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1.
Regul Toxicol Pharmacol ; 132: 105161, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-35508214

RESUMO

Parabens are esters of para-hydroxybenzoic acid that have been used as preservatives in many types of products for decades including agrochemicals, pharmaceuticals, food and cosmetics. This illustrative case study with propylparaben (PP) demonstrates a 10-step read-across (RAX) framework in practice. It aims at establishing a proof-of-concept for the value added by new approach methodologies (NAMs) in read-across (RAX) for use in a next-generation risk assessment (NGRA) in order to assess consumer safety after exposure to PP-containing cosmetics. In addition to structural and physico-chemical properties, in silico information, toxicogenomics, in vitro toxicodynamic, toxicokinetic data from PBK models, and bioactivity data are used to provide evidence of the chemical and biological similarity of PP and analogues and to establish potency trends for observed effects in vitro. The chemical category under consideration is short (C1-C4) linear chain n-alkyl parabens: methylparaben, ethylparaben, propylparaben and butylparaben. The goal of this case study is to illustrate how a practical framework for RAX can be used to fill a hypothetical data gap for reproductive toxicity of the target chemical PP.


Assuntos
Cosméticos , Parabenos , Cosméticos/química , Cosméticos/toxicidade , Parabenos/química , Parabenos/toxicidade , Conservantes Farmacêuticos/toxicidade , Reprodução , Medição de Risco/métodos
2.
Regul Toxicol Pharmacol ; 131: 105132, 2022 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-35217105

RESUMO

A novel approach was developed to help characterize the biokinetics of the cosmetic ingredient, phenoxyethanol, to help assess the safety of the parent and its major stable metabolite. In the first step of this non-animal tiered approach, primary human hepatocytes were used to confirm or refute in silico predicted metabolites, and elucidate the intrinsic clearance of phenoxyethanol. A key result was the identification of the major metabolite, phenoxyacetic acid (PAA), the exposure to which in the kidney was subsequently predicted to far exceed that of phenoxyethanol in blood or other tissues. Therefore, a novel aspect of this approach was to measure in the subsequent step the formation of PAA in the cells dosed with phenoxyethanol that were used to provide points of departure (PoDs) and express the intracellular exposure as the Cmax and AUC24. This enabled the calculation of the intracellular concentrations of parent and metabolite at the PoD in the cells used to derive this value. These concentrations can be compared with in vivo tissue levels to conclude on the safety margin. The lessons from this case study will help to inform the design of other non-animal safety assessments.


Assuntos
Cosméticos , Etilenoglicóis , Cosméticos/toxicidade , Etilenoglicóis/toxicidade , Humanos , Medição de Risco
3.
Regul Toxicol Pharmacol ; 129: 105094, 2022 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-34990780

RESUMO

This paper presents a 10-step read-across (RAX) framework for use in cases where a threshold of toxicological concern (TTC) approach to cosmetics safety assessment is not possible. RAX builds on established approaches that have existed for more than two decades using chemical properties and in silico toxicology predictions, by further substantiating hypotheses on toxicological similarity of substances, and integrating new approach methodologies (NAM) in the biological and kinetic domains. NAM include new types of data on biological observations from, for example, in vitro assays, toxicogenomics, metabolomics, receptor binding screens and uses physiologically-based kinetic (PBK) modelling to inform about systemic exposure. NAM data can help to substantiate a mode/mechanism of action (MoA), and if similar chemicals can be shown to work by a similar MoA, a next generation risk assessment (NGRA) may be performed with acceptable confidence for a data-poor target substance with no or inadequate safety data, based on RAX approaches using data-rich analogue(s), and taking account of potency or kinetic/dynamic differences.


Assuntos
Cosméticos/toxicidade , Toxicologia/métodos , Simulação por Computador , Técnicas In Vitro , Metabolômica , Medição de Risco , Toxicocinética , Toxicologia/normas
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