[HTML][HTML] Using historical control data in bioassays for regulatory toxicology

FM Kluxen, K Weber, C Strupp, SM Jensen… - Regulatory Toxicology …, 2021 - Elsevier
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 …

[HTML][HTML] Practical guidance to evaluate in vitro dermal absorption studies for pesticide registration: An industry perspective

FM Kluxen, E Felkers, SM Jensen… - Regulatory Toxicology …, 2023 - Elsevier
While there are some regulatory assessment criteria available on how to generally evaluate
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

PSR Wright, GF Smith, KA Briggs, R Thomas… - Regulatory Toxicology …, 2023 - Elsevier
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 …

bmd: an R package for benchmark dose estimation

SM Jensen, FM Kluxen, JC Streibig, N Cedergreen… - PeerJ, 2020 - peerj.com
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 …

[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 …

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 …

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 …

[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 …

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 …

Benchmark dose modelling in regulatory ecotoxicology, a potential tool in pest management

SM Jensen, FM Kluxen, C Ritz - Pest Management Science, 2022 - Wiley Online Library
For several authorities, benchmark dose (BMD) methodology has become the
recommended approach by which to derive reference values for risk assessment. However …