The aim of this study is to define chemical categories that can be applied to regulatory read-across assessments for repeated-dose toxicity, by classifying toxic substances based on their structures and mechanism of actions (MoAs). Hemolytic anemia, which often appears primarily, was examined as an example. An integrated database was constructed by collecting publicly available datasets on repeated-dose toxicity, in which 423 out of a total of 1518 chemicals were identified as capable of inducing hemolytic anemia. Subsequently, by grouping these chemicals based on their chemical structures and plausible MoAs on hemolytic substances, we identified the following categories: (i) anilines, (ii) nitrobenzenes, (iii) nitroanilines, (iv) dinitroanilines, (v) ethylene glycol alkyl ethers, (vi) hydroquinones, (vii) oximes, and (viii) hydrazines. In these categories, the toxicant and the measurable key events leading to hematotoxicity were identified, thereby allowing us to justify the categories and to discriminate the category substances. Moreover, toxicokinetics seems to critically affect the hemolytic levels of the category substances. Overall, the categories were validated through a comprehensive analysis of the collected information, while the utility was demonstrated by conducting a case study on the selected category. Further endeavors with this approach would attain categories for other organ toxicity endpoints.

Predictive toxicology plays an integral role in determining the toxicological profiles of chemicals for safety assessment. Vitamin D is an essential vitamin for the regulation of calcium absorption and homeostasis, as well as the treatment and prevention of several diseases such as rickets and osteomalacia. According to European Medicines Agency (EMA) Guideline on setting health-based exposure limits for use in risk identification in the manufacturing of different medicinal products in shared facilities, permitted daily exposure (PDE) calculation for active pharmaceutical ingredients (APIs) should be done by the medicinal product producers. PDE calculation is mainly based on critical toxicological endpoints such as repeated dose toxicity, genotoxicity, carcinogenicity, developmental and reproductive toxicity, and hypersensitivity potential. During this procedure, critical toxicological endpoints data of an API can be used to predict the PDE of another API that has a similar chemical structure. In the present paper, human toxicological endpoints of vitamin D2, D3, and their metabolites were evaluated and afterwards the data gaps in the toxicological endpoints were filled by forming a category. The read-across was justified by the structural and metabolic similarities. Molecular similarity and mechanistic relevance were found to be substantial, resulting in low uncertainty. The untested vitamin D analogs within the category can be read across with confidence to complete the data gaps related to the human health endpoints.

Read-across is a well-established data gap-filling technique applied for regulatory purposes. In US Environmental Protection Agency\'s New Chemicals Program under TSCA, read-across has been used extensively for decades, however the extent of application and acceptance of read-across among U.S. federal agencies is less clear. In an effort to build read-across capacity, raise awareness of the state of the science, and work towards a harmonization of read-across approaches across U.S. agencies, a new read-across workgroup was established under the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM). This is one of several ad hoc groups ICCVAM has convened to implement the ICCVAM Strategic Roadmap. In this article, we outline the charge and scope of the workgroup and summarize the current applications, tools used, and needs of the agencies represented on the workgroup for read-across. Of the agencies surveyed, the Environmental Protection Agency had the greatest experience in using read-across whereas other agencies indicated that they would benefit from gaining a perspective of the landscape of the tools and available guidance. Two practical case studies are also described to illustrate how the read-across approaches applied by two agencies vary on account of decision context.

Read-across is a popular data gap filling technique used within analogue and category approaches for regulatory purposes. In recent years there have been many efforts focused on the challenges involved in read-across development, its scientific justification and documentation. Tools have also been developed to facilitate read-across development and application. Here, we describe a number of publicly available read-across tools in the context of the category/analogue workflow and review their respective capabilities, strengths and weaknesses. No single tool addresses all aspects of the workflow. We highlight how the different tools complement each other and some of the opportunities for their further development to address the continued evolution of read-across.

Categories and read-across are essential tools for supplying information for assessments of endpoints without data while minimizing animal testing. This study is based on the guidance of ECHA in its Read-Across Framework (RAAF). A category of C1 - C8 alkyl methacrylate esters (methyl, ethyl, n-butyl, iso-butyl and 2-ethylhexyl) was constructed to fill in missing information for human health endpoints using read-across as a permitted adaptation under EU REACH. The esters form a series with common functional groups, small incremental changes of electrophilicity by molecular weight, and rapid hydrolysis by ester cleavage. Read-across is justified by two common specific modes of action, direct electrophilic reaction of the parent compounds and the potential inherent toxicities of the common metabolites methacrylic acid and the corresponding alcohols. The toxicological profile is very similar for all category members and not driven by the alcohol metabolites. Data gaps can be filled in with high confidence based on the number of studies available, the effects therein observed and the toxicological profiles of the hydrolysis products. The guidance provided by the RAAF enabled data gaps to be filled in a robust manner.

Substantial benefits are realized through the use of read-across and in silico techniques to fill data gaps for structurally similar substances. Considerable experience in applying these techniques was gained under two voluntary high production volume (HPV) chemical programs - the International Council of Chemical Associations\' (ICCA) Cooperative Chemicals Assessment Programme (with the cooperation of the Organization of Economic Cooperation and Development) and the U.S. Environmental Protection Agency\'s HPV Challenge Program. These programs led to the compilation and public availability of baseline sets of health and environmental effects data for thousands of chemicals. The American Cleaning Institute\'s (ACI) contribution to these national and global efforts included the compilation of these datasets for 261 substances. Chemicals that have structural similarities are likely to have similar environmental fate, physical-chemical and toxicological properties, which was confirmed by examining available data from across the range of substances within categories of structurally similar HPV chemicals. These similarities allowed the utilization of read-across, trend analysis techniques and qualitative structure activity relationship ((Q)SAR) tools to fill data gaps. This paper presents the first quantification of actual benefits resulting from avoided testing through the use of read-across and in silico tools. Specifically, in the evaluation of these 261 noted substances, the use of 100,000-150,000 test animals and the expenditures of $50,000,000 to $70,000,000 (US) were avoided.

We propose a three-step strategy that uses structural and physicochemical properties of chemicals to predict their 72 h algal growth inhibition toxicities against Pseudokirchneriella subcapitata. In Step 1, using a log D-based criterion and structural alerts, we produced an interspecies QSAR between algal and acute daphnid toxicities for initial screening of chemicals. In Step 2, we categorized chemicals according to the Verhaar scheme for aquatic toxicity, and we developed QSARs for toxicities of Class 1 (non-polar narcotic) and Class 2 (polar narcotic) chemicals by means of simple regression with a hydrophobicity descriptor and multiple regression with a hydrophobicity descriptor and a quantum chemical descriptor. Using the algal toxicities of the Class 1 chemicals, we proposed a baseline QSAR for calculating their excess toxicities. In Step 3, we used structural profiles to predict toxicity either quantitatively or qualitatively and to assign chemicals to the following categories: Pesticide, Reactive, Toxic, Toxic low and Uncategorized. Although this three-step strategy cannot be used to estimate the algal toxicities of all chemicals, it is useful for chemicals within its domain. The strategy is also applicable as a component of Integrated Approaches to Testing and Assessment.

The German Committee on Indoor Guide Values issues indoor air guide values to protect public health. For health evaluation of glycol ethers and glycol esters in air, the entire group of substances with data for 47 chemicals was analyzed in order to gain a consistent assessment. For some glycol ethers reproductive and hematological effects are of central interest, whereas for others effects on liver and kidneys are crucial. Moreover, some glycol ethers have also been shown to cause irritation of the respiratory tract. For 14 chemicals, suitable inhalation studies were available for deriving specific guide values, or analogies to closely related substances could be drawn. For these chemicals individual indoor air guide values were derived, the respective guide value I ranging from 0.02 to 2mg/m(3). Guide values were derived according to the procedures issued by the Committee, considering the exposure duration in indoor air compared to animal studies or the situation at workplaces, the duration of the respective study, species differences, and interindividual variability including special sensitivity of children. For glycol ethers with insufficient data default guide values II and I of 0.05 and 0.005ppm, respectively, were recommended based on statistical analyses of the available data on all glycol ethers and on evaluation of single studies. For evaluation of combined effects additivity is assumed.

The OECD QSAR Toolbox is a software application intended to be used by governments, the chemical industry and other stakeholders in filling gaps in (eco)toxicity data needed for assessing the hazards of chemicals. The development and release of the Toolbox is a cornerstone in the computerization of hazard assessment, providing an \'all inclusive\' tool for the application of category approaches, such as read-across and trend analysis, in a single software application, free of charge. The Toolbox incorporates theoretical knowledge, experimental data and computational tools from various sources into a logical workflow. The main steps of this workflow are substance identification, identification of relevant structural characteristics and potential toxic mechanisms of interaction (i.e. profiling), identification of other chemicals that have the same structural characteristics and/or mechanism (i.e. building a category), data collection for the chemicals in the category and use of the existing experimental data to fill the data gap(s). The description of the Toolbox workflow and its main functionalities is the scope of the present article.

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