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Updated: Apr 4, 2026

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
Published on: March 14, 2019
CHEMICAL AND BIOLOGICAL DESCRIPTOR INTEGRATION IMPROVES COMPUTATIONAL MODELING OF IN VIVO RAT TOXICITY
Cristian G Bologa1, Oleg Ursu1, Liliana Halip2
1Translational Informatics Division, Department of Internal Medicine, MSC09 5025, University of New Mexico School of Medicine, Albuquerque, NM 87131, USA.
Abstract:
Computational toxicology is a new discipline in the area of computational molecular sciences, which is rapidly developing as a result of the public interest stirred by several European and US initiatives. Here, we report the use of primary high throughput screening (HTS) data as biological descriptors to complement the chemical descriptors for the modelling of the acute toxicity. The combination of biological and chemical descriptors was performed on the median lethal dose following oral administration in rats (rat LD50). The hybrid model developed based on chemical and biological descriptors is superior to models based on the chemical or biological description alone. Using this model, besides the accurately prediction of a compound's toxicity we also identified molecular fragments whose presence may contribute to increase or decrease of the toxicity.
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