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Artificial Intelligence for chemical risk assessment

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Artificial Intelligence for chemical risk assessment. / Wittwehr, Clemens; Blomstedt, Paul; Gosling, John Paul; Peltola, Tomi; Raffael, Barbara; Richarz, Andrea-Nicole; Sienkiewicz, Marta; Whaley, Paul; Worth, Andrew; Whelan, Maurice.

In: Computational Toxicology, Vol. 13, 100114, 01.02.2020.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Wittwehr, C, Blomstedt, P, Gosling, JP, Peltola, T, Raffael, B, Richarz, A-N, Sienkiewicz, M, Whaley, P, Worth, A & Whelan, M 2020, 'Artificial Intelligence for chemical risk assessment', Computational Toxicology, vol. 13, 100114. https://doi.org/10.1016/j.comtox.2019.100114

APA

Wittwehr, C., Blomstedt, P., Gosling, J. P., Peltola, T., Raffael, B., Richarz, A-N., Sienkiewicz, M., Whaley, P., Worth, A., & Whelan, M. (2020). Artificial Intelligence for chemical risk assessment. Computational Toxicology, 13, [100114]. https://doi.org/10.1016/j.comtox.2019.100114

Vancouver

Wittwehr C, Blomstedt P, Gosling JP, Peltola T, Raffael B, Richarz A-N et al. Artificial Intelligence for chemical risk assessment. Computational Toxicology. 2020 Feb 1;13. 100114. https://doi.org/10.1016/j.comtox.2019.100114

Author

Wittwehr, Clemens ; Blomstedt, Paul ; Gosling, John Paul ; Peltola, Tomi ; Raffael, Barbara ; Richarz, Andrea-Nicole ; Sienkiewicz, Marta ; Whaley, Paul ; Worth, Andrew ; Whelan, Maurice. / Artificial Intelligence for chemical risk assessment. In: Computational Toxicology. 2020 ; Vol. 13.

Bibtex

@article{a8c0ccbef01f4611b4586731906d0f01,
title = "Artificial Intelligence for chemical risk assessment",
abstract = "As the basis for managing the risks of chemical exposure, the Chemical Risk Assessment (CRA) process can impact a substantial part of the economy, the health of hundreds of millions of people, and the condition of the environment. However, the number of properly assessed chemicals falls short of societal needs due to a lack of experts for evaluation, interference of third party interests, and the sheer volume of potentially relevant information on the chemicals from disparate sources.In order to explore ways in which computational methods may help overcome this discrepancy between the number of chemical risk assessments required on the one hand and the number and adequateness of assessments actually being conducted on the other, the European Commission's Joint Research Centre organised a workshop on Artificial Intelligence for Chemical Risk Assessment (AI4CRA).The workshop identified a number of areas where Artificial Intelligence could potentially increase the number and quality of regulatory risk management decisions based on CRA, involving process simulation, supporting evaluation, identifying problems, facilitating collaboration, finding experts, evidence gathering, systematic review, knowledge discovery, and building cognitive models. Although these are interconnected, they are organised and discussed under two main themes: scientific-technical process and social aspects and the decision making process.",
author = "Clemens Wittwehr and Paul Blomstedt and Gosling, {John Paul} and Tomi Peltola and Barbara Raffael and Andrea-Nicole Richarz and Marta Sienkiewicz and Paul Whaley and Andrew Worth and Maurice Whelan",
year = "2020",
month = feb,
day = "1",
doi = "10.1016/j.comtox.2019.100114",
language = "English",
volume = "13",
journal = "Computational Toxicology",
publisher = "Elsevier",
note = "Artificial Intelligence for Chemical Risk Assessment, AI4CRA ; Conference date: 04-04-2018 Through 05-04-2018",

}

RIS

TY - JOUR

T1 - Artificial Intelligence for chemical risk assessment

AU - Wittwehr, Clemens

AU - Blomstedt, Paul

AU - Gosling, John Paul

AU - Peltola, Tomi

AU - Raffael, Barbara

AU - Richarz, Andrea-Nicole

AU - Sienkiewicz, Marta

AU - Whaley, Paul

AU - Worth, Andrew

AU - Whelan, Maurice

PY - 2020/2/1

Y1 - 2020/2/1

N2 - As the basis for managing the risks of chemical exposure, the Chemical Risk Assessment (CRA) process can impact a substantial part of the economy, the health of hundreds of millions of people, and the condition of the environment. However, the number of properly assessed chemicals falls short of societal needs due to a lack of experts for evaluation, interference of third party interests, and the sheer volume of potentially relevant information on the chemicals from disparate sources.In order to explore ways in which computational methods may help overcome this discrepancy between the number of chemical risk assessments required on the one hand and the number and adequateness of assessments actually being conducted on the other, the European Commission's Joint Research Centre organised a workshop on Artificial Intelligence for Chemical Risk Assessment (AI4CRA).The workshop identified a number of areas where Artificial Intelligence could potentially increase the number and quality of regulatory risk management decisions based on CRA, involving process simulation, supporting evaluation, identifying problems, facilitating collaboration, finding experts, evidence gathering, systematic review, knowledge discovery, and building cognitive models. Although these are interconnected, they are organised and discussed under two main themes: scientific-technical process and social aspects and the decision making process.

AB - As the basis for managing the risks of chemical exposure, the Chemical Risk Assessment (CRA) process can impact a substantial part of the economy, the health of hundreds of millions of people, and the condition of the environment. However, the number of properly assessed chemicals falls short of societal needs due to a lack of experts for evaluation, interference of third party interests, and the sheer volume of potentially relevant information on the chemicals from disparate sources.In order to explore ways in which computational methods may help overcome this discrepancy between the number of chemical risk assessments required on the one hand and the number and adequateness of assessments actually being conducted on the other, the European Commission's Joint Research Centre organised a workshop on Artificial Intelligence for Chemical Risk Assessment (AI4CRA).The workshop identified a number of areas where Artificial Intelligence could potentially increase the number and quality of regulatory risk management decisions based on CRA, involving process simulation, supporting evaluation, identifying problems, facilitating collaboration, finding experts, evidence gathering, systematic review, knowledge discovery, and building cognitive models. Although these are interconnected, they are organised and discussed under two main themes: scientific-technical process and social aspects and the decision making process.

U2 - 10.1016/j.comtox.2019.100114

DO - 10.1016/j.comtox.2019.100114

M3 - Journal article

VL - 13

JO - Computational Toxicology

JF - Computational Toxicology

M1 - 100114

T2 - Artificial Intelligence for Chemical Risk Assessment

Y2 - 4 April 2018 through 5 April 2018

ER -