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[HTML][HTML] Using historical control data in bioassays for regulatory toxicology
Historical control data (HCD) consist of pooled control group responses from bioassays.
These data must be collected and are often used or reported in regulatory toxicology studies …
These data must be collected and are often used or reported in regulatory toxicology studies …
[HTML][HTML] Practical guidance to evaluate in vitro dermal absorption studies for pesticide registration: An industry perspective
While there are some regulatory assessment criteria available on how to generally evaluate
dermal absorption (DA) studies for risk assessment purposes, practical guidance and …
dermal absorption (DA) studies for risk assessment purposes, practical guidance and …
[HTML][HTML] Retrospective analysis of the potential use of virtual control groups in preclinical toxicity assessment using the eTOX database
Abstract Virtual Control Groups (VCGs) based on Historical Control Data (HCD) in
preclinical toxicity testing have the potential to reduce animal usage. As a case study we …
preclinical toxicity testing have the potential to reduce animal usage. As a case study we …
bmd: an R package for benchmark dose estimation
The benchmark dose (BMD) methodology is used to derive a hazard characterization
measure for risk assessment in toxicology or ecotoxicology. The present paper's objective is …
measure for risk assessment in toxicology or ecotoxicology. The present paper's objective is …
[HTML][HTML] Metribuzin-induced non-adverse liver changes result in rodent-specific non-adverse thyroid effects via uridine 5′-diphospho-glucuronosyltransferase …
W Bomann, H Tinwell, P Jenkinson… - Regulatory Toxicology and …, 2021 - Elsevier
Metribuzin is a herbicide that inhibits photosynthesis and has been used for over 40 years.
Its main target organ is the liver and to some extent the kidney in rats, dogs, and rabbits …
Its main target organ is the liver and to some extent the kidney in rats, dogs, and rabbits …
Application of Artificial Intelligence and Machine Learning in Computational Toxicology in Aquatic Toxicology
M Banaee, A Zeidi, C Faggio - Pollution, 2024 - jpoll.ut.ac.ir
Computational toxicology is a rapidly growing field that utilizes artificial intelligence (AI) and
machine learning (ML) to predict the toxicity of chemical compounds. Computational …
machine learning (ML) to predict the toxicity of chemical compounds. Computational …
Use compatibility intervals in regulatory toxicology
LA Hothorn, R Pirow - Regulatory Toxicology and Pharmacology, 2020 - Elsevier
Recently it was recommended to avoid significance tests, in particular dichotomization into
significant/non-significant on the basis of a p-value and a fixed 5% significance level (ie …
significant/non-significant on the basis of a p-value and a fixed 5% significance level (ie …
[PDF][PDF] " New statistics" in regulatory toxicology?
FM Kluxen - Regul Toxicol Pharmacol, 2020 - researchgate.net
The p-value has long been criticized in various scientific disciplines. Some journals banned
its use and the American Statistical Association and a Nature article suggested to abandon …
its use and the American Statistical Association and a Nature article suggested to abandon …
Deep learning-based available and common clinical-related feature variables robustly predict survival in community-acquired pneumonia
DY Feng, Y Ren, M Zhou, XL Zou, WB Wu… - … and healthcare policy, 2021 - Taylor & Francis
Background Community-acquired pneumonia (CAP) is a leading cause of morbidity and
mortality worldwide. Although there are many predictors of death for CAP, there are still …
mortality worldwide. Although there are many predictors of death for CAP, there are still …
Benchmark dose modelling in regulatory ecotoxicology, a potential tool in pest management
For several authorities, benchmark dose (BMD) methodology has become the
recommended approach by which to derive reference values for risk assessment. However …
recommended approach by which to derive reference values for risk assessment. However …