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Animal Testing Alternatives

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An in silico expert system for the identification of eye irritants.

SAR and QSAR in environmental research
This report describes development of an in silico, expert rule-based method for the classification of chemicals into irritants or non-irritants to eye, as defined by the Draize test. This method was developed to screen data-poor cosmetic ingredient c...

Evaluation of combinations of in vitro sensitization test descriptors for the artificial neural network-based risk assessment model of skin sensitization.

Journal of applied toxicology : JAT
The skin sensitization potential of chemicals has been determined with the use of the murine local lymph node assay (LLNA). However, in recent years public concern about animal welfare has led to a requirement for non-animal risk assessment systems f...

Estimation of the chemical-induced eye injury using a Weight-of-Evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part II: corrosion potential.

Regulatory toxicology and pharmacology : RTP
This is part II of an in silico investigation of chemical-induced eye injury that was conducted at FDA's CFSAN. Serious eye damage caused by chemical (eye corrosion) is assessed using the rabbit Draize test, and this endpoint is an essential part of ...

Estimation of the chemical-induced eye injury using a weight-of-evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part I: irritation potential.

Regulatory toxicology and pharmacology : RTP
Evaluation of potential chemical-induced eye injury through irritation and corrosion is required to ensure occupational and consumer safety for industrial, household and cosmetic ingredient chemicals. The historical method for evaluating eye irritant...

The potential of AOP networks for reproductive and developmental toxicity assay development.

Reproductive toxicology (Elmsford, N.Y.)
Historically, the prediction of reproductive and developmental toxicity has largely relied on the use of animals. The adverse outcome pathway (AOP) framework forms a basis for the development of new non-animal test methods. It also provides biologica...

Probabilistic hazard assessment for skin sensitization potency by dose-response modeling using feature elimination instead of quantitative structure-activity relationships.

Journal of applied toxicology : JAT
Supervised learning methods promise to improve integrated testing strategies (ITS), but must be adjusted to handle high dimensionality and dose-response data. ITS approaches are currently fueled by the increasing mechanistic understanding of adverse ...

Prediction of skin sensitization potency using machine learning approaches.

Journal of applied toxicology : JAT
The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers witho...

Toward a systematic exploration of nano-bio interactions.

Toxicology and applied pharmacology
Many studies of nanomaterials make non-systematic alterations of nanoparticle physicochemical properties. Given the immense size of the property space for nanomaterials, such approaches are not very useful in elucidating fundamental relationships bet...

Design and validation of an ontology-driven animal-free testing strategy for developmental neurotoxicity testing.

Toxicology and applied pharmacology
Developmental neurotoxicity entails one of the most complex areas in toxicology. Animal studies provide only limited information as to human relevance. A multitude of alternative models have been developed over the years, providing insights into mech...