PharmaceuticalsBackground/Objectives: Drug-Induced Kidney Injury (DIKI) presents a significant challenge in drug development, often leading to clinical-stage failures. The early prediction of DIKI risk can improve drug safety and development efficiency. Existing models
Mohan Rao +6 more
doaj +1 more source
Quantitative toxicity prediction using topology based multi-task deep neural networks
, 2017 The understanding of toxicity is of paramount importance to human health and environmental protection. Quantitative toxicity analysis has become a new standard in the field.
Wei, Guo-Wei, Wu, Kedi
core +2 more sources
Federated Learning in Computational Toxicology: An Industrial Perspective on the Effiris Hackathon. [PDF]
Chem Res Toxicol, 2023 Bassani D, Brigo A, Andrews-Morger A.
europepmc +1 more source
Changepoint in Linear Relations [PDF]
arXiv, 2019 Linear relations, containing measurement errors in input and output data, are considered. Parameters of these so-called errors-in-variables models can change at some unknown moment. The aim is to test whether such an unknown change has occurred or not. For instance, detecting a change in trend for a randomly spaced time series is a special case of the ...
arxiv
Analysis of biomarker utility using a PBPK/PD model for carbaryl
Frontiers in Pharmacology, 2014 There are many types of biomarkers; the two common ones are biomarkers of exposure and biomarkers of effect. The utility of a biomarker for estimating exposures or predicting risks depends on the strength of the correlation between biomarker ...
Martin Blake Phillips +3 more
doaj +1 more source
ToxicR: A computational platform in R for computational toxicology and dose-response analyses. [PDF]
Comput Toxicol, 2023 Wheeler MW +12 more
europepmc +1 more source
Toxicity Prediction using Deep Learning [PDF]
arXiv, 2015 Everyday we are exposed to various chemicals via food additives, cleaning and cosmetic products and medicines -- and some of them might be toxic. However testing the toxicity of all existing compounds by biological experiments is neither financially nor logistically feasible.
arxiv
In Vitro and Predictive Computational Toxicology Methods for the Neurotoxic Pesticide Amitraz and Its Metabolites. [PDF]
Brain Sci, 2023 Giorgini M +4 more
europepmc +1 more source
Failure of Optimal Design Theory? A Case Study in Toxicology Using Sequential Robust Optimal Design Framework [PDF]
arXivThis paper presents a quasi-sequential optimal design framework for toxicology experiments, specifically applied to sea urchin embryos. The authors propose a novel approach combining robust optimal design with adaptive, stage-based testing to improve efficiency in toxicological studies, particularly where traditional uniform designs fall short.
arxiv
An assessment of organic solvent based equilibrium partitioning methods for predicting the bioconcentration behavior of perfluorinated sulfonic acids, carboxylic acids, and sulfonamides [PDF]
, 2009 SPARC, KOWWIN, and ALOGPS octanol-water partitioning (log K~ow~) and distribution (log D) constants were calculated for all C~1~ through C~8~ and the straight chain C~9~ through C~15~ perfluoroalkyl sulfonic acids (PFSAs) and carboxylic acids (PFCAs ...
Kaya Forest, Sierra Rayne
core +1 more source