Cancer risk assesment for health care workers occupationally exposed to cyclphosphamide

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REACH, non-testing approaches and the urgent need for a change in mind set

The objectives of REACH cannot be achieved under the current risk assessment approach. A change in mind set among all the relevant stakeholders is needed: risk assessment should move away from a labor-intensive and animal-consuming approach to intelligent and pragmatic testing, by combining exposure and hazard data effectively and trying to group chemicals (category approaches). The focus should be on reducing the overall uncertainties of 30,000 chemicals while acknowledging the existence of the uncertainty paradox: reducing uncertainty in the assessment of individual chemicals following the classical chemical-by-chemical approach as we have in previous decades will result in a prolongation of uncertainty for the entire group of 30,000 chemicals as a whole. With the first REACH registration deadline (2010) rapidly approaching, a mind set change is urgently needed. We can speed up the regulatory acceptance process, starting with the maximum use of currently available exposure and hazard data, tools and models. Optimal use should also be made of experimental exposure and hazard data generated under REACH. Only such an approach will make it possible to obtain a sufficient level of information within the time frame of REACH. A much more intensive dialogue between stakeholders is necessary. © 2008 Elsevier Inc. All rights reserved

Risk estimation for carcinogens based on epidemiological data: a structured approach, illustrated by an example on chromium.

It is generally recognized that human, epidemiological data, if available, are preferred as the starting point for quantitative risk analysis above the use of data from animal studies. Although methods to obtain proper risk estimates from epidemiological data are available, several impediments prevent their widespread application. These impediments include unfamiliarity with epidemiological methods and the lack of a structured and transparent approach. We described a framework to conduct quantitative cancer risk assessment based on epidemiological studies in a structured, transparent, and reproducible manner. Important features of the process include a weight-of-the-evidence approach, estimation of the optimal exposure-risk function by fitting a regression model to the epidemiological data, estimation of uncertainty introduced by potential biases and missing information in the epidemiological studies, and calculation of excess lifetime risk through a life table to take into account competing risks. Sensitivity analyses are a useful tool to obtain insight into the impact of assumptions made and the variability of the underlying data. The framework is sufficiently flexible to allow many types of data, ranging from published, sometimes incomplete data to detailed individual data, while maintaining an optimal result, i.e., a state-of-the-art risk estimate with confidence intervals, based on all available evidence of sufficient quality

Stoffenmanager Nano Version 1.0: AWeb-Based Tool for Risk Prioritization of Airborne Manufactured Nano Objects

Stoffenmanager Nano (version 1.0) is a risk-banding tool developed for employers and employees to prioritize health risks occurring as a result of exposure to manufactured nano objects (MNOs) for a broad range of worker scenarios and to assist implementation of control measures to reduce exposure levels. In order to prioritize the health risks, the Stoffenmanager Nano combines the available hazard information of a substance with a qualitative estimate of potential for inhalation exposure. The development of the Stoffenmanager Nano started with a review of the available literature on control banding. Input parameters for the hazard assessment of MNOs were selected based on the availability of these parameters in, for instance, Safety Data Sheets or product information sheets. The conceptual exposure model described by Schneider et al. (2011) was used as the starting point for exposure banding. During the development of the Stoffenmanager Nano tool, the precautionary principle was applied to deal with the uncertainty regarding hazard and exposure assessment of MNOs. Subsequently, the model was converted into an online tool (http://nano.stoffenmanager.nl), tested, and reviewed by a number of companies. In this paper, we describe the Stoffenmanager Nano. This tool offers a practical approach for risk prioritization in exposure situations where quantitative risk assessment is currently not possible. Updates of this first version are anticipated as more data become available in the future

Risk estimation for carcinogens based on epidemiological data: A structured approach, illustrated by an example on chromium

It is generally recognized that human, epidemiological data, if available, are preferred as the starting point for quantitative risk analysis above the use of data from animal studies. Although methods to obtain proper risk estimates from epidemiological data are available, several impediments prevent their widespread application. These impediments include unfamiliarity with epidemiological methods and the lack of a structured and transparent approach. We described a framework to conduct quantitative cancer risk assessment based on epidemiological studies in a structured, transparent, and reproducible manner. Important features of the process include a weight-of-the-evidence approach, estimation of the optimal exposure-risk function by fitting a regression model to the epidemiological data, estimation of uncertainty introduced by potential biases and missing information in the epidemiological studies, and calculation of excess lifetime risk through a life table to take into account competing risks. Sensitivity analyses are a useful tool to obtain insight into the impact of assumptions made and the variability of the underlying data. The framework is sufficiently flexible to allow many types of data, ranging from published, sometimes incomplete data to detailed individual data, while maintaining an optimal result, i.e., a state-of-the-art risk estimate with confidence intervals, based on all available evidence of sufficient quality. © 2006 Elsevier Inc. All rights reserved

A Family of Water-Immiscible, Dipolar Aprotic, Diamide Solvents from Succinic Acid

Three dipolar aprotic solvents were designed to possess high dipolarity and low toxicity: N,N,N′,N′-tetrabutylsuccindiamide (TBSA), N,N′-diethyl-N,N′-dibutylsuccindiamide (EBSA), and N,N′-dimethyl-N,N′-dibutylsuccindiamide (MBSA). They were synthesized catalytically by using a K60 silica catalyst in a solventless system. Their water immiscibility stands out as an unusual and useful property for dipolar aprotic solvents. They were tested in a model Heck reaction, metal–organic framework syntheses, and a selection of polymer solubility experiments in which their performances were found to be comparable to traditional solvents. Furthermore, MBSA was found to be suitable for the production of an industrially relevant membrane from polyethersulfone. An integrated approach involving in silico analysis based on available experimental information, prediction model outcomes and read across data, as well as a panel of in vitro reporter gene assays covering a broad range of toxicological endpoints was used to assess toxicity. These in silico and in vitro tests suggested no alarming indications of toxicity in the new solvents

Integration of new approach methods in a structure based read-across for DART effects

Read-across is one of the most often applied alternative tools for hazard assessment, in particular for complex endpoints such as toxicity after repeated exposure or developmental and reproductive toxicity. We have applied this approach to a series of six aliphatic carboxylic acids that have developmental toxicity data, some being positive, some negative. For one of these compounds, 2-Methylhexanoic acid (MHA), we have specifically blinded this toxicity data, and we have applied new approach methodologies (NAM) to substantiate the read across of the other compounds (as source compounds) to MHA, and to explore whether these NAM correctly predict the in vivo developmental toxicity of MHA. Thus, we have tested MHA and the five analogues in a battery of in vitro tests with clear relevance to DART, i.e. the Zebrafish Embryo Test (ZET), mouse Embryonic Stem cell Test (mEST), iPSC-based neurodevelopmental model (UKN1), and a series of CALUX Reporter assays, and combined this with toxicokinetic models to calculate effective cellular concentrations and associated in vivo exposure doses. We also included two positive, and one negative control compound in this test. As the histone deacetylase enzyme is postulated to be the molecular initiating target leading to neural tube defects with these compounds, we have also investigated the potential of these six analogues to inhibit this enzyme in ZET, mEST, and UKN1 models. The NAM quite well predicted the in vivo developmental outcome of these six aliphatic carboxylic acids. This presentation will discuss the combining of results from multiple NAMs for predicting the teratogenic properties and potency of this series of structurally related chemicals and how this information can be used to establish a framework of testing for regulatory applications. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 681002

Evaluation of an alternative in vitro test battery for detecting reproductive toxicants

The application of alternative methods in developmental and reproductive toxicology is challenging in view of the complexity of mechanisms involved. A battery of complementary test systems may provide a better prediction of developmental and reproductive toxicity than single assays. We tested twelve compounds with varying mechanisms of toxic action in an assay battery including 24 CALUX transcriptional activation assays, mouse cardiac embryonic stem cell test, ReProGlo assay, zebrafish embryotoxicity assay, and two CYP17 and two CYP19 activity assays. The battery correctly detected 11/12 compounds tested, with one false negative occurring, which could be explained by the absence of the specific mechanism of action of this compound in the battery. Toxicokinetic modeling revealed that toxic concentrations were in the range expected from in vivo reproductive toxicity data. This study illustrates added value of combining assays that contain complementary biological processes and mechanisms, increasing predictive value of the battery over individual assays. © 2013