Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Automated workflows for modelling chemical fate, kinetics and toxicity.

Benito, JVS, Paini, A, Richarz, A-N, Meinl, T, Berthold, MR, Cronin, MTD and Worth, AP (2017) Automated workflows for modelling chemical fate, kinetics and toxicity. Toxicology In Vitro. ISSN 0887-2333

[img]
Preview
Text
Automated workflows for modelling chemical fate, kinetics and toxicity..pdf - Accepted Version
Available under License Creative Commons Attribution.

Download (763kB) | Preview

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.

Item Type: Article
Uncontrolled Keywords: 1115 Pharmacology And Pharmaceutical Sciences
Subjects: Q Science > QA Mathematics > QA76 Computer software
Q Science > QD Chemistry
Divisions: Pharmacy & Biomolecular Sciences
Publisher: Elsevier
Related URLs:
Date Deposited: 28 Mar 2017 10:44
Last Modified: 04 Sep 2021 11:45
DOI or ID number: 10.1016/j.tiv.2017.03.004
URI: https://researchonline.ljmu.ac.uk/id/eprint/6137
View Item View Item