Publications by authors named "E Zvinavashe"

Read-across has generated much attention since it may be used as an alternative approach for addressing the information requirements under regulatory programmes, notably the EU's REACH regulation. Read-across approaches are conceptually accepted by ECHA and Member State Authorities (MS) but difficulties remain in applying them consistently in practice. Technical guidance is available and there are a plethora of models and tools that can assist in the development of categories and read-across, but guidance on how to practically apply categorisation approaches is still missing.

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The description of quantitative structure-activity relationship (QSAR) models has been a topic for scientific research for more than 40 years and a topic within the regulatory framework for more than 20 years. At present, efforts on QSAR development are increasing because of their promise for supporting reduction, refinement, and/or replacement of animal toxicity experiments. However, their acceptance in risk assessment seems to require a more standardized and scientific underpinning of QSAR technology to avoid possible pitfalls.

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Article Synopsis
  • * The study created QSAR models using both existing literature and new experimental data, focusing on chemical properties such as the octanol/water partition coefficient and molecular orbital energies.
  • * Results suggest that toxicity data from Daphnia magna can successfully predict toxicity in fish, allowing researchers to estimate the toxicity of various compounds without extensive animal testing—83 candidate chemicals were identified from a larger database for further evaluation using these QSAR models.
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The new EU legislation for managing chemicals called REACH aims to fill in gaps in toxicity information that exist for the chemicals listed on the European Inventory of Existing Chemical Substances (EINECS). REACH advocates the use of alternatives to animal experimentation including, amongst others, (quantitative) structure-activity relationship models [(Q)SARs] to help fill in the toxicity data gaps. The aim of the present study was to provide a science-based estimate of the number of EINECS compounds that can be covered by (Q)SAR models for acute toxicity.

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Quantitative structure-activity relationship (QSAR) models are expected to play a crucial role in reducing the number of animals to be used for toxicity testing resulting from the adoption of the new European Union chemical control system called Registration, Evaluation, and Authorization of Chemicals (REACH). The objective of the present study was to generate in vitro acute toxicity data that could be used to develop a QSAR model to describe acute in vivo toxicity of chlorinated alkanes. Cytotoxicity of a series of chlorinated alkanes to Chinese hamster ovary (CHO) cells was observed at concentrations similar to those that have been shown previously to be toxic to fish.

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