Integrating (Q)SAR models, expert systems and read-across approaches for the prediction of developmental toxicity

Hewitt, Mark; Ellison, Claire M.; Enoch, Steven J.; Madden, Judith C.; Cronin, Mark T.D.

doi:10.1016/j.reprotox.2009.12.003

Cited by 60 publications

(36 citation statements)

References 19 publications

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“…The limited use of (Q)SAR reflects the lack of predictive models as stated recently (Hewitt et al, 2010): "This study has shown that current modelling methods available for developmental toxicity are still in their infancy. Each approach considered in this study is limited by available toxicity data in the public arena and by mechanistic understanding."…”

Section: In Vitro Opportunitiesmentioning

confidence: 99%

How are reproductive toxicity and developmental toxicity addressed in REACH dossiers?

Rovida

Longo²,

Rabbit³

2011

ALTEX

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Section: In Vitro Opportunitiesmentioning

confidence: 99%

How are reproductive toxicity and developmental toxicity addressed in REACH dossiers?

Rovida

Longo²,

Rabbit³

2011

ALTEX

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“…This method is widely used in in silico modelling to improve the overall predictability of models. [101]. However, the combining of models together make the method less transparent for the specific endpoint and difficult to explain the underlying mechanisms.…”

Section: In Silico Models For Intrinsic Hepatotoxicity In Humansmentioning

confidence: 99%

In silicomodels for drug-induced liver injury – current status

Przybylak

Cronin

2012

Expert Opinion on Drug Metabolism & Toxicology

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Most of the predictive methods discussed in this review are based on the structural properties of chemicals and do not take into account genetic and environmental factors; therefore, their predictions are still uncertain. To improve the predictability of in silico models for DILI, it is essential to better understand its mechanisms as well as to develop sensitive toxicogenomics biomarkers, which show relatively good differentiation between hepatotoxins and non-hepatotoxins.

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“…Metabolomic analysis of human WA09 embryonic stem cells identified teratogenic substances, including thalidomide, with 88% predictivity (Kleinstreuer et al 2011). Likewise the combination of read-across with several quantitative structure–activity relationship (QSAR) models allowed Hewitt et al (2010) to reach 89% predictivity for developmental toxicity. Even for the notorious non-genotoxic carcinogens, toxicogenomic approaches reach a predictivity of up to 80%, which is superior to the classic rodent–cancer bioassay (Fielden et al 2011; Liu et al 2011; Low et al 2011).…”

Section: Challenging High Expectationsmentioning

confidence: 99%

Wind of Change Challenges Toxicological Regulators

Tralau

Riebeling

Pirow

et al. 2012

Environ Health Perspect

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Background: In biomedical research, the past two decades have seen the advent of in vitro model systems based on stem cells, humanized cell lines, and engineered organotypic tissues, as well as numerous cellular assays based on primarily established tumor-derived cell lines and their genetically modified derivatives.Objective: There are high hopes that these systems might replace the need for animal testing in regulatory toxicology. However, despite increasing pressure in recent years to reduce animal testing, regulators are still reluctant to adopt in vitro approaches on a large scale. It thus seems appropriate to consider how we could realistically perform regulatory toxicity testing using in vitro assays only.Discussion and Conclusion: Here, we suggest an in vitro–only approach for regulatory testing that will benefit consumers, industry, and regulators alike.

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Integrating (Q)SAR models, expert systems and read-across approaches for the prediction of developmental toxicity

Cited by 60 publications

References 19 publications

How are reproductive toxicity and developmental toxicity addressed in REACH dossiers?

How are reproductive toxicity and developmental toxicity addressed in REACH dossiers?

In silicomodels for drug-induced liver injury – current status

Wind of Change Challenges Toxicological Regulators

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