Performance of the Pollen Tube Growth Test in the COLIPA Validation Study on Alternatives to the Rabbit Eye Irritation Test

1999 ◽  
Vol 13 (2) ◽  
pp. 335-342 ◽  
Author(s):  
U. Kristen ◽  
K. Jung ◽  
W. Pape ◽  
U. Pfannenbecker ◽  
A. Rensch ◽  
...  
2006 ◽  
Vol 17 (1) ◽  
pp. 58-62 ◽  
Author(s):  
Udo Kristen ◽  
Reinhard E. Friedrich

This study investigated whether mouthwash dilutions, recommended by the manufacturers, may contribute to oral mucosa irritation. Twenty frequently used mouthwash brands were examined by the pollen tube growth test, an alternative in vitro method for assessment of the irritating potential of ingredients of cosmetic formulations. The test is based on the photometric quantification of pollen tube growth inhibition. This parameter is expressed by IC50 values that characterize the cytotoxic potential of a product. The IC50s clearly revealed that none of the tested mouthwashes should cause acute irritation if used in the recommended dilution. However, at least 4 of the mouthwashes evaluated in this study could probably irritate the oral mucosa acutely if used undiluted (original concentration).


2003 ◽  
Vol 31 (1) ◽  
pp. 31-46 ◽  
Author(s):  
Ferdinand Moldenhauer

The international validation study on alternative methods to replace the Draize rabbit eye irritation test, funded by the European Commission (EC) and the British Home Office (HO), took place during 1992–1994, and the results were published in 1995. The results of this EC/HO study are analysed by employing discriminant analysis, taking into account the classification of the in vivo data into eye irritation classes A (risk of serious damage to eyes), B (irritating to eyes) and NI (non-irritant). A data set for 59 test items was analysed, together with three subsets: surfactants, water-soluble chemicals, and water-insoluble chemicals. The new statistical methods of feature selection and estimation of the discriminant function's classification error were used. Normal distributed random numbers were added to the mean values of each in vitro endpoint, depending on the observed standard deviations. Thereafter, the reclassification error of the random observations was estimated by applying the fixed function of the mean values. Moreover, the leaving-one-out cross-classification method was applied to this random data set. Subsequently, random data were generated r times (for example, r = 1000) for a feature combination. Eighteen features were investigated in nine in vitro test systems to predict the effects of a chemical in the rabbit eye. 72.5% of the chemicals in the undivided sample were correctly classified when applying the in vitro endpoints lgNRU of the neutral red uptake test and lgBCOPo5 of the bovine opacity and permeability test. The accuracy increased to 80.9% when six in vitro features were used, and the sample was subdivided. The subset of surfactants was correctly classified in more than 90% of cases, which is an excellent performance.


1995 ◽  
pp. 189-198 ◽  
Author(s):  
Udo Kristen ◽  
Rolf Kappler

1997 ◽  
Vol 11 (1-2) ◽  
pp. 141-179 ◽  
Author(s):  
P.G. Brantom ◽  
L.H. Bruner ◽  
M. Chamberlain ◽  
O. De Silva ◽  
J. Dupuis ◽  
...  

1989 ◽  
Vol 58 (3) ◽  
pp. 515-521 ◽  
Author(s):  
Goro OKAMOTO ◽  
Ikuo SHIBUYA ◽  
Miwa FURUICHI ◽  
Kazuo SHIMAMURA

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