Limits...
Retrospective analysis of the Draize test for serious eye damage/eye irritation: importance of understanding the in vivo endpoints under UN GHS/EU CLP for the development and evaluation of in vitro test methods.

Adriaens E, Barroso J, Eskes C, Hoffmann S, McNamee P, Alépée N, Bessou-Touya S, De Smedt A, De Wever B, Pfannenbecker U, Tailhardat M, Zuang V - Arch. Toxicol. (2013)

Bottom Line: Iritis was found to rarely drive the classification (<4 % of both Cat 1 and Cat 2 chemicals).Moreover, our analyses of the classification drivers suggest a critical revision of the UN GHS/EU CLP decision criteria for the classification of chemicals based on Draize eye test data, in particular Cat 1 based only on persistence of conjunctiva effects or corneal opacity scores of 4.In order to successfully replace the regulatory in vivo Draize eye test, it will be important to recognise these uncertainties and to have in vitro tools to address the most important in vivo endpoints identified in this paper.

View Article: PubMed Central - PubMed

Affiliation: Adriaens Consulting BVBA, Bellem, Belgium.

ABSTRACT
For more than two decades, scientists have been trying to replace the regulatory in vivo Draize eye test by in vitro methods, but so far only partial replacement has been achieved. In order to better understand the reasons for this, historical in vivo rabbit data were analysed in detail and resampled with the purpose of (1) revealing which of the in vivo endpoints are most important in driving United Nations Globally Harmonized System/European Union Regulation on Classification, Labelling and Packaging (UN GHS/EU CLP) classification for serious eye damage/eye irritation and (2) evaluating the method's within-test variability for proposing acceptable and justifiable target values of sensitivity and specificity for alternative methods and their combinations in testing strategies. Among the Cat 1 chemicals evaluated, 36-65 % (depending on the database) were classified based only on persistence of effects, with the remaining being classified mostly based on severe corneal effects. Iritis was found to rarely drive the classification (<4 % of both Cat 1 and Cat 2 chemicals). The two most important endpoints driving Cat 2 classification are conjunctiva redness (75-81 %) and corneal opacity (54-75 %). The resampling analyses demonstrated an overall probability of at least 11 % that chemicals classified as Cat 1 by the Draize eye test could be equally identified as Cat 2 and of about 12 % for Cat 2 chemicals to be equally identified as No Cat. On the other hand, the over-classification error for No Cat and Cat 2 was negligible (<1 %), which strongly suggests a high over-predictive power of the Draize eye test. Moreover, our analyses of the classification drivers suggest a critical revision of the UN GHS/EU CLP decision criteria for the classification of chemicals based on Draize eye test data, in particular Cat 1 based only on persistence of conjunctiva effects or corneal opacity scores of 4. In order to successfully replace the regulatory in vivo Draize eye test, it will be important to recognise these uncertainties and to have in vitro tools to address the most important in vivo endpoints identified in this paper.

Show MeSH

Related in: MedlinePlus

Boxplots presenting the distribution of individual animal mean CO (a) and mean IR (b) scores calculated over the reading times at 24, 48, and 72 h by classification driver. NCD: European New Chemicals Database, RCD: Reference Chemicals Databases, No Cat: not classified, Cat 2—1 ≤ COMaj < 3: classified based on majority of mean CO scores equal to or greater than 1 but less than 3, Cat 2—CRMaj/CCMaj ≥ 2 (and COMaj < 1): classified based on majority of mean CR and/or CC scores equal to or greater than 2 but with majority of mean CO scores less than 1, Cat 2—1 ≤ IRMaj ≤ 1.5 only: classified based on majority of mean IR scores equal to or greater than 1 but less than or equal to 1.5, Cat 1—COMaj ≥ 3: classified based on majority of mean CO scores equal to or greater than 3, Cat 1—CO = 4 (and COMaj < 3): classified based on CO = 4 but with majority of mean CO scores less than 3, Cat 1—IRMaj > 1.5 only: classified based on majority of mean IR scores greater than 1.5, Cat 1—Persistence only: classified based on persistence only. The whiskers correspond with the smallest and largest observation that fall within a distance of 1.5 times the length of the box (Interquartile Range, IQR) from the lower (bottom side of the box) and upper quartile (upper side of the box), respectively
© Copyright Policy - OpenAccess
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3927066&req=5

Fig1: Boxplots presenting the distribution of individual animal mean CO (a) and mean IR (b) scores calculated over the reading times at 24, 48, and 72 h by classification driver. NCD: European New Chemicals Database, RCD: Reference Chemicals Databases, No Cat: not classified, Cat 2—1 ≤ COMaj < 3: classified based on majority of mean CO scores equal to or greater than 1 but less than 3, Cat 2—CRMaj/CCMaj ≥ 2 (and COMaj < 1): classified based on majority of mean CR and/or CC scores equal to or greater than 2 but with majority of mean CO scores less than 1, Cat 2—1 ≤ IRMaj ≤ 1.5 only: classified based on majority of mean IR scores equal to or greater than 1 but less than or equal to 1.5, Cat 1—COMaj ≥ 3: classified based on majority of mean CO scores equal to or greater than 3, Cat 1—CO = 4 (and COMaj < 3): classified based on CO = 4 but with majority of mean CO scores less than 3, Cat 1—IRMaj > 1.5 only: classified based on majority of mean IR scores greater than 1.5, Cat 1—Persistence only: classified based on persistence only. The whiskers correspond with the smallest and largest observation that fall within a distance of 1.5 times the length of the box (Interquartile Range, IQR) from the lower (bottom side of the box) and upper quartile (upper side of the box), respectively

Mentions: The within-test variability of the mean tissue scores was further evaluated by grouping the data of the different studies available in the RCD and NCD according to the UN GHS/EU CLP classification of the tested chemicals and their classification driver as described above (De Wever et al. 2012; Barroso et al. 2013). These data are presented in boxplots that illustrate the distribution of the animals mean CO score (Fig. 1a), mean IR score (Fig. 1b), mean CR score (Fig. 2a), and mean CC score (Fig. 2b), per classification driver.Fig. 1


Retrospective analysis of the Draize test for serious eye damage/eye irritation: importance of understanding the in vivo endpoints under UN GHS/EU CLP for the development and evaluation of in vitro test methods.

Adriaens E, Barroso J, Eskes C, Hoffmann S, McNamee P, Alépée N, Bessou-Touya S, De Smedt A, De Wever B, Pfannenbecker U, Tailhardat M, Zuang V - Arch. Toxicol. (2013)

Boxplots presenting the distribution of individual animal mean CO (a) and mean IR (b) scores calculated over the reading times at 24, 48, and 72 h by classification driver. NCD: European New Chemicals Database, RCD: Reference Chemicals Databases, No Cat: not classified, Cat 2—1 ≤ COMaj < 3: classified based on majority of mean CO scores equal to or greater than 1 but less than 3, Cat 2—CRMaj/CCMaj ≥ 2 (and COMaj < 1): classified based on majority of mean CR and/or CC scores equal to or greater than 2 but with majority of mean CO scores less than 1, Cat 2—1 ≤ IRMaj ≤ 1.5 only: classified based on majority of mean IR scores equal to or greater than 1 but less than or equal to 1.5, Cat 1—COMaj ≥ 3: classified based on majority of mean CO scores equal to or greater than 3, Cat 1—CO = 4 (and COMaj < 3): classified based on CO = 4 but with majority of mean CO scores less than 3, Cat 1—IRMaj > 1.5 only: classified based on majority of mean IR scores greater than 1.5, Cat 1—Persistence only: classified based on persistence only. The whiskers correspond with the smallest and largest observation that fall within a distance of 1.5 times the length of the box (Interquartile Range, IQR) from the lower (bottom side of the box) and upper quartile (upper side of the box), respectively
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3927066&req=5

Fig1: Boxplots presenting the distribution of individual animal mean CO (a) and mean IR (b) scores calculated over the reading times at 24, 48, and 72 h by classification driver. NCD: European New Chemicals Database, RCD: Reference Chemicals Databases, No Cat: not classified, Cat 2—1 ≤ COMaj < 3: classified based on majority of mean CO scores equal to or greater than 1 but less than 3, Cat 2—CRMaj/CCMaj ≥ 2 (and COMaj < 1): classified based on majority of mean CR and/or CC scores equal to or greater than 2 but with majority of mean CO scores less than 1, Cat 2—1 ≤ IRMaj ≤ 1.5 only: classified based on majority of mean IR scores equal to or greater than 1 but less than or equal to 1.5, Cat 1—COMaj ≥ 3: classified based on majority of mean CO scores equal to or greater than 3, Cat 1—CO = 4 (and COMaj < 3): classified based on CO = 4 but with majority of mean CO scores less than 3, Cat 1—IRMaj > 1.5 only: classified based on majority of mean IR scores greater than 1.5, Cat 1—Persistence only: classified based on persistence only. The whiskers correspond with the smallest and largest observation that fall within a distance of 1.5 times the length of the box (Interquartile Range, IQR) from the lower (bottom side of the box) and upper quartile (upper side of the box), respectively
Mentions: The within-test variability of the mean tissue scores was further evaluated by grouping the data of the different studies available in the RCD and NCD according to the UN GHS/EU CLP classification of the tested chemicals and their classification driver as described above (De Wever et al. 2012; Barroso et al. 2013). These data are presented in boxplots that illustrate the distribution of the animals mean CO score (Fig. 1a), mean IR score (Fig. 1b), mean CR score (Fig. 2a), and mean CC score (Fig. 2b), per classification driver.Fig. 1

Bottom Line: Iritis was found to rarely drive the classification (<4 % of both Cat 1 and Cat 2 chemicals).Moreover, our analyses of the classification drivers suggest a critical revision of the UN GHS/EU CLP decision criteria for the classification of chemicals based on Draize eye test data, in particular Cat 1 based only on persistence of conjunctiva effects or corneal opacity scores of 4.In order to successfully replace the regulatory in vivo Draize eye test, it will be important to recognise these uncertainties and to have in vitro tools to address the most important in vivo endpoints identified in this paper.

View Article: PubMed Central - PubMed

Affiliation: Adriaens Consulting BVBA, Bellem, Belgium.

ABSTRACT
For more than two decades, scientists have been trying to replace the regulatory in vivo Draize eye test by in vitro methods, but so far only partial replacement has been achieved. In order to better understand the reasons for this, historical in vivo rabbit data were analysed in detail and resampled with the purpose of (1) revealing which of the in vivo endpoints are most important in driving United Nations Globally Harmonized System/European Union Regulation on Classification, Labelling and Packaging (UN GHS/EU CLP) classification for serious eye damage/eye irritation and (2) evaluating the method's within-test variability for proposing acceptable and justifiable target values of sensitivity and specificity for alternative methods and their combinations in testing strategies. Among the Cat 1 chemicals evaluated, 36-65 % (depending on the database) were classified based only on persistence of effects, with the remaining being classified mostly based on severe corneal effects. Iritis was found to rarely drive the classification (<4 % of both Cat 1 and Cat 2 chemicals). The two most important endpoints driving Cat 2 classification are conjunctiva redness (75-81 %) and corneal opacity (54-75 %). The resampling analyses demonstrated an overall probability of at least 11 % that chemicals classified as Cat 1 by the Draize eye test could be equally identified as Cat 2 and of about 12 % for Cat 2 chemicals to be equally identified as No Cat. On the other hand, the over-classification error for No Cat and Cat 2 was negligible (<1 %), which strongly suggests a high over-predictive power of the Draize eye test. Moreover, our analyses of the classification drivers suggest a critical revision of the UN GHS/EU CLP decision criteria for the classification of chemicals based on Draize eye test data, in particular Cat 1 based only on persistence of conjunctiva effects or corneal opacity scores of 4. In order to successfully replace the regulatory in vivo Draize eye test, it will be important to recognise these uncertainties and to have in vitro tools to address the most important in vivo endpoints identified in this paper.

Show MeSH
Related in: MedlinePlus