2 Background, Tasks, Modeling Methods …
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2.2 Tasks for Computational Toxicology
Computational toxicology is a typical interdisciplinary field based on environmental chemistry, computational chemistry, chemo-bioinformatics, and systems biology,
etc., and it aims at facilitating prediction of environmental exposure, hazard, and risk
of chemicals by various in silico models. There are two major tasks for computational toxicology: to facilitate sound chemicals management and to shape digitized
predictive toxicology.
2.2.1 Facilitating Sound Chemicals Management
One of the urgent needs for sound chemicals management is to build capability to
assess virtually all the existing chemicals in markets, i.e., to build a scientific highthroughput system for chemicals risk assessment [1]. HTS technology has made a
steady contribution to this envisioned system, but it is still not sufficient.
In 2005, the US Environmental Protection Agency (EPA) founded the National
Center for Computational Toxicology to lead and implement research on computational toxicology [21]. Meanwhile, the Joint Research Center of the EU along with
many research groups have also carried out projects around core topics of computational toxicology under the 6th and 7th Framework Programs, such as OSIRIS
(Optimized Strategies for Risk Assessment of Industrial Chemicals through Integration of Non-test and Test Information) [22] and SEURAT (Safety Evaluation
Ultimately Replacing Animal Testing) [23]. In this sense, computational toxicology
or in silico toxicology serves as one of the tools to meet the requirement of certain
countries, regional organizations [e.g., Organization of Economic Cooperation and
Development (OECD)] and/or regulatory laws (e.g., REACH) for chemicals risk
assessment.
A classic risk assessment scheme includes hazard identification, exposure assessment, effect assessment (dose–response relationships), and risk characterization [24].
Risk characterization is always represented as a mathematical function (e.g., risk quotient) of exposure levels and effect thresholds. Nowadays, a framework of in silico
models has emerged, linking key values such as source emission, concentrations
in environmental compartments, exposed concentrations at biological target sites,
and adverse efficacy or thresholds involved in the continuum of source to adverse
outcome of one queried chemical (Fig. 2.1) [20]. The framework needs parameter
modifications to be ready for application to other chemicals. For a large number of
concerning chemicals, the parameters might be virtually generated by quantitative
structure–activity relationship (QSAR) models in a high-throughput manner. Ultimately, the giant gap of safety data required by chemicals risk assessment could be
hopefully filled with this framework of computational toxicology in a truly pragmatic
sense.
19
2.2 Tasks for Computational Toxicology
Computational toxicology is a typical interdisciplinary field based on environmental chemistry, computational chemistry, chemo-bioinformatics, and systems biology,
etc., and it aims at facilitating prediction of environmental exposure, hazard, and risk
of chemicals by various in silico models. There are two major tasks for computational toxicology: to facilitate sound chemicals management and to shape digitized
predictive toxicology.
2.2.1 Facilitating Sound Chemicals Management
One of the urgent needs for sound chemicals management is to build capability to
assess virtually all the existing chemicals in markets, i.e., to build a scientific highthroughput system for chemicals risk assessment [1]. HTS technology has made a
steady contribution to this envisioned system, but it is still not sufficient.
In 2005, the US Environmental Protection Agency (EPA) founded the National
Center for Computational Toxicology to lead and implement research on computational toxicology [21]. Meanwhile, the Joint Research Center of the EU along with
many research groups have also carried out projects around core topics of computational toxicology under the 6th and 7th Framework Programs, such as OSIRIS
(Optimized Strategies for Risk Assessment of Industrial Chemicals through Integration of Non-test and Test Information) [22] and SEURAT (Safety Evaluation
Ultimately Replacing Animal Testing) [23]. In this sense, computational toxicology
or in silico toxicology serves as one of the tools to meet the requirement of certain
countries, regional organizations [e.g., Organization of Economic Cooperation and
Development (OECD)] and/or regulatory laws (e.g., REACH) for chemicals risk
assessment.
A classic risk assessment scheme includes hazard identification, exposure assessment, effect assessment (dose–response relationships), and risk characterization [24].
Risk characterization is always represented as a mathematical function (e.g., risk quotient) of exposure levels and effect thresholds. Nowadays, a framework of in silico
models has emerged, linking key values such as source emission, concentrations
in environmental compartments, exposed concentrations at biological target sites,
and adverse efficacy or thresholds involved in the continuum of source to adverse
outcome of one queried chemical (Fig. 2.1) [20]. The framework needs parameter
modifications to be ready for application to other chemicals. For a large number of
concerning chemicals, the parameters might be virtually generated by quantitative
structure–activity relationship (QSAR) models in a high-throughput manner. Ultimately, the giant gap of safety data required by chemicals risk assessment could be
hopefully filled with this framework of computational toxicology in a truly pragmatic
sense.