety of in silico models
linking key information of chemicals involved in the continuum of source to adverse
outcome, such as source emission, concentrations in environmental compartments,
exposure concentrations at biological target sites, and adverse efficacy or thresholds
are described and discussed. Finally, challenges in computational toxicology such
as parameterization for the proposed models, representation of complexity of living
systems, and modeling of interlinked chemicals as mixtures are also discussed.
Z. Wang · J. Chen (B)
Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education),
School of Environmental Science and Technology, Dalian University of Technology, Dalian,
China
e-mail: jwchen@dlut.edu.cn
Z. Wang
e-mail: wzy1989@mail.dlut.edu.cn
© Springer Nature Switzerland AG 2019
H. Hong (ed.), Advances in Computational Toxicology, Challenges and Advances
in Computational Chemistry and Physics 30,
https://doi.org/10.1007/978-3-030-16443-0_2
15