The High Production Volume Chemical Challenge Program: The Rodent LD50 and its Possible Replacement

Rosenkranz, Herbert S.; Cunningham, Albert R.

doi:10.1177/026119290002800208

Cited by 5 publications

(5 citation statements)

References 36 publications

(37 reference statements)

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“…This indicates that systemic toxicity may derive, in part, from cell toxicity. This is also in accord with the findings that a battery of cell toxicity assays might serve as a substitute for the rat LD50 test (22,24,60).…”

Section: Resultssupporting

confidence: 88%

“…As reported previously (60), there is a significant association between acute toxicity in rats and binding to the Ah receptor (Tables 3 and 4: Analysis 16). This suggests that binding to that receptor is a mechanism that can cause systemic toxicity and death.…”

Section: Resultssupporting

confidence: 78%

“…Of these, the rat acute toxicity test is controversial and even in dispute, yet various alternatives to the classic LD50 assay are used in the regulatory arena for categorising the toxicity of chemicals (1,61). It has been shown previously that there is potential for replacing it with a combination of in vitro cellular and subcellular assays (22,24,60).…”

Section: Resultsmentioning

confidence: 99%

“…It should not be inferred in that context that they are experimental observations.) The chemical diversity approach has been validated on a number of occasions (25, 26), and has been used to develop mechanistic hypotheses (57)(58)(59)(60). Moreover, with respect to the approach, it is noteworthy that it was found that, in fact, there was a correspondence between projected and experimentally determined prevalences for mutagens (26) and for "genotoxic" rodent carcinogens (25) in previous studies.…”

Section: The Chemical Diversity Approachmentioning

confidence: 99%

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Lack of Predictivity of the Rat Lethality (LD50) Test for Ecological and Human Health Effects

Rosenkranz

Cunningham

2005

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The relationship between acute toxicity in rats (LD50 values) and indicators of potential health hazards in humans was investigated, based on a chemical population-based paradigm (i.e. the “chemical diversity approach”). These structure–activity relationship-based analyses indicate that high toxicity in rats (i.e. a low LD50 value) is not a good predictor of health effects in humans. In fact, it was found that high acute toxicity to minnows, as well as toxicity to cultured cells, showed significantly greater associations with the potential for health effects than rat LD50 values.

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Section: Resultssupporting

confidence: 88%

Section: Resultssupporting

confidence: 78%

Section: Resultsmentioning

confidence: 99%

Section: The Chemical Diversity Approachmentioning

confidence: 99%

See 2 more Smart Citations

Lack of Predictivity of the Rat Lethality (LD50) Test for Ecological and Human Health Effects

Rosenkranz

Cunningham

2005

Altern Lab Anim

Self Cite

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“…A significantly greater observed than expected prevalence indicates a similarity in mechanism among the toxicological effects that are being studied, while a significantly lower observed than expected prevalence suggests a possible antagonism between the phenomena under investigation. The CDA has been validated on a number of occasions , and has also been used to develop mechanistic hypotheses − .…”

Section: Methodsmentioning

confidence: 99%

Structure−Activity Relationship Analysis of Rat Mammary Carcinogens

Cunningham

Moss

Iype

et al. 2008

Chem. Res. Toxicol.

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Structure-activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe here the application of the cat-SAR (categorical-SAR) program to two learning sets of rat mammary carcinogens. One set of developed models was based on a comparison of rat mammary carcinogens to rat noncarcinogens (MC-NC), and the second set compared rat mammary carcinogens to rat nonmammary carcinogens (MC-NMC). On the basis of a leave-one-out validation, the best rat MC-NC model achieved a concordance between experimental and predicted values of 84%, a sensitivity of 79%, and a specificity of 89%. Likewise, the best rat MC-MNC model achieved a concordance of 78%, a sensitivity of 82%, and a specificity of 74%. The MC-NMC model was based on a learning set that contained carcinogens in both the active (i.e., mammary carcinogens) and the inactive (i.e., carcinogens to sites other than the mammary gland) categories and was able to distinguish between these different types of carcinogens (i.e., tissue specific), not simply between carcinogens and noncarcinogens. On the basis of a structural comparison between this model and one for Salmonella mutagens, there was, as expected, a significant relationship between the two phenomena since a high proportion of breast carcinogens are Salmonella mutagens. However, when analyzing the specific structural features derived from the MC-NC learning set, a dichotomy was observed between fragments associated with mammary carcinogenesis and mutagenicity and others that were associated with estrogenic activity. Overall, these findings suggest that the MC-NC and MC-NMC models are able to identify structural attributes that may in part address the question of "why do some carcinogens cause breast cancer", which is a different question than "why do some chemicals cause cancer".

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