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Toxicol In Vitro. 2017 Dec;45(Pt 2):249-257. doi: 10.1016/j.tiv.2017.03.004. Epub 2017 Mar 18.

Automated workflows for modelling chemical fate, kinetics and toxicity.

Author information

1
Chemical Safety and Alternative Methods Unit, EURL ECVAM, Directorate F - Health, Consumers and Reference Materials, Joint Research Centre, European Commission, Ispra, Italy.
2
Chemical Safety and Alternative Methods Unit, EURL ECVAM, Directorate F - Health, Consumers and Reference Materials, Joint Research Centre, European Commission, Ispra, Italy. Electronic address: alicia.paini@ec.europa.eu.
3
Liverpool John Moores University, School of Pharmacy and Biomolecular Sciences, Byrom Street, Liverpool L3 3AF, UK.
4
KNIME.com AG, Zurich, Switzerland.
5
Universität Konstanz, Fachbereich Informatik und Informationswissenschaft, Box 712, 78457 Konstanz, Germany.

Abstract

Automation is universal in today's society, from operating equipment such as machinery, in factory processes, to self-parking automobile systems. While these examples show the efficiency and effectiveness of automated mechanical processes, automated procedures that support the chemical risk assessment process are still in their infancy. Future human safety assessments will rely increasingly on the use of automated models, such as physiologically based kinetic (PBK) and dynamic models and the virtual cell based assay (VCBA). These biologically-based models will be coupled with chemistry-based prediction models that also automate the generation of key input parameters such as physicochemical properties. The development of automated software tools is an important step in harmonising and expediting the chemical safety assessment process. In this study, we illustrate how the KNIME Analytics Platform can be used to provide a user-friendly graphical interface for these biokinetic models, such as PBK models and VCBA, which simulates the fate of chemicals in vivo within the body and in vitro test systems respectively.

KEYWORDS:

Automated workflows; KNIME; PBPK; Physiologically based kinetic models; Toxicity; Virtual cell based assay

PMID:
28323105
PMCID:
PMC5745146
DOI:
10.1016/j.tiv.2017.03.004
[Indexed for MEDLINE]
Free PMC Article

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