Cefic-lri Programme | European Chemical Industry Council

AIMT5.2 – A computational model for neural tube closure for in silico predictive toxicology of neural tube defects

Principal Investigator

Prof Dr Aldert Piersma
RIVM
National Institute for Public Health and the Environment
Centre for Health Protection
Antonie van Leeuwenhoeklaan 9
3720BA Bilthoven
The Netherlands
aldert.piersma@rivm.nl
Tel. +31 30 2742526/3485

Collaborators

Dr George Daston, Proctor & Gamble Company, Cincinnati, OH, daston.gp@pg.com

Description

The objective of this project is to translate the developmental ontology for neural tube closure, which was constructed in the LRI AIMT-5 project, into a computational model for predictive toxicology of neural tube defects. This represents a penultimate step for the proof of principle of this ontology approach towards designing computational solutions to chemical hazard and risk assessment with less reliance on animal testing.

In the LRI AIMT-5 project, we established a novel Developmental Toxicity Ontology (DTO), organizing information about Modes of Action (MoA) and their relationships with Adverse Outcome Pathways (AOPs) in developmental toxicity through an understanding of normal embryology. The DTO integrates MoA and AOP information from three different perspectives, the biological, the chemical and the toxicological perspective focusing on neural tube closure to provide a proof of principle for the ontology approach. The cellular and molecular mechanisms of neural tube closure have been subject of extensive studies, which have allowed us to compile existing information in an ontology framework using a standardized nomenclature that maps the different cell types involved, their morphogenetic functions, and regulatory cytokines and genes underlying their functionalities.

Further challenges for science and technology development remain toward building and testing a fully functional computational platform that can quantitatively predict the probability of a ‘teratological tipping point’ utilizing chemical structure information, in vitro data and in silico models for exposure and hazard.

Timeline: January 2019 > December 2019

LRI funding: € 158 000

Cefic-Lri Programme Responsible Care

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