Literature DB >> 35188636

In Silico Models for Repeated-Dose Toxicity (RDT): Prediction of the No Observed Adverse Effect Level (NOAEL) and Lowest Observed Adverse Effect Level (LOAEL) for Drugs.

Fabiola Pizzo1, Domenico Gadaleta2, Emilio Benfenati2.   

Abstract

Many regulatory contexts require the evaluation of repeated-dose toxicity (RDT) studies conducted in laboratory animals. The main outcome of RDT studies is the identification of the no observed adverse effect level (NOAEL) and the lowest observed adverse effect level (LOAEL) that are normally used as point of departure for the establishment of health-based guidance values. Since in vivo RDT studies are expensive and time-consuming, in silico approaches could offer a valuable alternative. However, NOAEL and LOAEL modeling suffer some limitations since they do not refer to a single end point but to several different effects, and the doses used in experimental studies strongly influence the results. Few attempts to model NOAEL and LOAEL have been reported. The available database and models for the prediction of NOAEL and LOAEL are reviewed here.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Chronic toxicity; Drug safety; In silico models; LOAEL; NOAEL; Repeated-dose toxicity

Mesh:

Substances:

Year:  2022        PMID: 35188636     DOI: 10.1007/978-1-0716-1960-5_11

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  34 in total

1.  Assessing toxicological data quality: basic principles, existing schemes and current limitations.

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2.  REPDOSE: A database on repeated dose toxicity studies of commercial chemicals--A multifunctional tool.

Authors:  A Bitsch; S Jacobi; C Melber; U Wahnschaffe; N Simetska; I Mangelsdorf
Journal:  Regul Toxicol Pharmacol       Date:  2006-08-28       Impact factor: 3.271

3.  Correlation of structural class with no-observed-effect levels: a proposal for establishing a threshold of concern.

Authors:  I C Munro; R A Ford; E Kennepohl; J G Sprenger
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Review 4.  Estimation of toxic hazard--a decision tree approach.

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5.  ToxRefDB version 2.0: Improved utility for predictive and retrospective toxicology analyses.

Authors:  Sean Watford; Ly Ly Pham; Jessica Wignall; Robert Shin; Matthew T Martin; Katie Paul Friedman
Journal:  Reprod Toxicol       Date:  2019-07-21       Impact factor: 3.143

Review 6.  In silico prediction of drug toxicity.

Authors:  John C Dearden
Journal:  J Comput Aided Mol Des       Date:  2003 Feb-Apr       Impact factor: 3.686

7.  Use of epidemiologic data in Integrated Risk Information System (IRIS) assessments.

Authors:  Amanda S Persad; Glinda S Cooper
Journal:  Toxicol Appl Pharmacol       Date:  2008-01-31       Impact factor: 4.219

8.  Profiling chemicals based on chronic toxicity results from the U.S. EPA ToxRef Database.

Authors:  Matthew T Martin; Richard S Judson; David M Reif; Robert J Kavlock; David J Dix
Journal:  Environ Health Perspect       Date:  2008-10-20       Impact factor: 9.031

Review 9.  The basics of preclinical drug development for neurodegenerative disease indications.

Authors:  Karen L Steinmetz; Edward G Spack
Journal:  BMC Neurol       Date:  2009-06-12       Impact factor: 2.474

10.  Comparison of Points of Departure for Health Risk Assessment Based on High-Throughput Screening Data.

Authors:  Salomon Sand; Fred Parham; Christopher J Portier; Raymond R Tice; Daniel Krewski
Journal:  Environ Health Perspect       Date:  2016-07-06       Impact factor: 9.031

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  1 in total

1.  Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity.

Authors:  Gianluca Selvestrel; Giovanna J Lavado; Alla P Toropova; Andrey A Toropov; Domenico Gadaleta; Marco Marzo; Diego Baderna; Emilio Benfenati
Journal:  Int J Mol Sci       Date:  2022-06-14       Impact factor: 6.208

  1 in total

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