Dose-Response Models for Correlated Multinomial Data from Developmental Toxicity Studies

1994 ◽  
Vol 43 (4) ◽  
pp. 583 ◽  
Author(s):  
Y. Zhu ◽  
D. Krewski ◽  
W. H. Ross
Keyword(s):  
Dose Response ◽  
Developmental Toxicity ◽  
Response Models ◽  
Multinomial Data ◽  
Toxicity Studies

scholarly journals Summary of Dose-Response Modeling for Developmental Toxicity Studies

Dose-Response ◽  
2008 ◽  
Vol 6 (4) ◽  
pp. dose-response.0 ◽  
Author(s):  
Daniel L. Hunt ◽  
Shesh N. Rai ◽  
Chin-Shang Li
Keyword(s):  
Risk Assessment ◽  
Dose Response ◽  
Response Pattern ◽  
Threshold Model ◽  
Developmental Toxicity ◽  
Discrete Distribution ◽  
Assessment Process ◽  
Future Research ◽  
Advantages And Disadvantages ◽  
Toxicity Studies

Developmental toxicity studies are an important area in the field of toxicology. Endpoints measured on fetuses include weight and indicators of death and malformation. Binary indicator measures are typically summed over the litter and a discrete distribution is assumed to model the number of adversely affected fetuses. Additionally, there is noticeable variation in the litter responses within dose groups that should be taken into account when modeling. Finally, the dose-response pattern in these studies exhibits a threshold effect. The threshold dose-response model is the default model for non-carcinogenic risk assessment, according to the USEPA, and is encouraged by the agency for the use in the risk assessment process. Two statistical models are proposed to estimate dose-response pattern of data from the developmental toxicity study: the threshold model and the spline model. The models were applied to two data sets. The advantages and disadvantages of these models, potential other models, and future research possibilities will be summarized.

scholarly journals Dose-Response Modeling with Summary Data from Developmental Toxicity Studies

Risk Analysis ◽  
2016 ◽  
Vol 37 (5) ◽  
pp. 905-917 ◽  
Author(s):  
John F. Fox ◽  
Karen A. Hogan ◽  
Allen Davis
Keyword(s):  
Dose Response ◽  
Developmental Toxicity ◽  
Toxicity Studies ◽  
Response Modeling ◽  
Summary Data

scholarly journals REPRODUCTIVE AND DEVELOPMENTAL TOXICITY STUDIES OF PRULIFLOXACIN (NM441) (4) : A Perinatal and Postnatal Study in Rats by Oral Administration

1996 ◽  
Vol 21 (SupplementI) ◽  
pp. 219-230 ◽  
Author(s):  
Tagahiko MORINAGA ◽  
Shigenobu FUJII ◽  
Shigenori FURUKAWA ◽  
Mikito KIKUMORI ◽  
Kimio YASUHIRA ◽  
...  
Keyword(s):  
Oral Administration ◽  
Developmental Toxicity ◽  
Toxicity Studies

Historical control data on developmental toxicity studies in rodents

2014 ◽  
Vol 54 (3) ◽  
pp. 150-161 ◽  
Author(s):  
Makoto Ema ◽  
Katsumi Endoh ◽  
Ryou Fukushima ◽  
Sakiko Fujii ◽  
Hiroaki Hara ◽  
...  
Keyword(s):  
Developmental Toxicity ◽  
Historical Control ◽  
Control Data ◽  
Toxicity Studies ◽  
Historical Control Data

scholarly journals Weighted mixed-effects dose–response models for tables of correlated contrasts

2021 ◽  
Vol 21 (2) ◽  
pp. 320-347
Author(s):  
Nicola Orsini
Keyword(s):  
Dose Response ◽  
Response Pattern ◽  
Mixed Effects ◽  
Data Generation ◽  
Measures Of Association ◽  
Response Models ◽  
Response Data ◽  
Hazard Ratios ◽  
Health Related ◽  
Generation Mechanisms

Recognizing a dose–response pattern based on heterogeneous tables of contrasts is hard. Specification of a statistical model that can consider the possible dose–response data-generating mechanism, including its variation across studies, is crucial for statistical inference. The aim of this article is to increase the understanding of mixed-effects dose–response models suitable for tables of correlated estimates. One can use the command drmeta with additive (mean difference) and multiplicative (odds ratios, hazard ratios) measures of association. The postestimation command drmeta_graph greatly facilitates the visualization of predicted average and study-specific dose–response relationships. I illustrate applications of the drmeta command with regression splines in experimental and observational data based on nonlinear and random-effects data-generation mechanisms that can be encountered in health-related sciences.

scholarly journals Predicting the in vivo developmental toxicity of benzo[a]pyrene (BaP) in rats by an in vitro–in silico approach

2021 ◽  
Author(s):  
Danlei Wang ◽  
Maartje H. Rietdijk ◽  
Lenny Kamelia ◽  
Peter J. Boogaard ◽  
Ivonne M. C. M. Rietjens
Keyword(s):  
Dose Response ◽  
In Silico ◽  
Response Curve ◽  
Developmental Toxicity ◽  
Toxicity Testing ◽  
Maximal Effect ◽  
Blood Concentrations ◽  
Reverse Dosimetry

AbstractDevelopmental toxicity testing is an animal-intensive endpoints in toxicity testing and calls for animal-free alternatives. Previous studies showed the applicability of an in vitro–in silico approach for predicting developmental toxicity of a range of compounds, based on data from the mouse embryonic stem cell test (EST) combined with physiologically based kinetic (PBK) modelling facilitated reverse dosimetry. In the current study, the use of this approach for predicting developmental toxicity of polycyclic aromatic hydrocarbons (PAHs) was evaluated, using benzo[a]pyrene (BaP) as a model compound. A rat PBK model of BaP was developed to simulate the kinetics of its main metabolite 3-hydroxybenzo[a]pyrene (3-OHBaP), shown previously to be responsible for the developmental toxicity of BaP. Comparison to in vivo kinetic data showed that the model adequately predicted BaP and 3-OHBaP blood concentrations in the rat. Using this PBK model and reverse dosimetry, a concentration–response curve for 3-OHBaP obtained in the EST was translated into an in vivo dose–response curve for developmental toxicity of BaP in rats upon single or repeated dose exposure. The predicted half maximal effect doses (ED50) amounted to 67 and 45 mg/kg bw being comparable to the ED50 derived from the in vivo dose–response data reported for BaP in the literature, of 29 mg/kg bw. The present study provides a proof of principle of applying this in vitro–in silico approach for evaluating developmental toxicity of BaP and may provide a promising strategy for predicting the developmental toxicity of related PAHs, without the need for extensive animal testing.

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