Toxic. in Vitro Vol. 9,No. 6,pp. 871-929, 1995 

### 08&V-2333(%)00092-5 Copyright 0 1995Elsevier ScienceLtd Printed inGreat Britain. Allrights reserved

0887-2333/95 $9.50 + 0.00



# The EC/HO International Validation Study on Alternatives to the Draize Eye

Irritation Test

M. 

### BALLS*, P. A. BOTHAM?, L. H. BRUNERS and H. SPIELMANN *ECVAM, JRC Environment Institute, 21020Ispra (VA),Italy, tCentra1 Toxicology Laboratory, Zeneca, Macclesfield, Cheshire SKlO4TJ, UK, IProcter &Gamble Health and Beauty Care (Europe), Egham,

Surrey TW209NW, UK and GZEBET,BgVV, 12277Berlin, Germany
Abstract-This isthe final report ofthe Management Team for a European Commission/British Home Office (EC/HO) validation study on alternatives to the Draize eye irritation test. The principal goal of thestudy wastoestablish whether oneormore ofninenon-animal testscould beusedtoreplacetheDraize testfor allseverelyirritating materials (orthose belonging to specificclasses)ortheanimal testcompletely forchemicals with orwithout regard tochemical class. Sixtychemicals wereindependently selected, coded and supplied, then the data obtained in 37laboratories were analysed independently. The results of comparisons between 27 alternative test index scores and the Modified Maximum Average Scores (MMASs) obtained in the Draize eye test were compared. Tables ofresults showing Pearson’s product moment correlation coefficients and Spearman’s rank coefficients for each laboratory are provided, and correlation matrices ofalternative test index scores among the different groups oflaboratories are shown for each endpoint. Scatter-plots are provided, in which the alternative test scores obtained by the lead laboratories for the nine tests are plotted against the MMAS for the full set of chemicals and 12 surfactants. Itisconcluded that, with thepossible exception ofpredicting theirritancy ofsurfactants, none ofthe nine tests met any ofthe four performance targets. Possible reasons forthis outcome arediscussed.

Introduction 

### For some considerable time, anumber ofgovernmental authorities, including the British Government and theCommission oftheEuropean Union (EU), aswell
as various industrial companies and industry associations, scientists and animal welfare groups, have been concerned that relevant and reliable in vitro 

### alternatives methods should replace the Draize eye irritation test in rabbits as soon as possible. An extensive literature now exists.

Abbreviations

### : AMA =alkaline membrane assay; BCOP=bovine comeal opacity/permeability; CEET =enucleated chicken eye test; DFU =directions for use; EC=European Commission; ECETOC = European Centre for Ecotoxicology and Toxicology of Chemicals; ECVAM =European Centre for the Validation ofAlternative Methods; EDE =EYTEX Draize equivalent; EU =European Union; FL =fluorescein leakage; GLP =Good Laboratory Practice; HETCAM= hen’s egg-2-chorioallantoic membrane test; HO=British Home Office:ICE =isolated chicken eve: IRAG =US 

### Interagency’ Regulatory Alternatiies Group; IRE =isolated rabbit eye; MDCK =MadinDarby canine kidney; MMAS =modified maximum average score; NRU =neutral red uptake; OD =optical density; OECD =Organisation for Economic Cooperation and Development; QC=quality control; RBC =red blood cell haemolysis; RMA =rapid membrane assay; SM=silicon microphysiometer; SOP= Standard Operating Procedure; UMA =upright membrane assay. 

### A meeting to consider the matter was held in London inNovember 1991,under the auspices ofthe British Home Office (HO) and Directorate General XI of the European Commission (EC), with the participation of representatives of British industrial companies and academia, and the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC). Recent progress in the development of alternative methods and steps towards their validation [including the results of an EC pilot study (Commission ofthe European Communities, 1991)]
were considered, and it was concluded that the methods now available were ofsufficient promise for
a formal validation study to be undertaken. It was also recognized that the setting up of an ECETOC task force toidentify asetofchemicals ofknown and different degrees of ocular irritation, specifically for
use in validation studies (Bagley et al., 

### 1992; ECETOC, 1992),afforded asuitable opportunity for the selection of an appropriate set of chemicals suitable forusein such avalidation study on alternatives to the Draize eye irritation test. As a result of this meeting, what waslater to become known asthe EC/HO international validation study on alternatives to the Draize eye irritation test was established. A Steering Group was formed and a series of meetings was held to make detailed proposals about the methods, laboratories, test chemicals and management procedures which could beincluded in such
astudy. Itwasagreed that thefirst priority should be

871872 

### M.Ballset al



### to evaluate the performance of non-animal tests as screens for the detection of chemicals likely to be severely irritant in the eye, while also taking all possible steps to evaluate the usefulness oftests and test batteries for predicting lesser degrees of ocular irritancy. It was also agreed that the proposed study should be conducted according to the principles of validation of non-animal tests as formulated at an international workshop held in Amden, Switzerland, in 1990(Balls et al., 1990a), with the aim ofgaining acceptance of new testing strategies, according to a further set ofprinciples established at another international workshop, held later in the same year in Vouliagmeni, Greece (Balls et al., 1990b). In June 1992, a further meeting was held at the Home Office, London, at which proposals put forward by the Steering Group were discussed with an international group of experts on regulatory testing and on alternatives, from academia and industry, and from the British Department of Health, the former German Federal Health Authority (BGA) and the Organisation for Economic Cooperation and Development (OECD). A Management Team representative ofacademia, industry, the British Government and ECETOC, and composed of members experienced in the conduct and management ofvalidation studies wasappointed with the following membership: Professor Michael Balls (University of Nottingham and HO Animal Procedures Committee); Dr Philip Botham (Zeneca and ECETOC); Dr Leon Bruner (The Procter & Gamble Company); and Professor Horst Spielmann (BGA and Free University of Berlin). The Management Team wascharged with drawing up a plan for the study, preparing a budget and seeking financial support for the study from the British Government, the EC and industrial and nonindustrial laboratories which would be invited to participate in the study. A Chemicals Selection Committee was appointed, under the chairmanship ofDr Arthur Walker (Apojay Consultancy, Whitley Bay,UK), tomake suggestions for the list ofchemicals to be used in the study and to investigate how they might be coded and supplied to the participating laboratories. Following discussions among members of the Management Team and with the Home Office, the University of Nottingham was invited to be the contractor for a grant application to the EC, on condition that coding and supply of the chemicals, and data receipt and analysis should bethe responsibility ofinstitutions independent ofthe university or the Management Team in order to guarantee lack of bias in the study. At the suggestion ofthe Steering Group, afurther international meeting was held at the Home Office, London, on 12-13 October 1992,atwhich theparticipants at the June 1992meeting werejoined by other experts from theUK, Europe and theUSA, including members ofthe US Interagency Regulatory Altematives 

### Group (IRAG) and representatives ofmany of the laboratories which weretobeinvited totake part in the study (see Appendix 1).At this meeting, the goal of the study, tests to be evaluated and procedures for the selection of laboratories and chemicals,and forthe submission and analysis ofdata were discussed and accepted.

The goal of the study It 

### was agreed by the Steering Group that the principal goal of the study would be to provide scientiJicallycredible datafor proposing toregulatory authorities that one or more non-whole-animal methods should be adopted as a replacement for the Draize rabbit eye irritationtest,

### and that four target steps related to this goal would be to determine whether or not the data obtained in the study indicated that it would be possible:
1. to 

### replace the Draize eyetest for identifying all severely irritating materials; or 2. to replace the Draize eye test for identifying severely irritating materials belonging to specific chemical classes; or 3. to replace the Draize eyetest completely (i.e.to identify all levels ofirritancy ofmaterials without regard to chemical class); or 4. to replace the Draize eyetest for identifying all levels of irritancy of materials belonging to specific chemical classes.

The tests to be evaluated 

### The Steering Group was able to benefit from a progress report on a survey ofpotential alternatives totheDraize eyetest,being prepared fortheEC [then in draft form, but now published (Atkinson et al., 

### 1994)j. As a result of this report, and following further discussion with the wider groups ofexperts in June and October 1992, it was agreed that the following nine tests should be included in the study:
1. Aphysicochemical test, based ontheinteraction between test chemicals and a purpose-designed protein matrix (Gordon and Bergman, 1987). 2. A red blood cell haemolysis test, which is an indicator ofcellmembrane and protein damage (Pape et al., 

### 1987). 3. Atest designed toindicate damage to acellular barrier, by measuring leakage of fluorescein across a confluent monolayer of epithelial cells (Shaw et al., 

### 1990). 4. A cell viability test, namely the neutral red uptake assay (Borenfreund and Puerner, 1985). 5. A test involving the evaluation of effects on cellular metabolism in a silicon microphysiometer (Bruner et al., 

### 1991). 6. The hen’s egg-chorioallantoic membrane test (HET-CAM; Luepke, 1985).EC/HO validation study on alternatives to the Drake test 873



### 7. The isolated, enucleated rabbit eyetest (Burton et al., 1981). 8. A similar test involving the use of isolated, enucleated chicken eyes (Prinsen and Koeter, 1992). 9. The isolated bovine cornea test (Gautheron et al., 1992).

These tests were selected because they were representative ofthe kinds ofapproaches available at the time, and because they met some or all of the following criteria:

The specific purposes for which the test had been developed were well defined and likely to complement, but not duplicate, those of other tests in the set. The test had been adequately developed, standardized and documented, and a need for it in relation to other candidate tests had been demonstrated. The test had shown promise in one or more interlaboratory evaluation studies (e.g.those of the EC, the US Soap &Detergent Association, the US Cosmetic, Toiletry &Fragrance Association, or ZEBET). The test wasjudged potentially tobecapable of routine use in laboratories worldwide.

Further details ofthenine tests and how they were conducted are given in Appendix 2.

Management ofthe study The four members of the Management Team jointly took responsibility for the detailed design and execution ofthe project and its day-to-day management, including:

8. Selection oflaboratories and ofalead laboratory for each test. Issuing instructions to laboratories and receiving and answering queries from them. Issuing requests to and receiving instructions from the Chemicals Selection Committee. Agreeing acontract with BIBRA International with regard tochemicals purchase, distribution and supply. Agreeing acontract with BIBRA International with respect to data collection and analysis. Reporting tothe sponsors ofthe study, theEC and HO. Advising the EC contractor (the University of Nottingham) on the finances of the study, including arranging for contracts with participating laboratories and BIBRA International. Monitoring progress in relation tothe goals of the study. 9. Dealing with safety issues. 10.

11.

12. Protecting the integrity of the study and, in particular, the secrecyoftheidentity ofthetest materials. Arranging for meetings with the participating laboratories to discuss the outcome of the study. Two meetings were held: at Egham (Surrey, UK) in March 1994 and at Ittingen (Switzerland) in September 1994. Producing this report on the study.

The Management Team maintained contact by letter, fax, conference telephone calls and regular meetings.

The participatinglaboratories Following discussion attheExpert Meeting inJune 1992, it was agreed that, in line with the Amden proposals on validation (Balls et al., 

### 1990a), four or five laboratories should be invited to conduct each test. Suggestions were made concerning the laboratories to be selected, taking into account the need for appropriate experience, adherence totheprinciples of Good Laboratory Practice (GLP) and for international participation. After further discussions by the Management Team, a lead laboratory for each test was identified, on the basis of demonstrated experience with the test concerned. The lead laboratories were responsible for maintaining contact withtheManagement Team onbehalf of the nine groups of laboratories, with respect to:
Logistical problems. Questions related to test protocols and GLP. Assuring consistent handling of test materials and application ofprotocols. Overseeing data reporting, but without having
access to the actual data from other laboratories.

The full set oflaboratories and contact persons was as follows:
1. The Red Blood Cell Haemolysis (RBC) Test 

### Zeneca CTL, Macclesfield, Cheshire, UK (Dr Richard Lewis)-lead laboratory. 

### Beiersdorf AG, Hamburg, Germany (Dr Wolfgang Pape). Shell Research Ltd, Sittingbourne, Kent, UK (Dr John Gardner). Rhone-Poulenc, Valbonne, France (Dr David Esdaile).

2. The EYTEA? Method 

### 1. Atochem, La Defense, Paris, France (Dr JeanFran9ois Regnierplead laboratory.

### M.Ballsetal.

814


### 2.
3.
4. Albright &Wilson Ltd, Whitehaven, Cumbria, UK (Dr Cliff Martin). Avon Products Inc.. Suffern, NY, USA (Dr Kevin Renskers). Sanofi Recherche, Montpellier. France (Dr Catherine Robles).

3. TheBovineCornea1Opacity/Permeability (BCOP) Test 1. 

### Laboratories MSD-Chibret, Riom, France (Dr Pierre Gautheron+lead laboratory. 

### CIDA. Barcelona, Spain (Dr Lourdes Mayordomo). Janssen Pharmaceutics, Beerse. Belgium (Dr Philippe Vanparys). ZEBET, BgVV, Berlin (Dr Joachim Heuer). RBM, Ivrea, Italy (Dr Raffaella Pirovano).

4. The HET-CAM Test 

### Henkel KGaA, Dusseldorf, Germany (Dr Winfried Steiling)--lead laboratory. 

### Beiersdorf AC, Hamburg, Germany (Dr Wolfgang Pape). L’Oreal, Aulnay-sous-Bois, France (Dr Odile de Silva). Parfums Christian Dior, Saint Jean de Braye, France (M Pascal Courtellemont).

5. The Fluorescein Leakage (FL) Test 

### Department of Human Morphology, University of Nottingham, Nottingham, UK (MS Karen Atkinson)--lead laboratory. 

### L’Orial, Aulnay-sous-Bois, France (Dr Martine Cottin). State University of New York, Binghampton, NY, USA (Dr Robert Van Buskirk). Philadelphia College of Pharmacy & Science, Philadelphia, PA, USA (Dr Ruy Tchao).

6. The Isolated Chicken Eye (ICE) Test 

### TN0 Toxicology & Nutrition Institute, Zeist, The Netherlands (Mr Menk Prinsen)-lead laboratory. 

### Shell Research Ltd, Sittingbourne, Kent, UK (Dr John Gardner). Rhone-Poulenc. Valbonne, France (Dr David Esdaile). ESL, Unilever Research, Sharnbrook, Bedford, UK (Dr Lesley Earl).

7. The Isolated Rabbit Eye (IRE) Test 

### 1. ESL,Unilever Research, Sharnbrook, Bedford, UK (Dr Lesley Earltlead laboratory. 2. 

### Shell Research Ltd, Sittingbourne, Kent, UK (Dr John Gardner). 3.
4. Zeneca CTL, Macclesfield, Cheshire, UK (Dr Richard Lewis). IHE, Ministry of Public Health of Environment, Brussels, Belgium (Dr GA Jacobs).

8. The Silicon Microphysiometer (SM) Test 

### The Procter & Gamble Company, Cincinnati, OH, USA (Dr Rosemarie Osborne)-lead laboratory. 

### Microbiological Associates Inc., Rockville, MD, USA (Dr Rodger Curren). L’Oreal. Aulnay-sous-Bois, France (Dr Martine Cottin). Department ofChemistry, Stanford University, Stanford, CA, USA (Dr Harden McConnell).

9. The Neutral Red Uptake (NRU) Test 

### Microbiological Associates Inc., Rockville, MD, USA (Dr Rodger Currentlead laboratory. 

### Istituto Superiore di Sanita, Rome, Italy (Dr Annalaura Stammati). Hatano Research Institute, Kanagawa, Japan (Dr Hiroshi Ono). Kurabo Industries Ltd, Osaka, Japan (Dr Ryohei Yamamoto).

Selection of chemicals 

### In 1992, ECETOC published a Reference Data Bank for ocular irritation (Bagley et al., 

### 1992; ECETOC, 1992) which presented the eye irritation data on individual rabbits obtained in Draize eye tests involving readily available chemicals of high purity. One object of the provision of in uivoeye 

### irritation data in the publication was to make it unnecessary for experimenters to carry out in uivo 

### studies simply to generate data to be used in the assessment of alternative eye irritation tests. The following stringent criteria were used in the selection of chemicals and data, with the result that the data bank comprised 60 chemicals assessed in 72 tests:

1. The reference chemicals should be single chemical entities available at known high consistency and purity and expected to be stable in storage. 2. The inuivo

### rabbit eyeirritation data should have been generated since 1981,in studies carried out according toOECD Test Guideline 405(OECD, 1987) and following the principles of Good Laboratory Practice (GLP) and should have been obtained in tests: -normally using at least three New Zealand White rabbits, tested at the same time; -involving instillation of 0.1ml or the equiv-

### EC/HOvalidation studyon alternativestotheDraizetest 875

alent weight into the conjunctival sac; -in which topical intraocular anaesthesia was not used; -in which observations weremade (atleast) 24, 48 and 72hr following instillation, and: -included individual scores (using theDraize scale) for each tissue measured in each rabbit; --enabled reversibility/irreversibility to be assessed; --in which chemicals were tested undiluted (except that data from studies using dilutions of the chemical were acceptable, when higher concentrations of the chemical could have been expected to cause severe effects).

The ECETOC Task Force ranked the irritancy potential of the chemicals in terms ofMMAS. This index was ‘modified’ from that originally proposed by Draize, but only inthat itwasdeveloped from Draize
scores calculated 24hr or more after instillation of thechemical (because not allthechemicals inthedata bank had been assessed 1hr after instillation in the rabbit eye). The ECETOC Task Force that developed theData Bank became the Chemicals Selection Committee for the EC/HO validation study, although individuals who would bepractically involved in the study were excluded inorder tomaintain strict confidentiality. A first selection of60test materials from the ECETOC data bank was presented to the meeting held in London inJune 1992.This selection wascriticized in that thenumber ofchemicals tested in solid form was inadequate, there wereinsufficient chemicals ofmoderate to severe irritancy, and no pesticides were included. At the meeting, the Chemicals Selection Committee wasmade aware ofother studies, not then published, and ofother sources ofunpublished data, which widened the range ofboth chemical types and irritant properties. Consequently, additional data
were obtained, and those chemicals and data which met the ECETOC selection criteria have been deposited in the ECETOC Data Bank. A revised proposal for asetof60testmaterials wasthen made and accepted by the Management Team for the EC/HO validation study. The final selection consisted of 52 chemicals assessed in60different tests (four chemicals
were tested at two, and two at three concentrations). 26 ofthe test materials were liquids. The remaining 34were solids, 20ofwhich wereadministered assuch in the in vivo 

### tests, while the remaining 14 were administered as diluted solutions (Table 1). After the invitro

### testing had begun, further checking ofthe invivo

### data revealed that 14ofthematerials had been tested by aprotocol which involved rinsing after 1hr or removal of solids after 1hr. These data therefore did not meet the ECETOC criteria. It was decided, with great reluctance, that these 14materials would have to be tested invivo

### because the invitro 

### testing had already begun. This work was commissioned by those who had given the original data to ECETOC, at no cost to ECETOC or the EC/HO study. One ofthese 14chemicals, thiourea, killed all three rabbits used by aneurotoxic effect.This chemical was therefore excluded from further testing and from the inviva/invitro

### comparisons in the EC/HO study. Table 1 shows the 60 test materials in order of decreasing MMAS. The source, purity and solubility ofthechemicals, theconcentration and form inwhich they were tested invivo,

### the number ofanimals used in each study, and the form tested invitro, 

### are also included inTable 1.In Table 2,the test materials are presented, together with the MMAS, in their 14 different chemical groups. The standard deviations of themean MMASs aregiven inTable 1and illustrated in Fig. 1.

Supply, coding anddistributionofsamples The responsibility for these three functions was assigned to BIBRA International, Carshalton, Surrey, UK (Brantom et al., 

### 1995).

SUPPlY 

### Chemicals with the same source and specification
as those tested invivo

### were obtained, wherever feasible. Where this was not possible, a specification as close aspossible tothat used inthe invivo

### testing was chosen.
Dispensing 

### To avoid any possible confusion of one test substance with another:

-only one substance was dispensed at any one time; -all samples were sealed and labelled with unique coded labels before the next substance was dispensed.

After dispensing, samples were returned to appropriate storage conditions until they were packed for despatch. Codingandlabelling 

### Each substance was first allocated anumeric code. Each participating laboratory was also allocated a unique code number so that subsequent analysis of invitro

### data would bepossible without knowledge of the identity ofthe laboratory or test substance. The number ofaliquots ofeach substance required for the full study was defined (requiring precise definition ofthenumber oflaboratories participating, and the total number ofassays). Random codes wereNO. Chemical’ Table 1. 60 test materials used in the EC/HO study, listed in order of decreasing MMAS Chemicals information In viuo test information

~~~ In vitro Form Concn Mean of SD of form CAS no. Source’ Cataloaue no. Puritv Solubilitv’ tested* tested MMAS’ MMAS’ n’ tested4 I 2 3 4 5 6 7 8 9 IO II I2 13 14 15 I6 17 I8 19 20 21 22 23 24 25 26 27 28 29 30 31 32 Sodium hydroxide 1310-73-2 Fisher

Benzalkonium chloride X001-54-5 Sigma Trichloroacetic acid 76-03-9 Fisher Cetylpyridinium bromide 140-72-7 Sigma Cetylpyridinium bromide 140-72-7 Sigma Benzalkonium chloride’ X001-54-5 Sigma Captan 90 concentrate* 133-06-2 EPA Chlorhexidine’ 50-56-I Degussa Cyclohexanol 10X-93-0 Fisher Quniacrine* 69-05-6 Sigma Promethazine HCI* 58-33-3 Aldrich Parafluoraniline 371-40-4 Aldrich Triton X-100 9002-93-I Sigma Acetone+ 67-64-I Fisher n-Hexanol IIl-27-3 E-Kodak I-Naphthalene acetic acid* 61-31-4 EPA Sodium oxalate’ 62-76-O Aldrich Isobutanol x 78-83-l Fisher Imidazole* 288-32-4 Aldrich Sodium lauryl sulfate+ 151-21-3 Sigma 2-Ethyl-I -hexanol 104-76-7 Fisher 4Carboxybenzaldehyde 619-66-9 Sigma Methyl ethyl ketone’ 78-93-3 Fisher Pyridine’ 11O-86-I Aldrich I-Naphthalene acetic acid* 86-87-3 EPA Benzalkonium chloride (I]/[21 8001-54-5 Sigma 2,2-Dimethylbutanoic acid 595-37-9 Aldrich Gammabutyrolactone’ 96-48-O Aldrich Thiourea’ 62-56-6 Aldrich n-Gctanol* 

### 11 l-87-5 Aldrich Methyl acetate + 79-20-9 Fisher t,-Aspartic acid* 70-47-3 Degussa Reagent grade B-1383 Reagent grade C-588 I C-588 

### I B-1383 98
98 98 98 90
855757 97 Q 3251 2X,41I-4 98 F380-0 99 T6878 98 Al8 99 BIHC 98 95 22,343.3 >99 851962 99.9 I-20-2 99 L-4509 98 85535 99 Cl904 95 M-209 99 27,04C-7 > 99.9 96 B-1383 98 DI5,260-9 96 810,360-X > 99 24,025-7 > 99 29,324-5 > 99 M-203 98

100 S SU 10

Sf SU IO S SU 30 Sf SU IO Sf SU 6 Sf SU 5 S SO 100 I* SO 100 S L 100 S SO loo s* SO 100 I L 100 Sf SU 10 S L 100 I* L 100 S* SO 100 S SO 100 I* L 100 S SO 100 Sf SU I5 S L 100 I* SO 100 S L 100 S L 100 I’ SO 100 Sf SU I I L 100 S L 100 S SO 100 I* L 100 S L 100 S SO 100 108.00 0.00 I 108.00 0.00 3 106.00 0.00 I 89.67 7.20 6 85.75 3.69 4 83.75 3.10 4 83.00 21.07 7 82.33 20.2

### I 3 79.75 4.27 4 82.00 0.00 3 Il.67 16.17 3 69.83 13.75 6 68.67 12.91 6 65.75 4.50 4 64.75 16.26 4 64.50 29.78 6 61.33 3.21 3 60.25 8.10 4 59.33 9.02 3 59.17 9.26 6 51.25 19.75 4 50.33 13.80 3 50.00 17.51 4 48.00 9.54 3 46.67 13.71 6 45.29 ? 10 44.67 14.49 6 43.00 14.42 3
41.00 15.62 3 39.50 17.71 4 37.33 19.66 3 SU SU SU SU SU SU SO SO L SO SO L SU L L SO SO L SO SU L SO L L SO SU L L SO L L SO33 34 35 36 37 38 39 40 41 42 43 44 45 46 41 48 49 50 51 52 53 54 55 56 51 58 59 60 Benzoyl-~-tar&c acid* 2143-38-6 Aldrich 34,584-9

Tli1on x-100 [I]/[21 9002-93-I Sigma T-6878 Potassium cyanate* 590-28-3 Degussa 1sopropano1+ 67-63-O Fisher 854888 Sodium perborate, 4H,O 10486-00-7 Dupont 004666 Dibenzyl phosphate* 1623-08-l Aldrich D3,655-0 2,5-Dimethylohexanediol* 110-03-2 BASF Methyl cyanoacetate* 105-34-o Aldrich 10,842-I Sodium hydroxide l 1310-73-2 Fisher Reagent grade Ethanol’ 64-17-5 Local vendor - 2,bDichlorotenzoyl chloride 4659-45-4 Aldrich 18,751-B Ammonium nitrate 6484-52-2 Aldrich 25,606-4 Ethyl-2-methylacetoacetate m-14-3 Fluka 65440 Sodium lauryl sulfate 151-21-3 Sigma L-4509 Ethyl acetate’ 141-78-6 fisher E-145 Maneb* 12427-38-2 EPA - Fomesafen* 72128-02-o EPA - Tetmaminopyrimidine sulfate* 5392-28-9 Aldrich T380-7 Toluene 108-88-3 Fisher T-324 n-Butyl acetate 123-86-4 Fisher B-396 Trichloroacetic acid+ 76-03-9 Fisher Reagent grade Methyl isobutyl ketone 108-10-I Fisher M-213 Tween 20 9005-64-5 Sigma P-1379 Ethyl trimethyl acetate 3938-95-2 Aldrich 23,455-9 Methylcyclopentane 96-31-1 Fluka 66495 Cetylpyridinium bromide 140-72-7 Sigma C-5881

_. 

### __ ^.

_ __.. . . 98 98 91 99.9 98.6 99 99.5 99

99 > 99.9 c.91 98 99 c.90 91.5 91 99 99

- 98 98 99 > 99 98 > 99.5 I

Sf S
s S I’ I s* S
s I* S S* Sf S
s S I* I* If S I* Sf I* I* Sf S Sf SO loo

SU 5 SO 100 L 100 SO 100 SO 100
so 100 L 100 SU 1 L 100 L 100
so 100 L 100 SU 3 L 100
so 100
so 100
so 100 L 100 L 100 SU 3 L 100 L 100 L 100 L 100 SU 0.1 L 100 L 100 36.61 33.08 31.33 30.50 30.50 30.00 28.33 21.61 25.15 24.00 23.83 18.33 18.00 16.00 15.00 14.33 13.50 IO.33 9.00 7.50 6.61 4.15 4.00 3.83 3.67 2.61 1.67 0.00 10.02

? 8.02 20.63 13.68 1.94 5.51 9.29 10.18 14.11 6.43 6.03 4.36 8.32 3.56 8.14 1.84 6.03 2.00 4.36 2.99 2.99 2.31 3.82 2.34 I.97 0.82 0.00 3

12 3 4 6 3 3 3 4 3 6 3 3 6 4 6 6 3 4 4 6 4 4 6 6 6 6 6 

### so

SU 

### so L
so so so L SU L L
so L SU L
so so so L L SU L L L L SU L L tilycerol 56-x1-5 Matlmkrcdt Polyethylene glycol 400 25322-68-3 Aldrich 20.239-B ‘Chemicals: l = 22 chemicals not from the ECETOC Reference Chemicals Data Bank; ’ = 10 chemicals used in the preliminary study; [I]/[21= two tests on the same chemical in the same laboratory. 2Source: EPA = US Environmental Protection Agency. ?Golubility: S= soluble in water; I= insoluble in water; Sf= surfactant; l = solubility uncertain. ‘Physical form: So = solid; Su = solution; L= liquid. ‘MMAS = modified maximum average score (Bagley ef al., 1992; ECETOC, 1992). 6sD = standard deviation. ‘n= number of animals used in Draize eye tests.878 

### M.Ballseral

Table 2. Chemical grouping ofthe 60test materials MMAS Acids (four chemicals, fivetests) Trichloroacetic acid (3%) Dibenzoyl-L-tartaric acid*t L-Aspartic acid’t 2,2-Dimethylbutanoic acid Trichloroacetic acid (30%)$ Acylhalide (one chemical) 2,6-Dichlorobenzoyl chloride Alcohols (nine chemicals) Glycerol Ethanol’ 2,5-Dimethylhexanediol’t lsopropanolf n-Octanol 2-Ethyl-hexanol Isobutanol$ n-Hexanol Cyclohexanol Aldebyde (one chemical) 4-Carboxybenzaldehydet Alkalis (one chemical, two tests) Sodium hydroxide (I%)I Sodium hydroxide (10%) Esters (sixchemicals) Ethyl trimethylacetate n-Butyl acetate Ethyl acetate1 Ethyl-2-methylaetoactate Methyl cyanoacetate Methyl acetatei Heterocyclics (three chemicals) Tetraaminopyrimidine sulfate*t Pyridine’ Imidazole’t Hydmcuhons (two chemicals) Methylcyclopentane Toluene Inorganic dwmicals (four chemicals) Ammonium nitrate7 Sodium perborate 4H,Ot Potassium cyanate*t Sodium oxa1ate.t Ketones (three chemicals) Methylisobutylketone Methylethylketonef Acetone: Organqlwphate (one chemical) Dibenzyl phosphate*? P&kidea (fivechemicals) Fomesafen (acid form)*? Maneb*t I-Nephthalene acetic acid*? 1-Naphthalene acetic acid, Na salt* Captan 90 concentrate’t Surfactanta (sixchemicals, I2 tests) Anionics Sodium lauryl sulfate (3%) 16.0 Sodium lauryl sulfate (lS%)f 59.2 CatiOOieS Benzalkonium chloride [I]/[21(1%) Benzalkonium chloride (So/.)$ Benzalkonium chloride (IO%) Cetylpyridinium bromide (0.I%) Cetylpyridinium bromide (6%) Cetyipyridinium bromide (10%) NOlliODiea Polyethylene glycol 400 Tween 20 Triton X-100 [11/[2](5%) Triton X-100 (10%) Miscellaneous (sixchemicals) Gamma-butyrolactone* Thiourea*t Parafluoroaniline Promethazinc HCI*t Quinacrine*t Chlorhexidine*t 6.1 36.1 37.3 44.1 106
23.8
1.7 24.0 28.3 30.5 41.o 51.3 60.3 64.8 79.8
50.3
25.8 108
3.8 1.5 15.0 la.0 21.1 39.5
10.3 48.0 59.3
3.7 9.0
18.3 30.5 31.3 61.3
4.8 50.0 65.8
30.0
13.5 14.3 46.1 64.5 83.0

34.3156.3 83.8 ioa.0 2.1 85.8 89.7
0.0 4.0 32.3133.8 68.1
43.0
6F8 71.7 82.0 82.3 *22chemicals not from theECETOC reference chemicals data bank; t20 solids; $10 chemicals used in the preliminary study; [I]/[21=two tests on the same chemical inthe same laboratory. 

### generated bycomputer software forthetotal number ofsamples, sothat each sample had aunique number. Distribution 

### Shipping chemical samples worldwide was carried out incompliance with various regulations governing thetransport ofdangerous substances and health and safety. These regulations generally require that the UN hazard and packing class are known for all substances tobetransported. Despite the small quantities involved in this study, there are significant limitations on the substances which can be transported in the same container, as well asprohibitions imposed by IATA on carrying certain chemicals as air freight. The procedure forhandling many ofthese issues was developed successfully by working with a number ofthe major shipping companies. Samples wereshipped under conditions designed to minimize damage during transit. Asmost substances
are expected to be most stable when stored at low temperatures, recipients were advised to store all the samples in a refrigerator. The US and Japan require that any shipment of chemicals must be accompanied by relevant health and safety data. Most recipients were able toidentify
a safety officer to receive the samples and retain the health and safety data before passing the samples to the experimental laboratory. Therefore, disclosure of the codes of samples was unnecessary, so the blind nature ofthe study was not jeopardized. Health and safety data 

### An emergency procedure was established to allow any participant to obtain the necessary health and safety data intheevent ofan accident. The procedure involved lodging a sealed envelope containing a full set of the coding information for each laboratory with theWest Midlands Poison Centre (Dudley, West Midlands, UK). All participating laboratories were given the telephone number ofthe Poison Centre so that if an 

### emergency occurred, the code could be broken, in which case the Poison Centre would inform the Management Team. This happened on one occasion, without any serious consequences for the technician concerned or for the integrity of the study.

Data collection andanalysis Data collection and analysis were performed by BIBRA International (Carshalton, Surrey, UK). The data analysis was conducted by a group that was completely independent from those who coded and distributed the test substances. This independence
was maintained to ensure that the analysis was conducted in a blind fashion. Data collection and quality control review 

### A data matrix containing the identity of each chemical, the in vivo eye 

### irritation data and each alternative method endpoint was established, based

### EC/HOvalidation studyon alternativestotheDraizetest 879



## 80

50 60



# Compound No. Fig.I. MMAS,meanf standarddeviation,for59chemicals,assuppliedtothemanagementteambythe ChemicalsSelectionCommittee.TheMMASscoreusedintheanalysisfortwochemicals(nos26and34) wasameanbasedontwoseparatestudies.Thevaluesfromeachstudyareshownseparatelyinthe 

### graph.

on information provided by the chemicals subgroup and participating laboratories. The data from each alternative method were provided on report forms submitted to BIBRA by each laboratory. The data contained in each report form werethen entered into
acomputer spreadsheet tocreate thedata matrix. The integrity ofthe data entry process was checked in an internal quality control review by BIBRA In addition, BIBRA confirmed that the data entry was correct by asking each of the participating laboratories to review the tabulated results against the results they had submitted. The Management Team reviewed each ofthe proposed changes that followed this check, to confirm that any alterations in data
werejustified, because oferrors in data transcription. Statistical analysis 

### Statistical analyses of the data contained in the data matrix were carried out using the Minitab package (Minitab, 1992;Ryan etal., 

### 1985).The data matrix contained 60rows (for each test substance in thetest set)by 83columns (foreach ofthe alternative method and invivo

### endpoints). The data analysis was carried out on the full set and six subsets of the reference test substances. The sets oftest substances evaluated are shown in Table 3. The allocation of each testmaterial into the subsets wasdetermined by the Chemicals Selection Committee. Some of the materials were of uncertain solubility. These chemicals are indicated in Table 1.No attempt was made to incorporate this uncertainty into the analysis. The statistical procedures used in the data analysis
were designed to assess (1)the between-laboratories reproducibility ofthe alternative method data and (2) the relationship between the in vivo eye 

### irritation potential ofeach test substance versus each endpoint obtained from each alternative method. Evaluationof interlaboratoryvariability 

### An analysis ofthe degree of interlaboratory variability in alternative method scores was carried out, first by determining the correlation between the

Table 3. Subsets of test substances evaluated in the data analysis process. This table indicates the seven subsets of reference test substances which were evaluated in the data analysis process. The number oftest substances placed into each subset isalso indicated. The full sat was subdivided in two ways: first into non-surfactant chemicals soluble orinsoluble inwater, and surfactant; and secondly, into solids, solutions made from solids and liquids (seeTable 1) Set evaluated No. of substances A. Full test set 60 B. Chemicals soluble in water 30 C. Chemicals insoluble in water 18 D. Surfactants 12 E. Solids 20 F. Solutions 14 G. Liquids 26880 M. Balls et

### al.

in vitro test results generated for each alternative method score in each laboratory. This a!lowed the construction ofmatrices containing Pearson’s correlation coefficients for each possible interlaboratory comparison. These matrices are shown for the entire test set, water-soluble materials, water-insoluble materials, surfactants, solids, solutions and liquids in Table 4A-G. In addition, an analysis ofvariance was carried out toquantify the degree ofvariability inthe results among the laboratories and chemicals. The residuals obtained from this analysis wereplotted for each ofthetest substances evaluated inthealternative methods. The data from the analysis ofvariance are not shown in this report. The interested reader will find these data in the full report ofthe study, which is available from ECVAM. Evaluation ofthe relationship between the invivaand alternative method data A statistical analysis was conducted to assess the relationship between the in vivo and alternative method data. This wasdone todetermine whether the alternative methods could predict the eye irritation potential of the reference test substances. 59 rather than 60test substances wereincluded in this analysis since invivo data were unavailable for thiourea (see above for explanation). The in vivo endpoint used to define the irritancy potential of the test substances was the MMAS, as defined in the ECETOC Technical Report on Eye Irritation (Bagley et al., 1992;ECETOC, 1992).The MMAS isbased on the eyeirritation scoring scheme developed by Draize et al. (1944). The MMAS was used asthe invivoeyeirritation endpoint because the working group which met at the Home Office in October 1992concluded that this endpoint would be most appropriate for use in this study. Initially, scatterplots were prepared so that the relationship between the MMAS versus each alternative method endpoint could be visualized. These scatterplots are shown inFigs 2and 3.Figure 2shows theresults obtained from thelead laboratories forthe full set oftest substances. Figure 3shows the results from thelead laboratories forthe subset ofsurfactant test substances. Each symbol shown in the plots represents a result from a single test substance. Censored values (i.e. results given with values < or > for certain cut-off scores) are shown in the figures
asupward-pointing or downward-pointing triangles, respectively. The study statistician included these censored values in the calculations of linear regression, 95% confidence intervals and correlation coefficients. For the HET-CAM and BCOP assays, the protocols indicated that scores >2 and >200, respectively, should be reported as either 2 or 200, respectively. As laboratories reported uncensored
scores greater than 2 and 200, data analysis was completed on two setsofdata. One analysis included theuncensored data and asecond usedcut-off values. The linear regression linetobeusedforpredicting the MMAS from an alternative method index and the 95% confidence interval for the linear regression line
are shown on each scatterplot. The 95% confidence interval for an MMAS prediction from a given alternative method index is also shown. In some cases, laboratories reported that some materials could not be tested because of technical factors such aslimited water solubility. These results
were reported as missing values (see Table 4) and
were not included in the scatterplots or statistical analysis. Quantitative statements provided by the laboratories (such as ‘non irritant atsolubility’ forthe SM test) werenot included inthe quantitative analysis. Rather, these results were reported in tabular form. Logarithmic transformation wasperformed on the RBC test DMax,D,,, and H,, scores, and on the NRU assay NRU,, scores. Statistics were calculated in the quantitative data analyses process for the entire test set, water-soluble materials, water-insoluble materials, surfactants, solids, solutions and liquids. The results from this analysis are shown inTable 4A-G, respectively. This summary table indicates (starting from left to right) the alternative methods index analysed, the number ofsubstances tested (n), the number ofchemicals for which no data were provided (missing), the Pearson product moment correlation coefficient (r), Spearman’s rank correlation coefficient (rank r),the linear regression equation to be used for predicting an MMAS from an alternative method index score and
anestimate ofthe sample standard deviation from the regression(s). This latter value isused to estimate the 95% confidence interval for the prediction of an MMAS from an alternative method score. Finally, a Mann-Whitney test was conducted to determine whether the rankings of the alternative methods scores between two sets of chemicals is different. The rankings of the alternative method index scores for chemicals with MMAS values >59
were compared against those from chemicals having MMAS scores <59inthefirsttest.Asecond testwas performed tocompare the rankings ofthe alternative method scoresforchemicals with MMAS ~25 versus those having MMAS>25. Although the MannWhitney test sometimes provided statistically significant W statistics, inspection of the scatterplots indicated these values arenot biologically significant. Accordingly, the results of Mann-Whitney tests are not shown in this report. Interested readers will find the results from this analysis contained in the full study report, which is available from ECVAM.

Results 

### A summary ofthe data analysis for the seven sets ofcomparisons between the invivoand invitro data isshown inFigs 2and 3and Table 4.Figure 1shows the eyeirritation scores given asthe MMAS for the 59 materials included in the reference set of test substances. The error bars show the variation oftheTable 4. Summary of statistical analysis of EC/HO study

In uilro testing In viva 0. invitrocorrelation Interlaboratory correlation of invitrodata

No. of No. of Spearman’s Alternative samples samples Pearson’s rank method tested not tested correlation correlation index invitro invitro coefficient coefficient Linear regression equation Lab Lab a Lab b Lab c Lab d Lab e A. Thefullset of 60 chemicals RBCbLI RBCDLZ RBCDL3 RBCDU 56 60 58 59 IogDL I 56 logDL2 60 logDL3 58 logDL4 59 RBCDM 1 56 RBCDMZ 60 RBCDM3 58 RBCDM4 60 IogDM 

### I 56 logDM2 60 logDM3 58 logDM4 60 RBCHI 56 RBCHZ 60 RBCH3 58 RBCH4 59 IogHl 56 logH2 60 logH3 58 logH4 59 EYTEX 5 EYTEX 6 EYTEX 7 EYTEX 8 BCOPW BCOPPIO BCOPPI I BCOPPIZ BCOPPI 3 BCOP09 BCOPOIO BCOPOl 1 BCOPOl2 BCOPOI 3 49 49 57 51 60 60 60 60 60 60 60 60 60 60 4

0 2 1 4 0 2 1 4 0 2 0 4 0 2 0 4 0 2 I 4 0 2 I II II 3 9 0 0 0 0 0 0 0 0 0 0 - 0.206

- 0.254

- 0.196

- 0.238

- 0.012

- 0.108

- 0.055

- 0.107 0.433 0.365 0.400 0.277 0.400 0.321 0.420 0.286

- 0.309

- 0.268

- 0.236

- 0.306

- 0.310

~ 0.31I

~ 0.200

~ 0.401 0.376 0.294 0.383 0.298 0.338 0.319 0.392 0.433 0.503 0.391 0.293 0.326 0.342 0.373 - 0.058

- 0.128

- 0.015 -0.119

- 0.058

- 0.128

- 0.015 -0.119 0.351 0.310 0.385 0.229 0.351 0.310 0.385 0.229

- 0.298

- 0.305

- 0.229

- 0.391

- 0.298

- 0.305

- 0.229

- 0.391 0.415 0.338 0.459 0.350 0.363 0.355 0.375 0.465 0.449 0.465 0.555 0.529 0.48I 0.527 MMAS = 48.485 - 1.35E-04 RBCDLl

MMAS = 49.302 - 1.69E-04 RBCDLZ MMAS = 48.180 - I.27E-04 RBCDL3 MMAS = 48.309 - 1.52E-04 RBCDL4 MMAS = 43.811 - 0.371 IogDLI MMAS = 56.683 - 3.501 logDL2 MMAS = 48.037 - 1.265 logDL3 MMAS = 57.294 - 3.761 logDL4 MMAS = 34.718 + 0.562 RBCDMl MMAS = 33.873 + 0.323 RBCDMZ MMAS = 36.294 + 0.461 RBCDM3 MMAS = 38.051 + 0.284 RBCDM4 MMAS = 34.953 + 15.997 1ogDMl MMAS = 33.616 + 11.016 logDM2 MMAS = 35.024 + 16.179 logDM3 MMAS = 37.588 + 10.759 logDM4 MMAS = 49.279 - 2.27E-04 RBCHI MMAS = 48.298 - 2.26E-04 RBCHZ MMAS = 48.226 - 1.738-04 RBCH3 MMAS = 47.896 - 2.28E-04 RBCH4 MMAS = 75.519 - 8.999 logHI MMAS = 76.352 - 9.266 logH2 MMAS = 60.362 - 4.903 logH3 MMAS = 88.200 - 12.714 logH4 MMAS = 13.452 + 0.826 EYTEX 5 MMAS = 21.258 + 0.571 EYTEX 6 MMAS = 14.382 + 0.783 EYTEX 7 MMAS = 19.376 + 0.636 EYTEX 8 MMAS = 33.009 + 5.305 BCOPP9 MMAS = 34.162 + 4.163 BCOPPIO MMAS = 30.824 + 6.118 BCOPPI I MMAS = 30.384 + 7.351 BCOPP12 MMAS = 27.646 + 12.035 BCOPPI 3 MMAS = 33.939 + 0.185 BCOP09 MMAS = 37.142 +0.127 BCOPOIO MMAS = 37.122 + 0.143 BCOPOll MMAS = 36.034 + 0.127 BCOP012 MMAS = 34.858 + 0.197 BCOP013 1.ooo 0.924 0.843 0.827 1.000 0.852 0.667 0.749 I.oOo 0.703 0.676 0.647 1.000 0.696 0.736 0.680 1.000 0.913 0.822 0.946 1.000 0.908 0.762 0.857 1.000 0.757 0.916 0.920 1.000 0.777 0.886 0.797 0.856 1.000 0.924 0.934 0.946 0.970 1.ooo

0.901 0.910

1.000 0.702 0.749

1.000 0.727 0.442

I.000 0.713 0.432

1.000 0.788 0.906

1.000 0.771 0.865

1.000 0.749 0.803

1.000 0.862 0.683 0.788

1.000 0.898 0.905 0.936 I.ooo

0.822

I.oOa 0.689

1.oOo 0.702

1.000 0.715

l.ooo 0.869

I.000 0.746

1.000 0.868

1.000 0.859 0.906

1.oOO 0.978 0.953 1.ooo

l.ooo

1.ooo

I

### .ooo

I

### .ooo

1.000

I.000

1.000 0.892 1.000

l.ooO 0.955 I.oOo [contd]In uirrotesting Inuivo0. inuitrocorrelation
No. of No. of Spearman’s Alternative samples samples Pearson’s rank method tested not tested correlation correlation

BCOP19 BCOPIIO BCOPIII BCOPII2 BCOPI13 index invitro

60 60 60 60 60 invim coefficient coefficient Linear regressionequation MMAS = 26.881 + 0.21

### I BCOP19 MMAS = 30.601 +0.162 BCOPIlO MMAS = 30.482+ 0.179 BCOPIII

BCOPI9b 60 BCOPIlOb 60 BCOPI

### IIb 60 BCOPI

### I2b 60 BCOPI

### I3b 60 0 0.492 0 0.411 0 0.448 0 0.448 0 0.490 0 0.508 0 0.524 0 0.553 0 0.536 0 0.549 II 0.310 20 0.368 13 0.41I 19 0.517 49 0.186 47 0.108 47 0.332 43 0.060 II 0.416 20 0.527 13 0.465 I9 0.451 49 0.308 47 0.089 47 0.320 I9 *** 1 -0.555 0 -0.565 0 -0.151 I -0.370 0 0.522 0 0.525 I 0.567 2 0.433 0 0.461 0 0.346 0 0.491 0 0.529 0 0.445 0 0.380 0.520 0.529 0.555 0.571 0.568 0.522 0.533 0.557 0.573 0.570 HETQ14 HETQl5 HETQ16 HETQl I 49 40 41 41 0.489 0.441 0.480 0.596 HETS14 HETSIS HETS16 HETSl7 II 13 13 17 0.29I 0.051 0.340 0.018 HETQ14b HETQl5b HETQ16b HETQI 7b 49 40 47 41 0.48I 0.588 0.462 0.581 HETS14b HETSISb HETS16b HETS17b 11 13 13 41 0.318 0.069 0.329 tt. MMAS = 30.739+ 0.155 BCOPI12

MMAS = 28.926+ 0.235 BCOPI13 MMAS = 24.100+ 0.264 BCOPI9b MMAS = 24.438 +0.264 BCOPIIOb MMAS = 23.478+ 0.310 BCOPII lb MMAS = 23.571 + 0.280 BCOPII2b MMAS = 25.558+0.306 BCOPII3b MMAS = 32.356+ 1.799HETQ14 MMAS = 26.833+ 3.473 HETQl5 MMAS = 32.721 + 2.919 HETQ16 MMAS = 18.271+ 5.105 HETQl7 MMAS = 45.789 + 2.554 HETSl4 MMAS = 37.824+ 0.352 HETSIS MMAS = 37.068+ 2.473 HETSl6 MMAS = 45.455 + 0.262 HETSl7 MMAS = 6.665+ 20.347 HETQI4b MMAS = - 6.835+ 29.423 HETQI 5h MMAS = 0.675 + 27.262 HETQ16b MMAS = - 22.371 + 34.706 HETQl7h MMAS =44.184+ 10.158 HETS14b MMAS = 31.449+ 5.881 HETSISb MMAS = 35.805 + 8.061 HETSl6b

*** FL20 18 FL20 19 FL20 20 FL20 21 59 60 60 59 -0.579

- 0.598 -0.176 -0.405 ICES 22 60 ICES 27 60 ICES 24 59 ICES 25 58 0.510 0.508 0.495 0.372 ICE0 22 60 ICE0 27 60 ICE0 24 60 ICE0 25 60 0.353 0.341 0.432 0.493 ICEF 22 60 ICEF 27 60 0.450 0.357 MMAS = 59.062- 0.044 FL20 18

MMAS = 61.695 - 0.042 FL20 19 MMAS = 50.939- 0.014 FL20 20 MMAS = 55.218- 0.027 FL20 21 MMAS = 22.869+ I I38 ICES 22 MMAS = 21.394+ 0.349 ICES 27 MMAS = 19.780+ 1.124 ICES 24 MMAS = 28.239+ 0.449 ICES 25 MMAS = 23.828+ 12.809ICE0 22 MMAS = 27.806+ 8.784 ICE0 27 MMAS = 14.040+ 17.484ICE0 24 MMAS = 16.237+ 15.481 ICE0 25 MMAS = 16.782+ 14.612 ICEF 22 MMAS = 26.381 + 10.892 ICEF 27 

### - Interlaboratory correlation of invitrodata

Lab a Lab b Lab c Lab d Lab e 1.000 0.894 0.922 0.924 0.955 1.000

0.896 0.867 0.90

### I 1.000

0.957 0.947 I.000

0.958 

### I.ooo 1.000 0.898 0.913 0.908 0.939 

### l.ooa

0.913 0.848 0.885 I.000

0.916 0.938 1.000 0.790 0.473 0.550 I.ooo

0.521 0.734 1.000

0.664 1.000

093x 

### I.ooo

I.000 I.000 0.174 -0.171 -0.103 

### I.000

-0.171 0.808 I.oOil

0.031 l.ooO 0.627 0.709 0.449 1.000

0.638 0.814 1.000

0.528 l.OOil
-o&3 * I.000 PO.316 I I.000

* I.OOil 0.841 0.490 0.373 

### I.ooo

0.513 0.424 1

.oOO 0.214 1.000 0.721 0.750 0.627 1.oOO

0.715 0.668 I.oOO

0.734 ,000

,000

*

,000

,000 1.000 0.700 0.759 0.752 I.oOO

0.716 0.679 1.000

0.732 I.ooo I.ooo 0.693 

### I.000ICEF 24 59 I 0.532 0.576 MMAS = 10.901 + 16.137 ICEF 24 ICEF 25 60 0 0.568 0.544 MMAS = 4.544 + 20.030 ICEF 25 ICEC 22 60 0 0.491 0.416 ICEC 27 60 0 0.490 0.449 ICEC 24 60 0 0.594 0.542 ICEC 25 60 0 0.599 0.552 MMAS = 18.576 + 0.294 ICEC 22 MMAS = 20.087 + 0.I81 ICEC 27 MMAS = 8.342 + 0.376 ICEC 24 MMAS = II.869 + 0.300 ICEC 25 IREA 26 60 0 0.461 0.439 IREA 23 60 0 0.443 0.364 IREA 28 60 0 0.407 0.316 IREA 29 60 0 0.502 0.510 IREB 26 60 0 0.498 0.467 IREB 23 60 0 0.485 0.451 IREB 28 60 0 0.568 0.544 IREB 29 60 0 0.606 0.606 IREC 26 58 2 0.247 0.166 IREC 23 60 0 0.420 0.289 IREC 28 58 2 0.410 0.515 IREC 29 60 0 0.528 0.512 IRED 26 58 2 0.447 0.364 IRED 23 60 0 0.542 0.435 IRED 28 58 2 0.485 0.582 IRED 29 60 0 0.61I 0.624 IRESUM 26 60 0 0.451 0.438 IRESUM 23 59 I 0.483 0.473 IRESUM 28 60 0 0.399 0.603 IREBUM 29 54 6 0.416 0.551 SM u) 38 SM 31 32 SM 32 35 SM 33 31 - 0.360 - 0.341

- 0.616 - 0.609

- 0.357 - 0.352

- 0.578 - 0.587 logNRU38 logNRU35 logNRU37 logNRU38 60
a 60 60 22

28 25 29 0 0 0 0

3 0 I 0 3 0 I 0 3 0 I 0 - 0.401 - 0.355

- 0.449 - 0.399

- 0.360 - 0.335

- 0.409 - 0.358 MMAS = 27.985 + 12.800 IREA 26 MMAS = 35.539 + 14.158 IREA 23 MMAS = 36.042 + 13.038 IREA 28 MMAS = 28.676 + 18.440 IREA 29 MMAS = 21.781 + Il.935 IREB 26 MMAS = 22.029 + 12.050 IREB 23 MMAS = 24.894 + 14.304 IREB 28 MMAS = 21.818 + 16.829 IREB 29 MMAS = 32.71I + 0.413 IREC 26 MMAS = 28.792 + 0.694 IREC 23 MMAS = 26.888 + 0.858 IREC 28 MMAS = 28.1IO+ 0.733 IREC 29 MMAS = 25.703 + 0.457 IRED 26 MMAS = 21.063 + 0.532 IRED 23 MMAS = 25.770 + 0.428 IRED 28 MMAS = 25.926 + 0.442 IRED 29 MMAS = 32.725 + O.OI6IRESUM 26 MMAS = 34.431 + 0.022IRESUM 23 MMAS = 37.621 + 0.02OIRESUM 28 MMAS = 38.701 + 0.026IRESUM 29 MMAS = 93.415 - 12.234 SM 30 MMAS = 139.832 - 22.643 SM 31 MMAS = 96.516 - 13.352 SM 32 MMAS = 130.366 - 20.081 SM 33 MMAS = 43.758 - 10.170 logNRU34 MMAS = 45.036 - II.806 logNRU35 MMAS = 43.377 - 8.925 logNRU37 MMAS = 44.662 - II.094 logNRU38 B. Chemicals soluble in wawr RBCDLI 27 RBCDL2 30 RBCDL3 29 RBCDL4 30 IogDLl 27 logDL2 30 logDL3 29 logDL4 30 RBCDM 1 27 RBCDMZ 30 RBCDM3 29 RBCDM4 30 - 0.391 - 0.223

- 0.353 - 0.281

- 0.332 -0.151

- 0.361 - 0.336

- 0.020 - 0.223

- 0.233 - 0.281 -0.136 -0.151

- 0.338 - 0.336 0.344 0.197 0.226 0.154 0.291 0.214 0.028 - 0.090 MMAS = 58.922 - 2.54E-04 RBCDLl MMAS = 56.316 - 2.22E-04 RBCDLZ MMAS = 55.1I8 - 2.OOE-04 RBCDL3 MMAS = 56.971 - 2.178-04 RBCDL4 MMAS = 53.876 - 2.317 IogDLl MMAS = 77.070 - 7.515 logDL2 MMAS = 56.077 - 2.777 logDL3 MMAS = 97.161 - 12.080 logDL4 MMAS = 38.063 + 0.433 RBCDMI MMAS = 40.181 + 0.205 RBCDMZ MMAS = 40.382 + 0.324 RBCDM3 MMAS = 44.585 + 0.023 RBCDM4 0.768 0.525 1.000 0.719 0.654 0.690 1.000 0.829 0.849 0.844 1.000

0.759 0.801 I.oOO

0.853 1.000 0.441 0.585 0.619 1.000

0.695 0.587 1.000

0.677 1.000 0.728 0.714 0.688 1.000

0.688 0.617 I,000

0.808 l.OW 0.524 0.485 0.625 1.000

0.414 0.68I I.000

0.819 1.000 0.623 0.707 0.813 1.000

0.618 1.000

0.882 1.000 0.502 0.574 0.689 1.ooo

0.834 0.709 1.000

0.798 l.M)o 0.948 0.563 0.923 l.Oc@

0.690 0.980 1.000

0.634 1.000 0.959 0.969 0.940 1.000

0.946 0.935 1.000

0.945

I.00 0.915 0.836 0.738 1.000

0.922 0.839 1.000

0.816 1.000 0.821 0.736 0.592 1.000

0.697 0.590 1.000

0.775 1.000 0.804 0.756 0.578 1.000

0.827 0.489 l.ooo

0.728 I

### .ooo

1.000

1.000

1.000

l.ooO

1.000

1.000

1.000

1.000

1.000

I.000

1.000 [mud]

# E

In vitrotesting b vim 0. in vitrocorrelation Interlaboratory correlation of in vitrodata

No. of No. of Spearman’s Ahnative SampIeS SamplcS Pearson’s rank method tested not tested correlation correlation index invirro invitro wetiicicnt cocllicient Linear regression equation Lab Laba Labb Lab c Lab d Lab e IogDM 1 27 3 0.297 0.197 logDM2 30 0 0.186 0.154 logDM3 29 I 0.284 0.214 logDM4 30 0 0.020 - 0.090 RBCHI 27 3 - 0.443 - 0.329 RBCHZ 30 0 - 0.388 - 0.322 RBCH3 29 I - 0.255 -0.154 RBCH4 30 0 - 0.401 - 0.430 IogH

### I 27 3 - 0.226 - 0.329 logH2 30 0 - 0.310 - 0.322 logH3 29 I - 0.092 - 0.154 logH4 30 0 - 0.445 - 0.430 EYTEX 5 26 4 0.225 0.219 EYTEX 6 24 6 0.161 0.177 EYTEX 7 29 I 0.125 0.241 EYTEX 8 25 5 0.037 0.101 BCOPP9 BCOPPIO BCoPPl I BCOPPIZ BCOPP13 30 30 30 30 30 0.200 0.188 0.086 0.198 0.228 0.228 0.244 0.250 0.381 0.327 BCOP09 BCOPOIO BCOPOI 

### I BCOPol2 BCOPOI 3 30 30 30 30 30 0.580 0.351 0.614 0.473 0.614 0.376 0.651 0.43I 0.561 0.320 BCOP19 BCOPIIO BCOPI 1I BCOPI 12 BCOPII3 30 30 30 30 30 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 13 7 12 0.558 0.388

0.477 0.326 0.582 0.368 0.625 0.448 0.575 0.396 BCOPI9b BCOPIlOb BCOPII 1

b BCOPIIZb BCOPII3b 30 30 30 30 30 0.482 0.388 0.446 0.326 0.523 0.368 0.531 0.448 0.554 0.395 HETQ14 25 HETQ15 17 HETQ16 23 HETQI7 18 0.314 0.327 0.380 0.326 0.598 0.517 0.758 0.681 MMAS = 38.538+ 

### 1 I.509 IogDM 1 MMAS = 40.176 + 6.291 logDM2 MMAS = 39.859+ 10.593 logDM3 MMAS = 44.720+ 0.654 logDM4 MMAS = 58.413- 3.028-04 RBCHI MMAS = 56.657- 2.928-04 RBCHZ MMAS = 52.563- 1.66E-04 RBCH3 MMAS = 55.291 - 2.61E-04 RBCH4 MMAS = 73.725 - 7.105 logHI MMAS = 86.275 - 9.945 logH2 MMAS = 53.878- 2.184 logH3 MMAS = 106.656- 15.139 logH4 MMAS = 28.178+ 0.484 EYTEX 5 MMAS = 36.002+ 0.283 EYTEX 6 MMAS = 36.985+ 0.254 EYTEX 7 MMAS = 41.I57+ 0.070 EYTEX 8 MMAS = 39.694+ 2.652 BCOPP9 MMAS ~43.157 + 1.030 BCOPPlO MMAS = 38.655+ 3.278 BCOPPll MMAS = 38.179+ 3.817 BCOPP12 MMAS = 34.672+ 8.377 BCOPP13 MMAS = 31.123+0.276 BCOP09 MMAS = 29.565+ 0.382 BCOPOIO MMAS = 32.196+ 0.301 BCOPOI I MMAS = 29.024+ 0.259 BCOPOIZ MMAS = 31.321 + 0.310 BCOPO13 MMAS = 27.607+ 0.215 BCOP19 MMAS = 30.780+ 0.208 BCOPIIO MMAS = 28.646+ 0.227 BCOPII I MMAS = 26.463+ 0.209 BCOPIIZ MMAS = 28.727+ 0.259 BCOPI13 MMAS = 27.943+ 0.226 BCOPI9b MMAS= 31.191+0.207 BCOPIlOb MMAS = 28.189+ 0.252 BCOPII lb MMAS = 25.439+ 0.246 BCOPIIZb MMAS = 28.539+ 0.270 BCOPI 13b MMAS = 34.226+ 1.371 HETQ14 MMAS = 24.989+ 3.201 HETQl5 MMAS = 30.640+ 3.150 HETQ16 MMAS = 2.232+ 7.294 HETQI7 1.ooo 0.738 0.733 0.507 1.000 0.936 0.695 0.944 I.ooo 0.871 0.763 0.760 1.000 0.799 0.925 0.865 1.000 0.733 0.864 0.760 0.880 1.000 0.945 0.971 0.962 0.959 1.000 0.906 0.952 0.929 0.950 1.000 0.888 0.936 0.892 0.930 1.000 0.711 0.355 0.456 1.ooo

0.708 0.349

I.oOO 0.713 0.920

1.000 0.744 0.768

1.000 0.757 0.871

1.000 0.818 0.521 0.666

1.000 0.932 0.927 0.938

1.000 0.936 0.855 0.864

I.000 0.938 0.823 0.850

1.000 0.387 0.760 1.000

0.619

1.000 0.785

1.000 0.67I

1.000 0.869

1.oOO 0.807 0.870

I.OOO 0.964 0.946

1.000 0.944 0.949

I.ooo 0.916 0.952

I.000 0.679 l.ooo

l.ooo

1.000

I.000

l.ooo 0.840 1.000

I.ooo 0.928 1.000

1.000 0.948 I.000

I.oOO 0.926 1.000

1.000HBTS14 5 25 l.* l** HETslS 9 21 0.309 0.357 HETSdl5 I 23 0.137 0.082 HBTSl7 II I9 0.137 0.131 HETQl4b HETQl5b HETQlLb HETQI7b 25 I7 23 I8 FL20 18 29 FL20 I9 30 FL20 20 30 FLU, 21 30 ICES 22 30 ICES 27 30 ICES 24 29 ICES 25 29 ICE0 22 ICE0 27 ICE0 24 ICE0 25 30 30 30 30 ICEF 22 30 ICEF 27 30 ICEF 24 29 ICEF 25 30 ICEC 22 ICEC 27 ICEC 24 ICEC 25 30 30 30 30 IREA 26 IREA 23 IREA 28 IREA 29 30 30 30 30 IREB 26 IREB 23 IREB 28 IREB 29 30 30 30 30 IREC 26 29 IREC 23 30 IREC 28 2s IREC 29 30 IRED 26 29 IRED 23 30 IRED 28 28 IRED 29 30 5 I3 7 I2 I 0 0 0 0 0 I I 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 I 0 2 0 I 0 2 0 0.3% 0.366

0.185 0.309 0.451 0.480 0.364 0.384

- 0.380 - 0.334

- 0.513 - 0.512

- 0.354 - 0.420

- 0.343 - 0.383 0.417 0.397 0.572 0.509 0.438 0.294 0.507 0.315 0.478 0.311 0.379 0.362 0.508 0.3% 0.501 0.401 0.380 0.377 0.408 0.373 0.384 0.453 0.329 0.291 0.451 0.334 0.523 0.450 0.520 0.429 0.558 0.386 0.470 0.377 0.438 0.259 0.514 0.238 0.422 0.308 0.379 0.304 MMAS = 29.813 + 8.207 IREB 26 0.341 0.226 MMAS = 31.548 + 7.688 IREB 23 0.516 0.426 MMAS = 30.358 + Il.276 IREB 28 0.514 0.440 MMAS = 30.019 + 12.374 IREB 29 0.305 0.162 0.492 0.253 0.246 0.253 0.429 0.233 0.405 0.307 0.552 0.365 0.329 0.293 0.528 0.511 

### *** MMAS = 29.2% + 1.098 HETSIS IUMAS = 42.749 + 0.989 HETS16 MMAS = 45.942 + 0.603 HETSI7 MMAS = 17.411 + 15.294 HETA14b MMAS = 17.337 + 14.415 HETQISb MMAS = 1.690 + 26.615 HETQl6b MMAS = - 71.906 + 59.035 HETQl7b MMAS = 57.493 - 0.033 FL20 18 MMAS = 64.096 - 0.041 FL20 19 MMAS = 63.736 - 0.035 FL20 20 MMAS = 57.514 - 0.024 FL20 21 MMAS = 30.327 + 0.849 ICES 22 MMAS = 24.341+ 0.299 ICES 27 MMAS = 26.559 + 0.753 ICES 24 MMAS = 30.692 + 0.406 ICES 25 MMAS = 26.348 + II.975 ICE0 22 MMAS = 28.193 + 9.230 ICE0 27 MMAS = 14.906 + 16.836 ICE0 24 MMAS = 22.642 + 12.893 ICE0 25 MMAS = 26.565 + 1I.I95 ICEF 22 MMAS = 29.592 + 10.479 ICEF 21 MMAS = 23.797 + IO.198 ICEF 24 MMAS = 23.281 + II.040 ICEF 25 MMAS = 25.236 + 0.242 ICEC 22 MMAS = 23.514 + 0.159 ICEC 21 MMAS = 16.500 + 0.294 ICEC 24 MMAS = 19.442 + 0.240 ICEC 25 MMAS = 31.303 + Il.526 IREA 26 MMAS = 36.917 + 12.481 IREA 23 MMAS = 36.212 + 13.346 IREA 28 MMAS = 34.001 + 12.532 IREA 29

MMAS = 35.016 + 0.380 IREC 26 MMAS = 32.589 + 0.585 IREC 23 MMAS = 33.443 + 0.379 IREC 28 MMAS = 34.822 + 0.463 IREC 29 MMAS = 31.031 + 0.322 IRED 26 MMAS = 26.628 + 0.437 IRED 23 MMAS = 31.923 + 0.232 IRED 28 MMAS = 31.973 + 0.326 IRED 29 1.000 0.727 0.645 0.927 1.000 0.822 0.495 0.375 1.000 0.808 0.722 0.691 1.000 0.775 0.775 0.847 1.000 0.803 0.846 0.676 1.cmO 0.892 0.881 0.881 1.000 0.503 0.624 0.608 1.000 0.754 0.699 0.690 1.000 0.606 0.655 0.117 I.ooo 0.663 0.799 0.855 1.ooo

0.949 0.831

1.000 0.594 0.470

1.000 0.597 0.526

1.000 0.789 0.795

1.000 0.821 0.812

l.ooO 0.692 0.727

1.000 0.860 0.896

1.000 0.814 0.706

1.000 0.746 0.674

1.000 0.439 0.733

1.000 0.598 0.747 1.ooo

0.420

1.000 0.535

1.000 0.344

1.Ocn-l 0.789

1.000 0.771

1.000 0.704

1.000 0.858

1.000 0.701

1.oOo 0.912

1.oo 0.855

1.000 0.939 1.000

l.OCUl

1.000

1.000

1.000

1.000

1.000

1.000

I.ooa

1.000

1.000 [conrd]Table kontd
In vitrotesting In Vito 0. in vitro correlation Interlaboratory correlation of in uitro data

No. of No. of Speamm’s Alternative samples samples PeatWo’s rank method tested not tested correlation con-elation index in vitro in vitro coefficient coefficient Linear regression equation Lab Laba Lab b Lab c Lab d Labe IRESUM 26 30 IRESUM 23 29 IRESUM 28 30 IRESUM 29 2s SM 30 22 SM 31 19 SM 32 20 SM 33 17 log NRU34 30 log NRU3S 30 log NRU37 30 log NRU38 30 C. Chemicals ittsoluble in water RBCDLI 17 RBCDLZ 18 RBCDW 17 RBCDL4 17 log DLl 17 log DL2 18 log DL3 17 log DLA 17 RBCDMI 17 RBCDMZ 18 RBCDM3 17 RBCDM4 18 log DM 1 17 log DM2 18 log DM3 17 log DM4 18 RBCHI 17 RBCHZ I8 RBCH3 17 RBCH4 17 logHI 17 log H2 18 log H3 17 log H4 17 EYTEX S 16 EYTEX 6 16 EYTEX 7 18 EYTEX 8 18 8 II IO 13 0 0 0 0

I 0 I I
I 0 I I
I 0 I 0
1 0 1 0 I 0 1 I I 0 I I 2 2 0 0 0.471 0.34s MMAS = 34.720 + 0.015 IRESUM 26

0.515 0.311 MMAS = 36.818 + 0.020 IRESUM 23 0.560 0.410 MMAS = 37.393 + 0.023 IRESUM 28 0.530 0.426 MMAS = 39.355 + 0.024 IRESUM 29

- 0.357 - 0.346 MMAS = 96.463 - 12.074 SM 30

- 0.591 - 0.451 MMAS = 148.542 ~ 23.757 SM 31

- 0.328 - 0.231 MMAS = 84.252 - 9.925 SM 32

- 0.577 - 0.413 MMAS = 152.142 - 23.601 SM 33

- 0.298 -0.312 MMAS = 46.753 - 5.945 log NRU34

- 0.376 - 0.384 MMAS = 48.541 - 8.459 log NRU35

- 0.283 - 0.337 MMAS = 46.931 - 5.774 log NRU37

- 0.374 - 0.363 MMAS = 48.896 - 8.649 log NRU38

0.102 - 0.046 0.046 0.173 0.141 0.230 -0.018 0.073

- O.OSl - 0.046 0.196 0.173 0.234 0.230 0.051 0.073

- 0.050 - 0.031 0.306 0.330 0.071 0.248

l** l**

- 0.050 - 0.031 0.277 0.330 0.201 0.248 *** *** 0.100 -0.062

- 0.003 0.069

- 0.001 0.053

- 0.017 0.181

- 0.053 - 0.062 0.058 0.069

- 0.063 0.053 0.078 0.181 0.604 0.630 0.699 0.679 0.748 0.798 0.570 0.650 MMAS = 33.790 + 9.138-05 RBCDLI MMAS = 33.848 + 4.768-05 RBCDLZ MMAS = 34.227 + 1.08E-04 RBCDL3 MMAS = 31.641 - 1.748-05 RBCDL4 MMAS = 39.972 - 1.533 log DLI MMAS = II.259 + 6.964 log DL2 MMAS = 15.454 + 6.304 log DL3 MMAS = 25.027 + 1.963 log DL4 MMAS = 35.244 - 0.076 RBCDM I MMAS = 28.955 + 0.198 RBCDMZ MMAS = 35.230 + 0.076 RBCDM3

l** MMAS = 35.244 - 2.846 log DMdl MMAS = 29.063 + 7.551 log DM2 MMAS = 34.003 + 9.103 log DM3

*** MMAS = 33.840 + 8.9OE-OS RBCHI MMAS = 34.348 - 3.34E-06 RBCHZ MMAS = 35.744 - I.47E-06 RBCH3 MMAS = 31.631 - 1.638-05 RBCH4 MMAS=40.190-1.613 logHI MMAS = 27.824 + 2.019 log H2 MMAS = 39.752 - 1.348 log H3 MMAS = 22.048 + 2.894 log H4 MMAS= -4.270+ I.103 EYTEX 5 MMAS = - 19.016 + 1.345 EYTEX 6 MMAS = - 8.947 + 1.180 EYTEX 7 MMAS = - 2.281 + I.013 EYTEX 8 l.ooo 0.568 0.595 0.835 1.000 0.901 0.427 0.875 1.000 0.969 0.984 0.939

1.000 0.959 0.986 0.828 1.000 0.775 0.654 0.609 1.000 0.402

- 0.078 I 1.000 0.375

- 0.095 * 1.000 0.905 0.910 0.829 1.000 0.824 0.421 0.643 1.000 0.791 0.889 0.991 I

### .ooo

0.955 0.749

1.000 0.549 0.986

1.000 0.964 0.930

1.000 0.903 0.948

1.000 0.797 0.731

1.000 0.472 *

I.000 0.526 *

I.oOO 0.997 0.983

1.000 0.649 0.772

I.,OOo 0.826 0.731 1.000

0.799

I.000 0.507

1.000 0.932

1.000 0.734

I.000 0.679

I.oOO *

1.000 *

I.oOO 0.974

1.000 0.613

1.000 0.870 I

### .ooo

l.ooo

I.000

l.olM

I.ooo

l

*

1.000

1.000

l.oooBCOPP9 I8 0 0.167 0.152 BCOPPIO I8 0 0.207 0.005 BCOPPI I I8 0 0.250 0.104 BCOPPIZ I8 0 0.153 0.212 BCoPP13 I8 0 0.236 0.123 MMAS = 30.592+ 3.469 BCOPP9 MMAS = 29.854+ 3.181 BCOPPIO MMAS = 29.205+ 4.201 BCOPPI I MMAS = 31.475+ 3.638 BCOPPIZ MMAS = 28.929+ 7.328 BCOPP13 BCOP09 I8 0 0.277 0.659 MMAS = 9.384+ 0.085 BCOP09 BCOPQIO I8 0 0.180 0.742 MMAS = 31.666+0.042 BCOPQIO BCOPOI I I8 0 0.135 0.706 MMAS = 32.648+ 0.035 BCOPOl I BCoPo12 I8 0 0.138 0.623 MMAS = 32.424 + 0.031 BCOPOl2 BCoPo13 I8 0 0.213 0.729 MMAS=31.190+0.070 BCOPO13 BCOPB I8 0 0.336 0.614 BCOPIIO I8 0 0.240 0.581 BCOPIII I8 0 0.198 0.690 BCoPIl2 I8 0 0.160 0.657 BCOPI13 I8 0 0.257 0.635 MMAS = 26.159+ 0.IIOBCOP19 MMAS = 29.334+ 0.059 BCOPIIO MMAS = 30.838+ 0.052 BCOPII I MMAS = 31.650+ 0.037 BCOPIIZ MMAS = 29.478+ 0.087 BCOPII 3 BCOPI9b I8 0 0.446 0.614 BCOPIlOb 18 0 0.430 0.582 BCOPIllb I8 0 0.416 0.690 BCOPII2b I8 0 0.359 0.657 BCOPII3b 18 0 0.372 0.635 MMAS = 21.560+0.187 BCOPI9b MMAS = 22.048+ 0.178 BCOPIlOb MMAS = 23.091 + 0.206 BCOPII Ib MMAS=25.192+0.160 BCOPll2b MMAS = 25.791 +0.171 BCOP113b HETQ14 I2 6 0.445 0.688 HETQl5 II 7 0.341 0.426 HETQ16 I2 6 0.232 0.41I HETQ17 II 7 0.242 0.345 HETS14 6 12 0.472 0.613 HETSIS 4 I4 - 0.922 - 0.971 HETS16 6 I2 0.716 0.738 HETSI7 6 I2 -0.111 - 0.353 HETQI4b I2 6 0.541 0.651 HETQlSb II 7 0.609 0.615 HETQl6b I2 6 0.41I 0.396 HETQI7b II 7 0.370 0.441 MMAS = 18.634+ 2.728 HETQ14 MMAS = 20.228+ 2.633 HETQI5 MMAS = 25.651 + 1.928HETQ16 MMAS = 23.326+ 1.591 HETQ17 MMAS = 35.935 + 4.524 HETS14 MMAS = 64.010- 1.831 HETSIS MMAS = 27.481 + 5.715 HETS16 MMAS = 45.785 - 0.461 HETS17 MMAS = - 1.402+ 19.074 HETOl4b MMAS = - 9.337+ 26.126 HETGI 5b MMAS = 7.441+ 15.821 HETQI6b MMAS = - 32.097+ 33.340 HETQl7b FL20 I8 FL20 I9 FL20 20 FL20 21 I8 I8 18 17 0

0 0 I 0 0 0 I 0 0 0 0 - 0.613 - 0.593

- 0.41I - 0.471

- 0.130 -0.199

- 0.212 - 0.247 ICES 22 ICES 27 ICES 24 ICES 25 I8 I8 I8 I7 0.560 0.515 0.751 0.680 0.655 0.501 0.539 0.604 ICE0 22 18 ICE0 27 I8 ICE0 24 18 ICE0 25 18 0.583 0.521 0.353 0.255 0.501 0.441 0.584 0.549 MMAS = 50.08I- 0.036 FL20 I8 MMAS = 47.WO- 0.025 FL20 I9 MMAS = 40.I52- 0.009 FL20 20 MMAS = 38.261 - 0.012 FL20 21 MMAS = 16.149+ 0.977 ICES 22 MMAS = 2.279+ 0.522 ICES 27 MMAS = 14.047+ 1.130ICES 24 MMAS = 15.847+ 0.528 ICES 25 MMAS = 9.755+ 14.739ICE0 22 MMAS = 17.117+ 8.346 ICE0 27 MMAS = 8.325+ 15.422 ICE0 24 MMAS = 8.157+ 15.289ICE0 25 l.Oiw 0.915 0.932 0.785 0.901 I.ooo 0.959 0.913 0.942 0.982 1.000 0.946 0.898 0.937 0.981 1.000 0.943 0.864 0.949 0.971 1.000 0.944 0.809 0.621 1.000 0.096 -0.159

- 0.288 1.000 0.692 0.816 0.626 1.000 0.778 0.609 0.350 l.Om 0.671 0.757 0.514 1.000 0.498 0.704 0.786 l.ooo

0.893 0.688 0.889

1.000 0.896 0.928 0.972

1.000 0.879 0.915 0.964

1.000 0.877 0.916 0.954

1.000 0.745 0.580

1.000 0.910 0.852

1.000 0.642 0.830

1.000 0.675 0.167

I.OOO 0.599 0.210

1.000 0.414 0.442 1.000

0.894 0.963

l.ooo 0.991 0.961

1.000 0.980 0.947

1.000 0.923 0.905

1.000 0.782

1.oOo 0.094

l.Ocm 0.562

1.000 0.386

I.oOo 0.732

1.000 0.851 l.ooo

0.922

1.000 0.978

1.000 0.978

1.000 0.968 l.OOa

1.000Table 4-conrd In viva0.invitrocorrelation Interlaboratory correlation of inuitrodata

Alternative method No. of No. of Spearman’s

samples samples Pearson’s rank tested not tested comlation correlation index invitro invitro coetlicient coei%cient Linear regression equation Lab Laba Lab b Labc Labd Labe ICEF 22 18 0 0.566 0.586 ICEF 27 18 0 0.233 0.197 ICEF 24 18 0 0.732 0.712 ICEF 25 18 0 0.779 0.736 ICEC 22 18 0 0.618 0.580 ICEC 21 18 0 0.603 0.510 ICEC 24 18 0 0.671 0.565 ICEC 25 18 0 0.748 0.664 IREA 26 18 0 0.475 0.480 IRBA 23 I8 0 0.104 0.117 IREA 28 18 0 0.407 0.434 IREA 29 18 0 0.706 0.770 IRE9 26 18 0 0.549 0.463 IRE9 23 18 0 0.422 0.346 IREB 28 18 0 0.677 0.599 IRE9 29 18 6 0.730 0.795 IREC 26 17 I 0.177 0.159 IREC 23 I8 0 0.243 0.223 IREC 28 18 0 0.661 0.629 IREC 29 I8 0 0.762 0.692 IRED 26 I7 I 0.501 0.434 IRED 23 I8 0 0.342 0.381 IRED 28 I8 0 0.738 0.620 IRED 29 18 0 0.763 0.656 IRESUM 26 I8 0 0.502 0.458 IRESUM 23 I8 0 0.156 0.467 IRESUM 28 I8 0 0.312 0.626 IRESUM 29 I8 0 0.315 0.625 SM 30 5 I3 0.434 0.141 SM 31 2 I6 - l.ooo - l.Olxl SM 32 4 I4 0.662 0.541 SM 33 2 I6 - 1.000 - l.Olxl IoaNRU34 18 IoaNRU35 18 IoaNRU37 18 logNRU38 18 - 0.398 - 0.181

- 0.336 - 0.127 -0.187 - 0.077 -0.177 - 0.059 D. Surfactants RBCDLI RBCDLZ RBCDL3 RBCDL4 12 12 12 I2 - 0.509 - 0.563 MMAS = 75.917 - 4.20E-04 RBCLI

- 0.664 - 0.672 MMAS = 77.594 - 0.001 RBCDL2

- 0.422 - 0.322 MMAS = 64.706 - 3.338-04 RBCDL3

- 0.657 - 0.676 MMAS = 79.068 - 0.001 RBCDL4 MMAS = - 0.588 + 16.982 ICEF 22 MMAS = 23.787 + 5.869 ICEF 27 MMAS = 1.724 + 18.433 ICEF 24 MMAS = 9.534 + 23.353 ICEF 25 MMAS = 3.543 + 0.331 ICEC 22 MMAS = 2.1I7 + 0.233 ICEC 27 MMAS = 3.824 + 0.351 ICEC 24 MMAS = - 0.117 + 0.327 ICEC 25 MMAS = 21.557 + 10.785 IREA 26 MMAS = 33.710 + 3.653 IREA 23 MMAS = 28.448 + Il.741 IREA 28 MMAS = 13.609 + 27.290 IREA 29 MMAS = 16.675 + II.507 IREB 26 MMAS = 20.533 + 8.991 IREB 23 MMAS = 15.088 + 14.985 IRB 28 MMAS = II ,978 + 18.696 IRE9 29 MMAS = 26.552 + 0.279 IREC 26 MMAS = 24.025 + 0.629 IREC 23 MMAS = 16.758 + 1.520 IREC 28 MMAS = 12.631 + 1.525 IREC 29 MMAS = 17.393 + 0.502 IRED 26 MMAS = 19.025 + 0.454 IRED 23 MMAS = 14.454 + 0.693 IRED 28 MMAS = 17.213 + 0.555 IRED 29 MMAS = 25.763 + 0.014 IRESUM 26 MMAS = 32.596 + 0.008 IRESUM 23 MMAS = 31.042 + 0.014 IRESUM 28 MMAS = 30.601 + 0.029 IRESUM 29 MMAS = 3.676 + 8.1I4 SM 30 MMAS = 253.548 - 43.370 SM 31 MMAS = - 79.463 + 32.957 SM 32 MMAS = 267.224 - 45.994 SM 33 MMAS = 35.506 - 12.853 logNRU34 MMAS = 36.367 - 8.963 logNRU35 MMAS = 34.368 - 5.31I loaNRU37 MMAS = 34.858 - 5.412 loaNRU38 

### _1.ooo 0.433 0.847 0.745 1.000 0.705 0.844 0.763 1.000 0.413 0.599 0.656 l.OfXl 0.629 0.683 0.607 1.000 0.169 0.276 0.210 1.000 0.490 0.704 0.790 1.000 0.481 0.555 0.628 l.ooO 1.000 1.000 1.000 I.@30 0.935 0.887 0.928

1.000 0.854 0.712 0.845 1.ooo

0.371 0.517

1.000 0.569 0.595

1.000 0.722 0.480

1.000 0.552 0.409

1.000 0.456 0.392

1.000 0.689 0.615

I.oOO 0.861 0.964

I.oOO 1.000 I.oOO

1.000 0.853 0.909

1.000 0.828 0.998 1.ooo

0.763

1.000 0.905

I.oOo 0.634

1.000 0.575

I.oOO 0.748

1.oOO 0.874

1.000 0.896

I.oOo I.OOo

l.OlXl 0.941

1.000 0.828 1.ooo

1.000

I.OOO

I.oOO

1.000

1.000

1.000

1.000

,000



### .oooIOgDLl logDL2 logDL3 lOgDL4 RBCDM I RBCDMZ RBCDM3 RBCDM4 logDM 1 logDIU2 logDM3 logDM4 RBCHl RBCI-IZ RBCH3 RBCH4 logH1 lo&I2 logH3 logH4

EYTEX 5 EYTEX 6 EYTBX 7 EYTEX 8 BCOPP9 BCOPPIO BCOPPI I BCOPPl2 BCOPPI 3 BCOP09 BCOPOIO BCOPOII BCOFol2 BCoPo13 BCOP19 BCOPIIO BCOPII 1 BCOPIIZ BCOPIl3 BCOP19b BCOPIlOb BCOPIl lb BCOPIlZb BCOPII 3b 12 12 12 12 12 12 12 12 I2 12 12 12 12 12 12 12 12 12 12 12

7 9 10 8 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
5 3 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 

### - 0.509 - 0.563

- 0.647 - 0.672

- 0.226 - 0.322

- 0.657 - 0.676 0.784 0.827 0.737 0.752 0.789 0.790 0.813 0.830 0.693 0.827 0.577 0.752 0.697 0.790 0.716 0.830

- 0.612 - 0.897

- 0.562 - 0.930

- 0.596 - 0.904

- 0.611 - 0.953

- 0.879

- 0.873

- 0.836

- 0.894 - 0.897

- 0.930

- 0.904

- 0.953
0.543 0.465 0.346 0.186 0.539 0.534 0.533 0.628 0.642 0.566 0.728 0.615 0.718 0.531 0.837 0.769 0.835 0.797 0.663 0.678 0.789 0.853 0.758 0.846 0.706 0.715 0.762 0.810 0.772 0.713 0.861 0.685 0.859 0.790 0.876 0.825 0.895 0.818 0.772 0.713 0.861 0.685 0.859 0.790 0.876 0.825 0.895 0.818 MIUAS = 222.899 - 37.795 logDL1 MMAS = 187.564 - 31.821 logDL2 MMAS = 72.647 - 5.955 logDL3 MMAS = 266.143 -48.105 logDL4 MMAS= 17.569+ 1.151 RBCDMI MMAS = 17.897 + 0.872 RBCDMZ MMAS= 17.967 + 1.133 RBCDh43 MMAS= 17.875 + 1.132 RBCDM4 MMAS = 19.779 + 30.562 1ogDMl MMAS = 20.371 + 25.751 logDM2 MMAS = 19.637 + 30.754 logDM3 MMAS = 18.953 + 31.614 logDM4 MMAS = 60.581- 0.001 RBCHl MMAS = 58.647 - 0.001 RBCH2 MMAS = 60.020 - 0.001 RBCH3 MMAS = 60.462 - 0.001 RBCH4 MMAS = 151.533 - 32.322 logHI MMAS = 146.781 - 32.314 logH2 MMAS = 148.156- 31.628 logH3 MMAS = 148.335 - 31.922 logH4
MMAS = - 4.891 + 1.564 EYTEX 5 MMAS = 15.797 + 1.049 EYTEX 6 MMAS = - 0.530 + 1.478 EYTEX 7 MMAS = - I.653 + 1.634 EYTEX 8 MMAS = 16.884 + 13.200 BCOPP9 MMAS = 10.503 + 11.264 BCOPPIO MMAS = 6.526 + 14.373 BCOPPI 1 MMAS = 3.748 + 16.928 BCOPPl2 MMAS = 0.105 + 24.116 BCOPP13 MMAS = 28.041+ 0.864 BCOP09 MMAS = 23.986 + 1.122 BCOPOIO MMAS = 27.164 + 1.325 PCOPOI l MMAS = 2$.656+ 1.169 BCOPOIZ MMAS = 24.321 + 1.143 BCOPO13 MMAS = Il.685 + 0.610 BCOPI9 MMAS = 5.582 + 0.587 BCOPIIO MMAS = 2.572 + 0.759 BCOPIl 

### I MMAS = 6.448 + 0.742 BCOPIIZ MMAS = 4.630 + 0.850 BCOPIl3 MMAS = 11.685 + 0.610 BCOPI9b MMAS = 5.582 + 0.587 BCOPIlOb MMAS = 2.572 + 0.759 BCOPII lb MMAS = 6.448 + 0.742 BCOPIl2b MMAS = 4.630 + 0.850 BCOPIl3b 1.000 0.832 0.643 0.845 1.000 0.962 0.997 0.991 l.wO 0.906 l.Om 0.998 1.000 0.737 0.999 1.000 1.000 0.949 0.985 0.997
l.Ocm 0.716 0.972 0.927 1.000 0.835 0.932 0.843 0.766 1.000 0.957 0.971 0.947 0.967 1.000 0.914 0.951 0.915 0.915 1.000 0.914 0.951 0.915 0.915 1.000

0.632 0.894

1.000 0.956 0.966

1.000 0.906 0.907

l.000 0.729 0.737

1.000 0.904 0.947

1.000 0.610 0.923

l.Ocm 0.912 0.966 0.924

1.000 0.981 0.972 0.995

1.000 0.952 0.989 0.959

l.Ow 0.952 0.989 0.959 1.000

0.617

l.ooO 0.992

l.Ofxl 0.998

1.000 0.999

l.ooo 0.985

1.000 0.930

1.000 0.922 0.921

1.000 0.957 0.985

1.000 0.936 0.947

1.000 0.936 0.947 1.000

1.000

1.oOO

1.000

l.ooO

1.000

l.ooo 0.958 l.Om

1.000 0.973 1.000

1.000 0.966 1.000

1.000 0.966 l.Ocm [conrd]Table bontd In vitro testing In viva 0. invitrocorrelation Interlaboratory correlation of in vitro data

No. of No. of Spearman’s Alternative SampIeS samples Pearson’s rank method tested not tested correlation correlation index invitro invitro cc&icient coefficient Linear regression equation Lab Lab a Lab b Lab c Lab d Lab e MMAS = 3.558 + 14.740 HETQ14 MMAS = 13.625 + 13.908 HETQIS HETQ14 HBTQl5 HETQl6 HETQI7 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.688

0.742 0.448 0.847 0.643

0.776 0.596 0.839 HETQ14b HETQl Sb HETQ16b HETQ16b 0.476 0.570 0.774 0.780 0.622 0.619 0.701 0.753 FL20 18 FL20 19 FL20 20 FL24l21 - 0.745 - 0.671

- 0.769 - 0.634 0.099 0.081

- 0.586 - 0.434 ICES 22 ICES 27 ICES 24 ICES 25 0.851 0.841 0.676 0.762 0.889 1.811 0.428 0.350 MMAS = 18.981 + 18.142 HETCj16 MMAS = - 0.033 + 15.659 HETQl7 MMAS = - 21.392 + 38.797 HETQ14b MMAS = - 12.443 + 40.443 HETQI5b MMAS = - 23.624 + 50.840 HETQ16b MMAS = - 17.076 + 40.330 HETQ17b MMAS = 68.875 - 0.070 FL20 18 MMAS = 69.287 - 0.064 FL20 19 MMAS = 42.385 + 0.010 FL20 20 MMAS = 69.808 - 0.058 FL20 21 MMAS = 9.026 + 2.551 ICES 22 MMAS = - 6.095 + I.363 ICES 27 MMAS = 5.439 + 2.692 ICES 24 MMAS = 30.031 + 0.889 ICES 25 MMAS = 25.81 I + 24.472 ICE0 22 MMAS = 26.171 + 27.920 ICE0 27 MMAS = 2.807 + 38.784 ICE0 24 MMAS = 8.167 + 25.282 ICE0 25 MMAS = - 7.856 + 34.865 ICEF 22 MMAS = 7.354 + 37.895 ICEF 27 MMAS = - 18.941 + 31.449 ICEF 24 MMAS = - 16.600 + 37.161 ICEF 25 MMAS = 9.143 + 0.606 ICEC 22 MMAS = - I.395 + 0.638 ICEC 27 MMAS = - 19.331 + 0.818 ICEC 24 MMAS = - 5.939 + 0.614 ICEC 25 MMAS = 23.213 + 26.458 IREA 26 MMAS = 33.667 + 24.005 IREA 23 MMAS = 40.836 + 53.010 IREA 28 MMAS = 23.614 + 55.245 IREA 29 MMAS = 8.758 + 22.316 IREB 26 MMAS = - 4.376 f 28.571 IREB 23 MMAS = 19.706 + 28.538 IREB 28 MMAS = 9.146 + 29.472 IREB 29 MMAS = 29.574 + 0.963 IREC 26 MMAS = - 9.127 + 2.602 IREC 23 MMAS = 10.553 + 2.447 IREC 28 MMAS = 15.834 + 1.461 IREC 29 1.ooo 0.793 0.438 0.816 1

### .ooo

0.779 0.876 l.ooo

0.579 I.wO 0.581 0.670 0.420 1.000

0.768 0.966 1.000

0.721 1.000

1.000 1.000 0.957 0.402 0.358 1.000

0.359 0.516 I.oOo

0.126 1.000 0.741 0.920 0.641 1.000

0.696 0.392 I.OOO

0.543 .OOO

,000 ICE0 22 ICE0 27 ICE0 24 ICE0 25 0.601 0.526 0.730 0.808 0.727 0.792 0.63I 0.677 l.ooo 0.618 0.719 0.438 1.000

0.759 0.834 1.000

0.483 1.000 ICEF 22 ICEF 27 ICEF 24 ICEF 25 0.758 0.693 0.838 0.823 0.638 0.640 0.879 0.873 1.000 0.663 0.636 0.950 1.000

0.546 0.748 I.oOO

0.664 ICEC 22 ICEC 27 ICEC 24 ICEC 25 0.724 0.657 0.833 0.872 0.820 0.795 0.759 0.797 1.000 0.827 0.854 0.870 1.000

0.805 0.759 1.000

0.724 000

000 IREA 26 IREA 23 IREA 28 IREA 29 0.590 0.532 0.618 0.615 0.466 0.486 0.833 0.855 1.000 0.433 0.317 0.678 1.000

0.567 0.462 I.OOO

0.480 I

### .ooo IREB 26 IREB 23 IREB 28 IREB 29 0.696 0.623 0.853 0.828 0.750 0.739 0.762 0.682 1.000 0.786 0.894 0.814 1.000

0.789 0.736 I.000

0.845 IREC 26 IREC 23 IREC 28 IREC 29 0.204 0.007 0.532 0.487 0.625 0.699 0.690 0.720 1.000 0.091 -0.148 -0.010 1.000

0.269 0.527 1.000

0.835 

### ooo

000IRED 26 IRBD 23 IRED 28 IRBD 29 12 12 12 12 IRBSUM 26 IRBSUM 23 1RIwJM 28 IRBSUM 29 12 12 12 II SM 30 SM 31 SM 32 SM 33 11 11 II I2 logNRU34 loSNRU35 logNRU37 loSNRU38 I2 I2 I2 12 E. Solids RBCDLl RBCDLZ RBCDL3 RBCDLA 18 20 18 19 1ogDLl 18 lo.gDL2 20 logDL3 18 IOgDLA 19 RBCDMI RBCDMZ RBCDM3 RBCDM4 18 20 18 20 1ogDM I 18 logDM2 20 logDM3 I8 logDM4 20 RBCH 1 18 RBCHZ 20 RBCH3 18 RBCH4 19 IogH 1 18 logH2 20 logH3 18 loSH4 19 EYTEX 5 16 EYTEX 6 17 EYTEX 7 20 EYTEX 8 17 0 0 0 0 0 0 0 I 1 I I 0 0 0 0 0

2 0 2 1 2 0 2 

### 1
2 0 2 0 2 0 2 0 2 0 2 I 2 0 2 I 4 3 0 3 0.621 0.504 MMAS=11.704+1.175 IRED 26

0.653 0.713 MMAS = 8.581 + 0.860 IRED 23 0.532 0.734 MMAS = 27.536 + 0.597 IRED 28 0.677 0.746 MMAS = 20.806 + 0.661 IRED 29 0.513 0.613 MMAS = 33.972 + 0.034 IRESUM 26 0.666 0.839 MMAS = 29.ooO + 0.043 IRESUM 23 0.555 0.776 MMAS = 33.987 + 0.228 IRESUM 28 0.554 0.597 MMAS = 33.813 + 0.202 IRESUM 29

- 0.746 - 0.800 MMAS = 201.566 - 45.800 SM 30

- 0.791 - 0.864 MMAS = 207.530 - 45.109 SM 31 -0.818 - 0.836 MMAS = 259.055 - 62.599 SM 32

- 0.706 - 0.755 MMAS = 152.848 - 29.258 SM 33

- 0.837 - 0.874 MMAS = 38.485 - 35.029 loSNRU34

- 0.848 - 0.862 MMAS = 36.639 - 35.195 logNRU35

- 0.831 - 0.867 MMAS = 35.880 - 32.070 loSNRU37 -0.815 - 0.874 MMAS = 38.052 - 32.396 loSNRU38

- 0.162 0.068

- 0.192 - 0.097

- 0.286 - 0.192

- 0.165 - 0.127 0.067 0.068

- 0.120 - 0.097

- 0.177 -0.192

- 0.089 -0.127 0.058 0.085 0.067 0.070 0.070 0.228

- 0.350 - 0.332 0.107 0.085 0.053 0.070 0.191 0.228

- 0.337 - 0.332

- 0.280 - 0.062

- 0.250 - 0.228

- 0.403 - 0.268 -0.313 - 0.281 MMAS = 45.402 - 9.09E-05 RBCDLl MMAS = 47.759 - 1.16E-04 RBCDL2 MMAS = 51.418 - 1.62E-04 RBCDL3 MMAS = 45.698 - 8.39E-05 RBCDL4 MMAS = 38.152 + 1.410 loSDLl MMAS = 56.361 - 3.147 loSDL2 MMAS = 56.305 - 2.836 logDL3 MMAS = 51.641 - 2.286 loSDL4 MMAS = 42.547 + 0.071 RBCDMI MMAS = 43.413 + 0.043 RBCDMZ MMAS = 46.564 + 0.059 RBCDM3 MMAS = 48.975 - 0.293 RBCDM4 MMAS = 42.122 + 4.379 IoSDM I MMAS = 43.537 + 1.420 loSDM2 MMAS = 44.880 + 6.289 loSDM3 MMAS = 48.949 - 10.730 logDM4 MMAS = 46.682 - 1.75E-04 RBCHl MMAS = 48.556 - 1.70E-04 RBCHZ MMAS = 52.399 - 2.54E-04 RBCH3 MMAS = 46.882 - 1.988-04 RBCH4

- 0.022 - 0.062

- 0.186 - 0.228

- 0.217 - 0.268

- 0.249 - 0.281 -0.134 0.061

- 0.026 0.228 -0.100 0.231

- 0.189 0.161 MMAS = 44.654 - 0.488 logHI MMAS = 61.520 - 4.677 logH2 MMAS = 61.271 - 4.311 loBH3 MMAS = 67.937 - 6.949 logH4 MMAS = 54.282 - 0.210 EYTEX 5 MMAS = 47.913 - 0.038 EYTEX 6 MMAS = 51.778 - 0.170 EYTEX 7 MMAS = 56.432 - 0.309 EYTEX 8 1.000 0.647 0.405 0.686 1.000 0.363 0.769 0.665 1.00 0.959 0.787 0.966 l.KJO 0.991 0.989 0.992

1.000 0.993 0.861 0.779 1.000 0.832 0.600 0.674 I.009 0.424

- 0.030

- 0.179 1.000 0.402 0.150

- 0.188 1.000 0.989 0.871 0.992 1.000 0.869 0.760 0.725 l.Oca 0.898 0.928 0.985 1.000

0.635 0.589

1.000 0.498 0.614

1.000 0.796 0.935

l.cmO 0.987 0.983

1.000 0.854 0.751

1.000 0.562 0.491

1.000 0.559 -0.166

l.caO 0.457

- 0.221

1.000 0.829 0.973

1.000 0.752 0.695

1.000 0.914 0.902 1.000

0.758

l.Ocm 0.872

1.000 0.655

1.000 0.686

1.000 0.699

1.000 0.137

1.000 0.085

1.000 0.893

1.000 0.585



### I.olxl 0.917 1.000

1.000

1.oOo

1.000

1.000

1.000

1.000

1.000

1.000

1.000

1.000 

### [conrd]Table 4-conrd Invitrotesting Inviva0.invim correlation

._

No. of No. of Spearman’s Alternative Zllllples samples Pearson’s rank method tested not tested correlation correlation

BCOPP9 BCOPPIO BCOPPI 1 BCOPPI2 BCOPPI3 index invitro

20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 9 0 7 1 II 13 13 17 9 0 7 1 20 20 20 20 20 20 20 19 invitro coefficient coefficient Linear regression equation MMAS = 45.904 - 0.977 BCOPP9 MMAS = 47.977- 2.339 BCOPPIO MMAS = 45.768- 0.890 BCOPPI I

BCOP09 BCOPOIO BCOPOI I BCoPo12 BCOPol3 BCOPB BCOPllO BCOPIII BCoP112 BCOPII3 BCOPI9b BCOPIlOb BCOPII lb BCOPI12b BCOPII 3b HETQ14 HETQl5 HETQl6 HE-I-Q17 HETS14 HETSlS HETS16 HETSl7 HETQl4b HETQl5b HETQI6b HETQl7b FL20 18 FL20 19 FL20 20 FL20 21 ICES 22 ICES 27 ICES 24 ICES 25 0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0 II 20 13 19 9 7 7 3 II 20 I3 I9 0 0 0 0 0 0 0 1 

### - 0.091 - 0.036

- 0.265 - 0.216

- 0.072 0.003

- 0.028 -0.116 0.025 - 0.266 0.096 0.174 0.044 0.267 0.056 0.25I 0.082 0.348 0.139 0.216 0.056 0.061

- 0.061 0.020 0.033 0.148 0.078 0.328 0.142 0.201 0.121 0.061 0.025 0.022 0.182 0.148 0.297 0.328 0.237 0.201 0.578 0.694

l** l** 0.808 0.875 *** l** 0.186 0.289 0.108 - 0.002 0.332 0.326 0.060 - 0.009 0.458 0.512

l** *** 0.694 0.816 *** ***

- 0.042 - 0.003

- 0.367 - 0.357

- 0.412 - 0.395

- 0.356 - 0.343 0.428 0.160 0.427 0.316 0.545 0.464 0.331 0.418 MMAS = 45.267 - 0.635 BCOPPIZ MMAS = 44.484 + 0.551 BCOPP13 MMAS = 42.877+ 0.030 BCOP09 MMAS=44.106+0.010 BCOPOlO MMAS = 44.024 + 0.014 BCOPOI I MMAS = 43.359+ 0.019 BCOPOIZ MMAS = 42.328+ 0.044 BCOPOI 3 MMAS = 43.415 + 0.017 BCOP19 MMAS = 46.121 - 0.014 BCOPIIO MMAS = 44.227 + 0.008 BCOPII

### I MMAS = 43.230 + 0.018 BCOPIIZ MMAS = 41.896+ 0.044 BCOPI13 MMAS = 41.384 + 0.045 BCOPI9b MMAS = 44.167 + 0.009 BCOPIlOb MMAS = 40.173 + 0.076 BCOPII1 b MMAS = 35.586+ 0.125 BCOPIIZb MMAS = 39.187+ 0.092 BCOPIl3b MMAS = 29.913+ 3.537 HETQ14

l** MMAS = 13.547+ 12.013 HETQl6

*** MMAS = 45.789+ 2.554 HETSl4 MMAS = 37.824+ 0.352 HETS15 MMAS = 37.068+ 2.473 HETSl6 MMAS = 45.455 + 0.262 HETSI 7 MMAS = 24.537+ 10.920 HETQl4b

*** MMAS = - 4.827+ 29.946 HETQl6b

*** MMAS = 45.651 - 0.004 FL20 I8 MMAS = 58.179- 0.047 FL20 I9 MMAS = 61.378- 0.045 FL20 20 MMAS = 54.240- 0.037 FL20 21 MMAS = 34.980+ 0.753 ICES 22 MMAS = 33.570+ 0.179 ICES 27 MMAS = 30.517+0.918 ICES 24 MMAS = 35.838+ 0.304 ICES 25 Interlaboratory correlation of inuirro data

Lab Lab a Lab b Lab c Lab d Lab e

1.000 0.773 1.ooo 0.926 0.843 0.878 0.563 0.932 0.670 l.OCKl 0.941 0.908 0.912 0.966 l.OOa

0.887 0.903 0.930 1.000 0.902 0.897 0.880 0.945 1.000

0.872 0.852 0.884 1.000 0.881 0.887 0.870 0.921 1.000

0.869 0.776 0.824 1.000
O.&

l *

* * 1.000 0.174 -0.171

- 0.103 l.ooO

-0.171 0.808 1.000 0.5;85 * l
l
l 1.000 0.727 0.165 0.822 1.Ocm

0.368 0.882 1.000 0.869 0.847 0.778 1.000

0.734 0.722 I

### .ooo

0.889 0.934

1.000 0.977 0.952

1.000 0.960 0.943

I.OOO 0.889 0.925

1.000 t

l.wO 0.03I

1.000 *

1.000 0.432

l.Ooa 0.81I 1.000

0.886 1

.ooo

1.000 0.942 I.ooo

I.ooo 0.942 1.000

I

### .ooo 0.930 1.000



### *

1.ooo



### t

1.000

1.ooo



### ~ .,_^ ~.^.

_. .-._.-_- ,... .....__.^._._-._..ICE0 22 

### m 0 0.307 0.026 MMAS = 35.837+ 6.283 ICE0 22 ICE0 27 20 0 0.220 0.216 MMAS = 37.840+ 4.178 ICE0 27 ICE0 24 m 0 0.516 0.429 MMAS = 19.720+ 17.243 ICE0 24 ICE0 25 20 0 0.398 0.250 MMAS = 31.451 + 9.016 ICE0 25 ICEF 22 m 0 0.268 0.195 MMAS = 35.086+ 6.407 ICEF 22 ICEF 27 m 0 0.223 0.193 MMAS = 38.244+ 4.759 ICEF 27 ICEF 24 m 0 0.345 0.364 MMAS = 30.352+ 8.829 ICEF 24 ICEF 25 m 0 0.323 0.257 MMAS = 27.545 + 10.494 ICEF 25 ICEC 22 m 0 0.335 0.060 MMAS = 34.183+ 0.147 ICEC 22 ICEC 27 20 0 0.356 0.269 MMAS = 34.099+ 0.086 ICEC 27 ICEC 24 m 0 0.492 0.424 MMAS = 24.001 + 0.269 ICEC 24 ICEC 25 20 0 0.445 0.347 MMAS = 29.204+ 0.175 ICEC 25 IRW 26 20 0 0.001 - 0.056 MMAS = 44.809+ 0.018 IREiA 26 IREA 23 20 0 0.225 0.277 MMAS = 43.215 + 7.680 IREA 23 IREA 28 20 0 0.235 0.237 MMAS = 42.416+ 7.652 IREA 28 IREA 20 0 0.403 0.373 MMAS = 34.070+ 13.948 IREA 29 IREB 26 

### m 0 0.231 0.130 MMAS = 39.341 + 4.123 IREB 26 IREB 23 

### m 0 0.298 0.301 MMAS = 37.694+ 5.975 IREB 23 IREB 28 

### m 0 0.564 0.534 MMAS = 36.028+ 12.211 IREB 28 IREB 29 20 0 0.284 0.302 MMAS = 38.013+ 7.934 IREB 29 IREC 26 19 1 - 0.0% -0.182 MMAS = 44.090- 0.064 IREC 26 IREC 23 20 0 0.340 0.295 MMAS = 38.830+ 0.431 IREC 23 IREC 28 20 0 0.422 0.504 MMAS = 35.475+ 0.674 IREC 28 IREC 29 20 0 0.487 0.390 MMAS=36.115+0.516 IREC 29 IRED 26 19 I 0.112 -0.085 MMAS = 40.198+ 0.089 IRED 26 IRED 23 20 0 0.384 0.299 MMAS = 36.571+ 0.319 IRED 23 IRED 28 20 0 0.492 0.565 MMAS = 34.311

### +0.375 IRED 28 IRED 20 0 0.566 0.612 MMAS = 36.312+ 0.290 IRED 29 IRESUM 26 20 0 0.033 0.045 MMAS = 44.143+ 0.001 IRESUM 26 IRESUM 23 19 1 0.182 0.286 MMAS = 43.579+ 0.009 IRESUM 23 IRESUM 28 20 0 0.216 0.545 MMAS = 43.168+ 0.010 IRESUM 28 IRESUM 29 15 5 0.293 0.177 MMAS = 49.195 + 0.014 IRESUM 29 SM 30 I2 8 0.058 0.027 MMAS = 33.719+ 1.204SM 30 SM 31 7 13 - 0.655 - 0.795 MMAS= 101.344-14.179 SM 31 SM 32 6 14 - 0.810 - 0.771 MMAS = 137.020- 26.029 SM 32 SM 33 6 14 - 0.492 - 0.647 MMAS = 92.257- 11.293 SM 33 logNRU34 logNRU35 logNRU37 logNRU38 - 0.565 - 0.442 MMAS = 39.306- 10.245 logNRU34

- 0.487 - 0.365 MMAS = 41.869- 9.238 logNRU35 -0.433 - 0.352 MMAS = 39.995- 8.148 logNRU37

- 0.667 - 0.478 MMAS = 38.720- 14.847logNRU38 F. Sohuiom RBCDLI RBCDLZ RBCDL3 RBCDL4 - 0.593 - 0.621 MMAS = 86.666- 4.87E-04 RBCDLI

- 0.692 - 0.651 MMAS = 86.319- 0.001 RBCDLZ

- 0.449 - 0.251 MMAS = 74.755- 3.7OE-04RBCDL3

- 0.693 - 0.681 MMAS = 87.784 - 0.001 RBCDL4 IogDL

### I logDL2 logDL3 lOgDL4 20 20 20 20

14 14 14 14 14 14 14 14 0

0 0 0

0 0 0 0 0 0 0 0 - 0.593 - 0.621 MMAS = 257.016- 43.804 IogDLl

- 0.621 - 0.651 MMAS = 200.238- 32.746 logDL2

- 0.139 - 0.251 MMAS = 75.317- 3.976 logDL3

- 0.693 - 0.681 MMAS = 288.739 - 51.674 logDL4 l.OWl 0.595 0.752 0.868 1.000 0.729 0.864 0.739 l.wo 0.806 0.874 0.883 1.000 0.195 0.394 0.405 1.000 0.782 0.629 0.569 l.Ow 0.335 0.670 0.559 1.000 0.540 0.791 0.798 1.000 0.199 0.191 0.432 1.000 0.977 0.481 0.884 1.000 0.976 0.976 0.903

1.000 0.871 0.737 0.866 1.000 0.816 0.571 0.866 1.m

0.602 0.649

1.000 0.678 0.869

1.000 0.752 0.816

1.000 0.908 0.543

l.CKlO 0.649 0.524

l.Ow 0.404 0.628

l.ooO 0.685 0.689

1.000 0.991 0.606

l.Ooa 0.623 0.981

1.000 0.978 0.921

l.wo 0.842 0.998

1.000 0.616 0.884 l.OC@

0.752

1.000 0.674

1.000 0.880

l.ooO 0.468

1mO 0.672

l.ooO 0.829

l.Om 0.949

1.am 0.635

1.ooo 0.370

1.000 0.878

1.000 0.842

1.000 0.563 1.000

1.000

1.000

l.Ocm

1.000

I.000

I.000



### I.loo

l.m

1.ooo

1.000

1.000 

### [conrcf

]Table &confd In uirro testing In viva 0. in vitro correlation Interlaboratory correlation of in vitro data

No. of No. of Spearman’s Alternative samples samples Pearson’s rank method tested not tested correlation correlation index in vitro in vitro coefficient coefficient Linear regression equation Lab Lab a Lab b Lab c Lab d Lab e RBCDM 

### I RBCDMZ RBCDM3 RBCDM4 logDM 

### 1 logDM2 logDM3 logDM4 RBCH 

### I RBCHZ RBCH3 RBCH4 logHI logH2 logH3 logH4 EYTEX 5 EYTEX 6 EYTEX I EYTEX 8 BCOPP9 BCOPPIO BCOPPI 

### I BCOPPI 2 BCOPPI 3 BCOP09 BCOPOIO BCOPDII BCoPo12 BCoFJo13 BCOP19 BCOPIlO BCOPI 

### II BCOPIl2 BCOPI 13 BCOPI9b BCOPIlOb BCOPIllb BCOPIIZb BCOPI l3b 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 10 II 13 10 14 14 I4 14 14 14 I4 I4 14 14 14 14 14 14 14 I4 14 14 14 I4 0

0 0 0
0 0 0 0
0 0 0 0
0 0 0 0 4 3 I 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.546 0.526

0.497 0.442 0.474 0.504 0.432 0.483 0.435 0.526 0.438 0.442 0.403 0.504 0.413 0.483

- 0.484 ~ 0.609

- 0.628 - 0.546

- 0.180 ~ 0.363

- 0.462 ~ 0.595

- 0.640 - 0.609

- 0.598 - 0.546

- 0.326 - 0.363

- 0.616 - 0.596 0.455 0.671 0.319 0.335 0.490 0.673 0.370 0.372 0.426 0.319 0.575 0.451 0.548 0.293 0.701 0.629 0.745 0.770 0.502 0.365 0.599 0.594 0.494 0.497 0.467 0.403 0.509 0.497 0.586 0.546 0.771 0.689 0.628 0.640 0.598 0.563 0.643 0.568 0.558 0.543 0.775 0.693 0.641 0.644 0.581 0.561 0.649 0.565 MMAS = 26.657 + 0.857 RBCDMI MMAS = 32.009 + 0.575 BCDM2 MMAS = 30.204 + 0.712 RBCDM3 MMAS = 35.956 + 0.530 RBCDM4 MMAS = 29.636 + 22.889 IogDMl MMAS = 29.694 + 21.794 logDM2 MMAS = 31.708 + 20.880 logDM3 MMAS = 31.332 + 20.949 logDM4 MMAS = 67.254 - 0.001 RBCHI MMAS = 72.859 - 0.002 RBCHZ MMAS = 63.519 - 2.27E-04 RBCH3 MMAS = 66.618 - 0.001 RBCH4 MMAS = 146.096 - 27.346 logHI MMAS = 134.127 -24.148 logH2 MMAS = 100.394 - 12.383 logH3 MMAS = 139.708 - 25.704 logH4 MMAS = - 4.250 f 1.569 EYTEX 5 MMAS = 22.594 + 0.813 EYTEX 6 MMAS = 2.479 + 1.419 EYTEX I MMAS= l2.540+ I.150 EYTEX 8 MMAS = 30.307 + 10.132 BCOPP9 MMAS = 18.942 + 10.743 BCOPPlO MMAS = 13.654 + 13.707 BCOPPI 1 MMAS = 7.437 + 16.837 BCOPPIZ MMAS = - I.786 + 25.384 BCOPPI 3 MMAS = 42.995 + 0.252 BCOP09 MMAS = 38.031 + 0.419 BCOPOIO MMAS = 45.345 + 0.251 BCOPOl I MMAS = 46.834 + 0.186 BCOPOIZ MMAS = 41.647 + 0.326 PCOPO13 MMAS = 29.938 + 0.270 BCOP19 MMAS = 10.545 + 0.451 BCOPIlO MMAS = 26.938 + 0.303 BCOPIl I MMAS = 33.872 + 0.223 BCOPIIZ MMAS = 25.803 + 0.368 BCOPI13 MMAS = 24.666 + 0.353 BCOPI9b MMAS = 6.71I + 0.502 BCOPIlOb MMAS = 16.633 + 0.442 BCOPII lb MMAS = 24.757 f 0.362 BCOPIIZb MMAS = 22.206 + 0.424 BCOP113b 1.000 0.965 0.945 0.897 

### I.ooo 0.997 0.992 0.987 l.ooO 0.906 0.478 0.997 1.000 0.967 0.903 0.994 1.000 0.777 0.989 0.797 I.000 0.731 0.901 0.795 0.699 1.000 0.984 0.985 0.989 0.984 1.000 0.917 0.975 0.974 0.969 1.000 0.899 0.970 0.955 0.946 I.000

0.913 0.915

I.000 0.987 0.986

I.ooo 0.527 0.892

1.000 0.880 0.968

1.000 0.736 0.940

I.000 0.864 0.903 0.846

1.000 0.959 0.968 0.988

l.OOil 0.920 0.914 0.926

1.000 0.928 0.921 0.918 1.000

0.963



### 1.000 0.996

I.000 0.427

1.000 0.917

1.000 0.93I

1.000 0.896 0.875

1.000 0.987 0.955

1.000 0.974 0.954

1.000 0.962 0.976 

### t,000

I.000

I 000



### I.ooo

1.000

I.000 0.933

I.000 0.976

1.000 0.980



### 1.000 0.972 1.000

1.000

I.oOO

1.000HETQ14 HETQIS HETQ16 HETQI7 14 14 14 14 HETQ14b HETQl5b HETQl6b HETQI 7b 14 14 14 14 FL20 18 FL20 19 FL20 20 FL20 21 14 14 14 14 ICES 22 ICES 27 ICES 24 ICES 25 14 14 13 13 ICE0 22 14 ICE0 27 14 ICE0 24 14 ICE0 25 14 ICEF 22 ICEF 27 ICEF 24 ICEF 25 ICEC 22 ICEC 27 ICEC 24 ICEC 25 IREA 26 IREA 23 IREA 28 IREA 29 IREB 26 IREB 23 IREB 28 IREB 29 IREC 26 IREC 23 IREC 28 IREC 29 IRED 26 IRED 23 IRED 28 IRED 29 14 14 13 14 14 14 14 14 14 14 14 14 14 14 14 14 13 14 12 14 13 14 12 14 0

0 0 0 0 0 0 0
0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0
0 0 0 0
0 0 0 0 0 0 0 0 I 0 2 0 I 0 2 0 0.125 0.268

0.340 0.436 0.341 0.315 0.678 0.658 **t l** 0.483 0.493 0.238 0.292 0.430 0.448

- 0.654 - 0.616

- 0.612 - 0.477 0.116 0.104

- 0.634 -0.832 0.853 0.823 0.640 0.678 0.657 0.608 0.471 0.342 0.751 0.725 0.559 0.600 0.549 0.503 0.593 0.561 0.713 0.734 0.672 0.705 0.799 0.810 0.833 0.824 0.777 0.761 0.680 0.617 0.743 0.722 0.692 0.726 0.718 0.702 0.672 0.665 0.502 0.425 0.603 0.624 0.733 0.722 0.763 0.761 0.660 0.673 0.657 0.598 0.463 0.308 0.564 0.726 0.157 0.436 0.407 0.367 0.553 0.591 0.686 0.664 0.240 0.495 0.529 0.623 MMAS = 54.195+ 0.905 HETQ14 MMAS = 40.839+ 4.228 HETQl5 MMAS = 49.585+ 2.071 HETQ16 MMAS = 19.294+ 8.415 HETQl7

*** MMAS = - 2.657+ 34.574 HETQl5b MMAS = 14.869+ 26.376 HETQ16b MMAS = 2.670+ 30.814 HETQ17b MMAS = 75.327- 0.086 FL20 18 MMAS = 73.927- 0.069 FL20 19 MMAS = 53.194+ 0.011 FL20 20 MMAS = 79.839- 0.077 FL20 21 MMAS = 9.018+ 2.647 ICES 22 MMAS = 29.664+ 0.484 ICES 27 MMAS = 23.299+ 1.374 ICES 24 MMAS = 40.525 + 0.452 ICES 25 MMAS = 31.431 + 20.437 ICE0 22 MMAS = 34.426+ 16.433 ICE0 27 MMAS = 26.751 + 18.810ICE0 24 MMAS = 12.823+ 21.467 ICE0 25 MMAS = 2.430+ 30.020 ICEF 22 MMAS = 17.736+ 26.829 ICEF 27 MMAS = - 25.773+ 37.446 ICEF 24 MMAS = - 17.319+ 37.148 ICEF 25 MMAS = 15.501+ 0.529 ICEC 22 MMAS = 22.987+ 0.296 ICEC 27 MMAS = 2.019+ 0.541 ICEC 24 MMAS = 13.495+ 0.371 ICEC 25 MMAS = 28.604+ 22.699 IREA 26 MMAS = 37.044+ 21.329 IREA 23 MMAS = 48.073+ 14.913 IREA 28 MMAS = 35.352+ 25.778 IREA 29 MMAS = 6.570+ 23.330 IREB 26 MMAS = 1.915+ 24.087 IREB 23 MMAS = 29.086+ 18.513 IREB 28 MMAS = 18.633+ 21.799 IREB 29 MMAS = 34.226+ 0.845 IREC 26 MMAS = 33.188+ 0.874 IREC 23 MMAS = 44.360+ 0.378 IREC 28 MMAS = 43.136+ 0.520 IREC 29 MMAS = 29.714+ 0.638 IRED 26 MMAS = 16.878+ 0.698 IRED 23 MMAS = 42.224+ 0.211 IRED 28 MMAS = 33.191+ 0.441 IRED 29 1.000 0.880 0.776 0.712

1.000 0.990 0.363 0.589 1.000 0.617 0.757 0.539 1.000 0.797 0.796 0.794 1.000 0.781 0.604 0.901 1.000 0.873 0.877 0.907 1.000 0.648 0.733 0.789 1.000 0.808 0.862 0.789 1.000 0.914 0.464 0.805 1.000 0.776 0.613 0.868 1.000

0.730 0.842

1.000 0.591 0.974

l.Ooa 0.387 0.528

l.ooO 0.856 0.889

1.000 0.907 0.868

1.000 0.543 0.689

1.000 0.905 0.913

l.ooO 0.712 0.596

1.000 0.812 0.746

l.Oml 0.682 0.815

1.000 0.575 0.696 l.ooo

0.765

1.000 0.590

1.000 0.031

1.000 0.821

1.000 0.717

1.000 0.772

1.000 0.868

1.000 0.817

1.oOo 0.906

l.Ooa 0.845

1.000 0.78I 1.000

1.000

l.OW

1.000

1.oOo

1.000

1.000

1.000

1.000

l.Ooa

1.000 [contd]Table 4-contd In vitro testing In ho 0. in virrocorrelation Interlaboratory correlation of in uirro data

No. of No. of Spearman’s Alternative samples samples PeWsoIl’s rank method teated not tested comlation correlation index in vitro in vitro co&c&t coefficient Linear regression equation Lab Lab a Lab b Lab c Labd Lab e IRESUM 26 0.651 0.122 IRESUM 23 IRESUM 28 IRESUM 29 14 I4 14 14 0.743 0.770 0.548 0.703 0.539 0.631 1.000 0.770 0.863 0.884 1.000

0.811 0.800 1.000

0.957 SM 30 Shl 31 SM 32 SM 33 14 14 14 I4 - 0.765 - 0.724

- 0.775 - 0.770

- 0.754 - 0.752

- 0.755 - 0.783 1.000 0.964 0.882 0.976 1.000

0.799 0.985 1.000

0.799 1.000

1.000 logNRU34 logNRU35 logNRU37 logNRU38 14 14 I4 14 - 0.473 - 0.466

- 0.609 - 0.565

~ 0.484 - 0.455

~ 0.495 - 0.475 MMAS = 40.064 + 0.024 IRESUM 26 MMAS = 34.283 + 0.033 IRESUM 23 MMAS = 49.242 + 0.027 IRESUM 28 MMAS = 48.404 + 0.032 IRESUM 29 MMAS = 211.546 - 44.800 SM 30 MMAS = 223.200 - 47.046 SM 31 MMAS = 225.846 - 49.054 SM 32 MMAS = 204.210 - 41.085 SM 33 MMAS = 61.273 - 15.387 logNRU34 MMAS = 58.658 - 20.474 logNRU35 MMAS = 59.469 - 15.257 logNRU37 MMAS = 60.047 ~ 16.707 logNRU38 1.ooo 0.971 0.971 G. Liquti RBCDLl RBCDLZ RBCDL3 RBCDL4 24 26 26 26 0

0 0 0
0 0 0 0
0 0 0 0

2 0 0 0 2 0 0 0 2 0 0 0 2 0 0 0 2 0 0 0 2 0 0 0 3 5 2 2 1.000 0.974 0.992 0.993 1.000 0.998

0.040 0.079 0.001 0.019 0.067 0.124

- 0.055 -0.113 MMAS = 30.323 + 2.17E-05 RBCDLl MMAS = 31.948 + 4.48E-07 RBCDLZ MMAS = 30.484 + 3.35E-05 RBCDL3 MMAS = 33.124 - 2.838-05 RBCDL4 MMAS = 13.615 +4.158 IogDLl MMAS = 21.357 + 2.617 logDL2 MMAS = 17.991 + 3.609 logDL3 MMAS = 43.438 - 2.895 logDL4 MMAS = 30.709 + 0.227 RBCDMI MMAS = 29.693 + 0.I87 RBCDMZ MMAS = 30.587 + 0.444 RBCDM3

*** 1.000 0.908 0.883 0.88

### I 1.000

0.961 0.987 1.000

0.930 ,000

,000 logDL1 24 logDL2 26 logDL3 26 logDL4 26 0.139 0.079 0.104 0.019 0.168 0.124

~ 0.109 -0.113 1.000 0;.945 0.816 0.880 1.000

0.869 0.906 I.000

0.841 1.000 RBCDM 1 24 RBCDMZ 26 RBCDM3 26 RBCDM4 26 0.114 0.112 0.177 0.171 0.198 0.227 *** *** l.ooO 0.588 0.833 0.900 1.000

0.524 0.356 1.000

0.936 logDM 

### I 24 logDM2 26 logDM3 26 logDM4 26 0.089 0.112 MMAS = 30.845 + 4.925 IogDM 1 0.128 0.171 MMAS = 29.975 + 4.274 logDM2 0.216 0.227 MMAS=30.138+11.711 logDM3 *** t** l** l.lXlO 0.599 0.512 0.762 1.000

0.593 0.351 1.oOa

0.713 ,000

,000 RBCHI 24 RBCH2 26 RBCH3 26 RBCH4 26 - 0.020 - 0.004

- 0.031 - 0.009

- 0.033 - 0.016 -0.111 - 0.125 MMAS = 32.085 - l.l8E-05 RBCHl MMAS = 32.643 - I.9OE-05 RBCHZ MMAS = 32.660 - I.76E-O5 RBCH3 MMAS = 34.200 - 5.98E-05 RBCH4 MMAS = 18.340 + 3.089 IogHl MMAS = 22.624 + 2.354 logH2 MMAS = 33.497 - 0.413 logH3 MMAS = 44.106 - 3.100 logH4 MMAS= -4.215+1.211 EYTEX 5 MMAS = - 6.505 + 1.191 EYTEX 6 MMAS= -1.500+1.094 EYTEX 7 MMAS = 0.875 + 1.094 EYTEX 8 1.000 0.878 0.851 0.911 I.000

0.827 0.875 1.000

0.945 1.000 logHI 24 logH2 26 logH3 26 logH4 26 0.101 - 0.004 0.091 ~ 0.009

- 0.023 - 0.016 -0.117 - 0.125 1.000 0.956 0.772 0.909 l.OOil

0.782 0.889 1.000

0.810 EYTEX 5 23 EYTEX 6 21 EYTEX 7 24 EYTEX 8 24 0.580 0.681 0.600 0.625 0.643 0.666 0.529 0.624 1.000 0.571 0.876 0.830 1.000

0.585 0.644 1.000

0.809 000

000BCOPP9 26 BCOPPIO 26 BCOPPI I 26 BCOPPIZ 26 BCOPPI 3 26 BCoPo9 26 BCOPOIO 26 BCOPOII 26 BCoPol2 26 BCoPo13 26 BCoPI9 26 BCOPIIO 26 BCOPII I 26 BCOPIIZ 26 BCOPI I3 26 BCOPbb 26 BCOPIlOb 26 BCOPIllb 26 BCOPIlZb 26 BCOPIl3b 26 HETQ14 26 HETQl5 26 HETQIL 26 HETQI7 26 HETQl4b 26 HETQl5b 26 HETQl6b 26 HETQI 7b 26 FL20 18 25 FL20 19 26 FL20 20 26 FL20 21 25 ICES 22 26 ICES 27 26 ICES 24 26 ICES 25 26 ICE0 22 26 ICE0 27 26 ICE0 24 26 ICE0 25 26 ICEF 22 26 ICEF 27 26 ICEF 24 26 ICEF 25 26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 I 0 0 I 0 0 0 0 0 0 0 0 0 0 0 0 0.676 0.692

0.541 0.560 0.603 0.634 0.429 0.612 0.589 0.639 0.528 0.71I 0.491 0.687 0.537 0.728 0.503 0.706 0.489 0.687 0.690 0.770 0.612 0.664 0.638 0.722 0.521 0.717 0.602 0.747 MMAS = 12.458 + 10.910 BCOPP9 MMAS = 17.489 + 8.829 BCOPPIO MMAS = 15.607 + 8.919 BCOPPI 1 MMAS = 22.292 + 5.915 BCOPPIZ MMAS = 16.315 + 14.554 BCOPP13 MMAS = 20.005 + 0.509 BCOP09 MMAS = 21.680 +0.504 BCOPOIO MMAS = 20.528 + 0.698 BCOPOI I MMAS=21.120+0.438 BCOPOIZ MMAS = 21.324 + 0.567 BCOPO13 MMAS = II.622 + 0.404 BCOP19 MMAS = 14.722 + 0.383 BCOPIIO MMAS = 14.536 + 0.397 BCOPII I MMAS = 19.174 + 0.261 BCOPIIZ MMAS = 15.739 + 0.465 BCOP113 0.690 0.770 MMAS = I1.622 + 0.404 BCOP19b 0.612 0.664 MMAS = 14.722 +0.383 BCOPIlOb 0.638 0.722 MMAS = 14.536 + 0.397 BCOPII lb 0.521 0.717 MMAS = 19.174+0.261 BCOPIIZb 0.602 0.747 MMAS = 15.739 + 0.465 BCOPIl3b 0.406 0.596 MMAS = 23.053 + I.741 HETQ14 0.444 0.489 MMAS = 19.61I + 2.957 HETQl5 0.328 0.549 MMAS = 25.853 + 2.592 HETQ16 0.48I 0.616 MMAS = 17.094 + 3.426 HETQ17 0.541 0.576 MMAS = - 0.723 + 19.990 HETQl4b 0.540 0.587 MMAS = - 2.650 + 22.109 HETQl5b 0.502 0.546 MMAS = 3.125 + 20.751 HETQ16b 0.550 0.625 MMAS = - 36.545 + 37.550 HETQ17b

- 0.658 - 0.691 MMAS = 56.201 - 0.041 FL20 I8

- 0.491 - 0.489 MMAS = 52.564 - 0.030 FL20 I9 -0.180 - 0.274 MMAS = 45.617 - 0.018 FL20 20 0.134 0.008 MMAS = 23.995 + 0.008 FL20 21 0.577 0.608 MMAS = 12.182 + 1.004 ICES 22 0.703 0.725 MMAS = - 1.407 + 0.564 ICES 27 0.573 0.550 MMAS=9.816+ 1.108 ICES 24 0.484 0.51I MMAS = 16.845 + 0.526 ICES 25 0.449 0.471 0.442 0.379 0.528 0.577 0.548 0.606 0.535 0.595 0.401 0.421 0.619 0.646 0.676 0.657 MMAS = 10.418 + 13.869 PCEO 22 MMAS = 13.755 + 10.1I9 ICE0 27 MMAS = 2.540 + 17.194 ICE0 24 MMAS = 8.183 + 14.689 ICE0 25 MMAS = 1.912 + 15.916 ICEF 22 MMAS = 17.422 + 9.385 ICEF 27 MMAS = 2.733 + 14.951 ICEF 24 MMAS = - 4.941 + 18.419 ICEF 25 1.ooo 0.733 0.801 0.781 0.893 1.000 0.961 0.935 0.949 0.961 l.OOtl 0.873 0.875 0.897 0.953 1.000 0.873 0.875 0.897 0.953 1.000 0.755 0.221 0.492 1.000 0.721 0.771 0.675 1.000 0.741 0.563

-0.360 1.000 0.779 0.690 0.626 1.000 0.757 0.770 0.719 1.000 0.607 0.748 0.594 1.ooo

0.856 0.612 0.794

1.000 0.955 0.961 0.964

1.000 0.939 0.851 0.891

1.000 0.939 0.851 0.891

1.000 0.450 0.692

1.000 0.638 0.765

1.000 0.531 0.203

1.000 0.736 0.461

1.000 0.695 0.692

1.000 0.394 0.494 1.000

0.801 0.858

1.000 0.967 0.913

1.000 0.902 0.898

1.000 0.902 0.898

1.000 0.704

1.000 0.591

1.000 0.374

1.000 0.560

1.000 0.764

1.000 0.654 1.ooo

0.845 1.000Table Lcontd In vitro testing In viva 0. in vitro correlation Interlaboratory correlation of in vitro data

No. of No. of Spearman’s Alternative samples samples Pearson’s rank method tested not tested correlation correlation index invitro in vitro coefficient coefficient Linear rearession eauation Lab Lab a Lab b Lab c Lab d Lab e 

# H

ICEC 22 26 ICEC 27 26 ICEC 24 26 ICEC 25 26 IREA 26 26 IREA 23 26 IREA 28 26 IREA 29 26 IREB 26 26 IREB 23 26 IREB 28 26 IREB 29 26 IREC 26 26 IREC 23 26 IREC 28 26 IREC 29 26 IRED 26 26 IRED 23 26 IRED 28 26 IRED 29 26 IRESUM 26 26 IRESUM 23 26 IRESUM 28 26 IRESUM 29 25 SM 30 SM 31 SM 32 SM 33 12 II 15 11 logNRU34 logNRU35 26 26 26 26 0

0 0 0 0 0 0 0
0 0 0 0
0 0 0 0
0 0 0 0 0 0 0 I 14 15 II 15 0 0 0 0 0.557 0.583

0.620 0.640 0.616 0.613 0.666 0.676 1.000 0.856 0.830 0.778 1.ooo

0.745 0.751 1.000

0.803 0.595 0.617 0.197 0.261 0.393 0.413 0.459 0.522 MMAS = 3.836 + 0.317 ICEC 22 MMAS = 1.698 + 0.240 ICEC 27 MMAS = 0.701 + 0.335 ICEC 24 MMAS = - I.I51+ 0.327 ICEC 25 MMAS = 15.963 + 16.847 IREA 26 MMAS = 29.455 + 5.941 IREA 23 MMAS = 26.042 + II.673 IREA 28 MMAS = 23.402 + 13.101 IREA 29 MMAS = 8.952 + 12.925 IREB 26 MMAS = 15.515 + 9.506 IREB 23 MMAS = 10.189 + 15.472 IREB 28 MMAS = Ii.213 + 17.687 IREB 29 MMAS = 28.182 + 0.236 IREC 26 MMAS = 24.805 + 0.377 IREC 23 MMAS = 10.775 + 1.392 IREC 28 MMAS = 7.258 + 

### I.586 IREC 29 MMAS = 13.322 + 0.578 IRED 26 MMAS = 5.559 + 0.653 IRED 23 MMAS = 8.512 + 0.702 IRED 28 MMAS = 12.267 + 0.610 IRED 29 MMAS = 23.816 + 0.021 IRESUM 26 MMAS = 29.217 + 0.010 IRESUM 23 MMAS = 28.214 + 0.016 IRESUM 28 MMAS = 29.974 + 0.017 IRESUM 29 MMAS = 31.281 + 1.819 SM 3 MMAS = - 1.948 + 7.668 SM 31 MMAS = 22.989 + 3.812 SM 32 MMAS = 21.559 + 2.431 SM 33 MMAS = 33.679 - 2.982 logNRU34 MMAS = 33.867 - 2.679 logNRU35 MMAS = 32.373 - 0.662 logNRU37 1.000 0.496 0.685 0.709 1.000

0.518 0.625 l.Ooa

0.704 0.588 0.580 0.402 0.384 0.651 0.661 0.759 0.764 

### I.ooo 0.525 0.628 0.664 

### 1

.ooo 0.526 0.470 

### I.ooo

0.824 0.115 0.192 0.143 0.139 0.624 0.61

### I 0.709 0.774 l.ooo 0.137 0.245 0.342 

### 1.000

0.214 0.101 

### I.ooo

0.808 0.591 0.577 0.527 0.524 0.743 0.699 0.736 0.782 l.ooo 0.539 0.712 0.790 

### I.ooo

0.507 0.613 

### 1

.ooo 0.906 0.514 0.627 0.203 0.524 0.336 0.660 0.259 0.743 1.oOO 0.527 0.693 0.626 

### 1

.ooo 0.793 0.696 1.000

0.716 0.053 - 0.131 0.153 - 0.121 0.158 0.177 0.072 - 0.364 1.000 0.876 0.260 0.836 I.000

0.273 0.976 1.000

0.263

- 0.099

- 0.087

- 0.024 0.047 - 0.089

-0.135

- 0.064 I.000 0.912 0.917 0.940 1.000

0.840 0.896 I.ooo

1.000

1.000

I.000

1.000

I

### .ooo

1.000

1.000 logNRU37 1.000 logNRU38 - 0.032 MMAS = 31.048 + 1.334 logNRU38 d 0.966 The seven parts of this table (AG) correspond to the seven sets of comparisons listed in Table 3. Further details of each of the nine tests are given in Appendix 2. The 27 endpoints are numbered in sequence in this legend (El to E27). The numbers 1-38 against each endpoint in the Table refer to the laboratories which conducted each particular test. Laboratory 36 left the study without submitting any results. RBC = the Red Blood Cell Haemo!vsis Test El BRCDL = D Low E2 LogDL = D Low. log transformed E3 RBCDM = D Max E4 Log DM = D Max. log transformedLegend to Fig. 4. contd E5 RBCH = H50 E6 LogH = H50, log transfomxd EYTEX = the EYTEX Reagent Turbidity Test El EYTEX = EYTEX Draize Equivalent BCOP = the Bovine Comeal OpacitylPermeobility Test E8 BCOPP = Permeability E9 BCOPO El0 BCOPI I= El1 BCOPIb = Index, with cut-off at 200 HET = The Hen’s Egg Test (Chorioollontoic Membrane Assay) El2 HETQ =QScore El3 HETS =sSco?e El4 HETQB = Q Score, with cut-off at 2 El5 HETSB = S Score, with cut-off at 2
FL = The Fluorescein Leakage Test El6 FL, = 20% Fluorescein leakage ICE = the Isolated, Emcleated Chicken Eye Test El7 ICES = Swelling El8 ICE0 = Opacity El9 ICEF = Fluorescein retention E20 ICEC = Classification IRE =the Isolated, Emcleated Rabbit Eye Test E21 IREA = Opacity (1 hour) E22 IREB = Opacity (4 hour) E23 IREC = Swelling (I hour) E24 IRED = Swelling (4 hours) E25 IRESUM = Summary score SM =

### the

Silicon Microphysiometer Test E26 SM = log MRDSO NRU = the Neutral Red Uptake Test E21 NRU = log NRUSO The subsequent columns show the following: Number of samples tested in vitro Number of samples not tested in vitro Pearson’s product moment correlation coefficient Spearman’s rank correlation coefficient The linear regression equation The interlaboratory correlation matrix, for which the letters a-d (or e) refer to the four or five laboratories which conducted each test. MMAS = Modified Maximum Average Score (Bagley et al., 1992; ECETOC, 1992). 6 

# ,”
% k’ CD 6 

### z.M. Balls et al.

Y=48.485-0.00014X Y=43.811 -0.371X

r= -0.206 r=-0.012 

# -

.Y_

# * ---.---- - -.. _ 100 --_ - -_

. 80 1

0 25000 50000 75000 100000 0 1 2 3 4 

### I

RBCDLI IogDLl

Y q 34.718+0.562X r= 0.433

100

80

20

0

0 10 20 30 40 50 60 70 60 90 100



### RBCDMI 

### I

.
80 : 

### .
.

20 ;
.

z 0 L I’, ; 1’

0 1 2



### IogDMl Fig. 2(a).EC/HO validation study on alternatives to the Drake test 901

Y=49.279-0.00023X Y =75.519-8.999X r=-0.309 r=-0.310 120

100

60

3 60 I

40

20

0 J


### *i-

. -. -’ ‘- -_ ,__
--__

- - -_ ,_

- .- _. 

### I

.

.

.

. l
. . . l . . I 

# .;--::1:---.-_

. ._

’

: 1



### . . 1 

### I I I 0 25000 50000 75000 100000 0 1 2 3 4 5



### RBCHI IogHl

120- Y=13.452+0.826X

r=0.376

, ‘.

, 

### * 100- I~ ” / /’ /’ ,’ /’ 80- _..*/’ l 

### ,

3 60 5

40

20

0

0 10 20 30 40 50



### EYTEX 5 120

100

80

3 60 I

40

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### \

logNRU34 Fig. 3(g). Fig. 3. Scatterplots showing the relationships between the MMAS for 12surfactant test materials and the scores from theleadlaboratories forthe ninetests, with regression linesand 95% confidence intervals. The order ofthe scatterplots and descriptions ofthe endpoints are as in Table 4.Further details ofthe 

### testsaregiveninAppendix2.

eye irritation scores within each eyeirritation test as the standard deviation. The eyeirritation potential of the test substances covered nearly the entire range that may be encountered in a rabbit eye irritation study (on the basis of MMAS =0-108) and the irritancy of the test substances was uniformly distributed across this entire range. The capacity ofthe invitro

### methods to predict eye irritation potential was assessed by preparing plots showing the relationship between the invivo

### MMAS and the invitro

### endpoints tested. Although comparisons were assessed for all the subsets of test substances shown inTable 3,plots for only theentire set of test substances (Fig. 2) and the surfactant subset (Fig. 3)are shown. The invivo

### MMAS areplotted on the ordinate, and the corresponding invitro

### endpoint
scores are plotted on the abscissa. Simple regression analysis was conducted for each in vitro 

### endpoint reported in this paper (see legend for Table 4 and Appendix 2).The results ofthis analysis are shown on each of the plots, and summary statistics are presented in Table 4A-G. The best-fit linear regression line is shown as a solid line, and the standard deviation for the regression line is shown as dotted lines (narrow lines, narrow spaces) closest to the regression line. The 95% confidence interval for the prediction ofan invivo

### MMAS (95% CI,& from a given invitro

### score is shown as dotted lines (broad lines, narrow spaces) furthest away from the regression lines. The equation for each regression line and the Pearson’s correlation coefficient is shown at the top of each figure. The results from only one laboratory (thelead laboratory) are shown inthetwo figures, because ofspace restrictions. Nevertheless, as isclear from Table 4,the results from all the laboratories in each group werehighly correlated with each other. Thus, the figures presented provide a reasonable representation oftheresults from allthe laboratories. The plots ofresults from the entire test set (Fig. 2) show that there isgenerally abroad scattering ofthe data points around the regression line. The correlation coefficients for each of the endpoints vary, depending on the endpoint measured, ranging from a high of0.616(SM31, Table 4A) toalowof0.012 (log DLl, Table 4A). Additionally, the 95% CI,, are relatively wide, frequently greater than f40. The plots showing the results from the various chemical subsets had similar relationships between the invivo 

### and alternative method data (figures not shown) with confidence intervals of similar width. The results for the surfactants were somewhat more encouraging, in that the correlation coefficients tended to be higher (Table 4D) and the 95% CIpd tended tobenarrower (Fig. 3) than was observed with the more diverse chemical subsets. The summary statistics from theregression analysis
are shown in Table 4A-G. Each section ofthe table lists the alternative method index measured, the number of samples tested in the invitro 

### assay, the

### 914 M.Ballsetal.



### number oftest substances for which no results were reported, the Pearson’s correlation coefficient, Spearman’s rank correlation coefficient, and the equation ofthe best-fit linear regression line for each subset of chemicals that underwent statistical analysis. The interlaboratory reproducibility of the in z?itro 

### methods was assessed by calculating the correlations ofthe invitro

### scores among the participating laboratories for each test. The correlation between laboratories is shown in a matrix for each endpoint in the extreme right-hand columns of Table 4. In most cases,theresults obtained inthedifferent laboratories
werehighly correlated with each other (RBCDL, log NRU, BCOPI; Table 4A). There were, however, endpoints where the between-laboratories reproducibility wasnot ashigh, which suggests poorer interlaboratory reproducibility (HETS, Table 4A). As noted earlier, a Mann-Whitney test was also conducted, to assess whether the rankings of the invitro

### scores for chemicals with MMAS values >59
were significantly different from those with scores ~59. The same test was performed for the sets of substances having MMAS values <25and >25.The Mann-Whitney method tests the hypothesis that there are directional differences in response between the data sets. A significant difference only indicates that the scores ofthetwogroups aredifferent. Itdoes not provide estimates ofhowlarge thedifferences are. Although the analysis indicated that there wereafew statistically significant separations in scores, inspection ofthescatterplots showed that there wasno clear association of invitro

### scores with either high or low invivo

### irritation potential (Figs 2and 3).The results of this analysis are therefore not presented in this report.

Discussion The purpose of this study was to determine whether one ormore non-whole-animal methods may be useful as a replacement for the Draize eye irritation testforidentifying either severely irritating test materials or for assessing the irritancy potential of chemicals across the entire measurable range. Nine promising alternative methods were evaluated using
areference setof60testsubstances inorder toanswer this question. The results from the alternative methods for 59 of these substances were compared directly with the invivoeye

### irritation potential ofthe testsubstances asmeasured intheOECD Test Guideline405procedure. Examination oftheplots comparing the relationships between the invivo

### and invitro 

### data indicate that there isconsiderable scatter ofthe data points around the regression line. Additionally, the data analysis shows that the 95% C& are wide, in many cases greater than f40. Thus, while the results of this study show that some alternative method endpoints may be capable ofpredicting the invivoeye 

### irritation potential (MMAS) oftest substances, theprecision ofthepredictions issolowthat the practical utility of such predictions is questionable. There are several factors associated with the study design and the state of the art that may help to explain why the irritancy predictions are not very precise. These factors include the choice ofmaterials included in the test set, the protocols that were assessed in the study, variability in the invivo

### data, the invivo

### endpoint usedtocompare with thealternative method data, and the data analysis procedures used to assist in quantification of method performance. The contribution ofeach ofthese factors tothe overall outcome of the study is discussed in the following paragraphs. One ofthe most important factors contributing to the results obtained may bethe diverse nature ofthe chemicals included in the reference set of test substances. One ofthe goals ofthe study was to determine whether the methods are useful for predicting irritancy potential of test substances representing many chemical classes and physical forms, and to determine the ability of the methods to assess irritancy potential without reference tobenchmark standards. The consensus at the International Expert Group meeting held in London in October 1992was that the test setneeded to beasbroad aspossible, in order to demonstrate the general applicability ofthe alternative methods for use in the regulatory setting. Accordingly, the reference set oftest substances was assembled tomaximize thediversity ofthetestchemicals. While itisclear that itwould bemost useful for regulators to have alternative methods that can test all substances without reference to benchmark controls, experience with currently available alternative methods in the industrial toxicology setting suggests theprocedures work best when their useislimited to specific classes of test substances that act through similar mechanisms of toxicity (Chamberlain and Barratt, 1995).Furthermore, the results from invitro 

### tests are usually interpreted with reference to data from benchmark test materials (see, for example, O’Brien et al., 

### 1994).Since the principal objective of the study was to determine whether currently-available alternative methods could replace the invivo

### test for regulatory purposes, it isnot surprising that the accuracy and precision of the predictions observed
waslow. Most invitro

### methods currently inusehave not been developed toprovide answers intheregulatory context. Rather, they have been developed to make assessments within limited classes, relative to benchmark controls. In effect, then, the methods tested inthis study wereevaluated inamanner which is not consistent with their use by many industry toxicologists during the in-house safety assessment process. The next issue to consider isthe individual protocols tested. In some cases, the protocols evaluated had not been used before. This isbecause significant changes were made in the test protocols in order to establish a common procedure that could be agreedEC/HO validation study on alternatives to the Drake test 915



### by each ofthe participating laboratories. Itisnot yet known whether the changes in procedure altered the predictive capacity ofthe methods. Ifthese changes did alter the performance of the methods, this may have affected the outcome ofthe study. In order to ensure that only welldeveloped methods are assessed in future studies, itwillbeimportant toinsist that the protocols be optimized, agreed, and tested, and that
aPrediction Model be established before an alternative method isaccepted into future validation studies (Balls et al., 1995;Bruner et al., 

### 1995;Curren et al., 

### 1995). The quality of the invivoeye 

### irritation data that
were used to assess the performance ofthe methods is another important issue. The invivo

### data used in this study werejudged against asetofcriteria formulated byan ECETOC Task Force (Bagley etnl., 1992; ECETOC, 1992).Thus, the quality ofthe data used
was ashigh ascould bereasonably expected without conducting large amounts ofadditional eyeirritation testing. One of the quality factors that it is not possible to assessunder the conditions ofthepresent study isthe accuracy and precision ofthe invivoeye 

### irritation scores used for comparison with the alternative method results. This isbecause there were no data on the interlaboratory reproducibility ofthe eye irritation scores on the majority of materials in the test set. This is important, because it is well known that the inter-laboratory variability in the Draize rabbit eyeirritation test can behigh (Weil and Scala, 1971). High variability in the invivo

### data can have considerable influence on the alternative method performance evaluated in avalidation study. Computer simulations show that the excellent performance of highly predictive alternative methods can beobscured to the point where they appear to perform at levels equivalent to or even below those observed in this study (Bruner et al., 

### 1995; Bruner and Carr; see Loprieno et al., 

### 1995).Given that the accuracy and precision ofthe invivo

### data arenot known, itmay not be possible to clearly assess the influence of data variability on the predictive capacity ofthe methods for this study unless additional in vivo 

### testing is conducted. Next, it is important to consider whether the MMAS isthe most appropriate invivoeye

### irritation parameter to use for comparison with the alternative method scores obtained invalidation studies. The use oftheMMAS hasbeen criticized asbeing inappropriate, because (1) it represents a composite score of responses from several tissues that does not accurately reflect the responses of the individual tissues, and (2)some alternative methods have been designed to predict only broad eye irritation classifications rather than irritancy according toasupposedly morerefined scheme such as the llO-point Draize scale. Despite these concerns, there isconsiderable support for the use of the MMAS as the most appropriate endpoint to use for assessing alternative method performance in the present study. This question has been addressed in the US CTFA evaluation of alternative methods for cosmetic eye safety testing. Feder etal.

### (1991)examined theextent ofassociation between the Kay-Calandra Irritation Score (Kay and Calandra, 1962) themaximum average (total) scores forthecornea, oriris, orconjunctiva (Williams etal., 

### 1982) the FHSA classification scheme (US Code of Federal Regulations, 1988) and days to clear (US EPA, 1984). Their analysis resulted in correlation coefficients ranging between 0.9 and 0.98 for comparisons between the MAS versus the Kay-Calandra score, cornea score, conjunctival score and iris score. These results led to the conclusion that any ofthese measurements could be used as a comparable indication of in vivo eye 

### irritation potential of test materials (Feder et al., 

### 1991; Gettings et al., 

### 1990). Thus, while the analysis of alternative method performance inthepresent study could have been carried out using any of the available scoring schemes, the high correlation between alloftheendpoints suggests that such an analysis isunlikely to markedly change the overall conclusions ofthe study. This conclusion should not, however, preclude further analysis ofthe results once the data are made generally available. Such post hoc

### analysis may provide leads that could be tested in future validation studies. The initial statistical analysis presented in this report has involved the use of linear regression techniques and calculation of95% CI,,. No attempt has been made to fit the data to more complex models. The analysis didnot useother models fortwo reasons. First, the simple plots ofthe invivo

### irritancy
versus the alternative methods provide aclear viewof the relationship between the invivo

### and invitro

### data obtained from the study. This clear viewallows users ofmethods toidentify materials for which the invivo 

### and alternative method results may be usefully related, and allows the identification of outlier data points. Exploration of the data presented in these plots may allow the development of models and hypotheses that can be tested in subsequent validation programmes. Secondly, the developers ofthe protocols tested inthe study did not define models to beused for assessing the performance ofthe alternative methods at any time before the start ofthe data analysis phase of the programme. In order to use more complex data analysis techniques, itwould have been necessary for participants to identify other models that could have been evaluated during the data analysis process. The data analyst could have explored the data in an attempt to identify potential useful models, but this is a subjective process that may not have yielded models that better fitthe data. Additionally, even ifthe analyst had identified such models, they would have to be assessed in a subsequent validation study in order to ensure the proposed model wasuseful generally, and not specific to the current data set. Once the data from the present study are made available, itisexpected that the data set will be explored fully by the participants in the

### 916 M.Ballsel al.



### study and by other interested parties in an effort to identify models that could be used for predicting inuivo

### responses from alternative method results. If such models are identified, they can be assessed in future validation studies. Finally, the analysis presented in this report only considered whether single endpoints obtained from the alternative methods could be used to predict the eyeirritation potential oftest substances. It ispossible that multiple alternative method endpoints may be combined in a manner that provides improved predictions ofeyeirritancy compared with the use of only single endpoints. To address this question, a multivariate analysis ofthe data from this study has been initiated. A summary of the results from this analysis willappear assoon asthe study iscompleted. The utility of such approaches is not yet clear, but early work suggests multivariate data analysis may be promising. The results of the ongoing multivariate analysis may provide useful models that also could be tested in future validation programmes.

conclusions In conclusion, the results ofthis study suggest that
some of the endpoints of the in vitro

### methods may have some capacity for predicting the eye irritation potential oftest substances. However, the confidence intervals associated with thesepredictions are sowide that the use ofthese methods may not be practical. The lack of precision in these predictions leads to obvious questions about how the methods can be used in the safety assessment process by industrial toxicologists. The most likely explanation for this dichotomy is that this study was not designed to answer the questions posed bymany oftheindustrial toxicologists who already usethemethods on adaily basis. As noted in the Discussion section, currentlyavailable alternative methods are rarely used in isolation bytoxicologists, but rather inconjunction with
a great deal of supplementary information. Most importantly, testing with alternative methods is usually conducted with relatively restricted subsets of test substances, which presumably act through similartoxicmechanisms, and theresults from alternative methods areinterpreted inrelation toexperience with well characterized benchmark controls. This study was principally designed to answer questions asked by regulatory toxicologists, who must assess a broad range ofchemicals that do not necessarily act through similar toxic mechanisms. Most often, regulatory assessments must also be made without reference tobenchmark controls. Since most ofthe alternative methods have been developed to meet the needs ofthe industrial toxicologist, it is perhaps not surprising that the performance of the methods in this validation study was, in aregulatory sense, disappointing. Itwill beimportant todeal with this dichotomy as a matter ofurgency ifthe new procedures are to be accepted by regulatory authorities. There are two possible solutions. The first would be for regulatory toxicologists toadopt amore flexible approach tothe
use ofalternative methods, ashasbeen suggested by, for example, Balls etal. (1990b) and Koiter (1994). This would require the acceptance of methods that have been shown to be useful for predicting the irritancy ofonly limited classes oftest substances that act through common toxic mechanisms, and for assessing the toxicity ofmaterials relative to appropriate benchmark controls. A precedent for this approach has been set by the US Department of Transportation, which recently accepted two invitro 

### tests forassessing skin corrosion forlimited classes of test substances. Ifthis approach were not deemed acceptable, the second solution would be to continue and accelerate the research and development process, in order to provide alternative methods that gave acceptably precise predictions for materials of all classes and without reference tobenchmark controls. This would be the more demanding of the two options, since it would require the development ofuniversal methods that were both capable ofassessing the major mechanisms ofeyetoxicity and suitable fortesting alltypes oftest substances. It is not likely that such research and development could be completed in the short term. If it could be agreed that the first solution were acceptable, then itshould bepossible intherelatively short term to identify the most important classes of test substances and benchmark controls to be evaluated and used in future validation studies. Studies focused on more-limited sets of test substances are likely tobemore fruitful, sincetheywillassesscurrent methods in a manner consistent with their presentday usebyindustrial toxicologists. With co-operation between industrial and regulatory toxicologists, it should be possible to identify approaches and procedures that willminimize animal use in the shortest possible time frame. In the meantime, the basic research needed toproduce more-generally applicable batteries of alternative methods must continue. As new, more highly predictive, alternative methods
are developed, based on better mechanistic understanding, they can gradually beincorporated into the eye safety assessment process. Ofcrucial importance tothesedevelopments would bethewillingness onthe part oftoxicologists, and especially industrial toxicologists, to publish their data (including the identities ofthe materials tested) in the peer-review literature. The issue of the precision and accuracy of data obtained from the inuiuoeye

### irritation test must also be addressed. If the invivo

### data used to assess the performance ofan alternative method arenot precise, then it is not reasonable to expect high levels of correlation between the in oiuo 

### and alternative method data, evenifthealternative methods aregood predictors of eye irritancy. Noisy data will obscure the adequate performance ofthe alternative methods

### EC/HOvalidation studyon alternativestotheDraizetest 917

being evaluated. Future studies must therefore determine the quality of the in vivo 

### data used in the assessment process, so that it is possible to put a proper perspective on the results obtained from a validation study (Balls et al., 1995; Bruner et al., 1995). Even ifitispossible toaccurately assessthequality ofthe invivo 

### data used in the studies, there will still be problems ifit is found that the in vivo 

### data are highly variable. The only solution to this variability problem will be to conduct more basic research, in order to develop procedures that improve the scientist’s ability to assess the true eye irritancy of test chemicals. While the Draize test and itsvariants have served acceptably wellup tonow aspredictors ofeye irritation potential for safety and regulatory assessments, the rabbit eye irritation test may ultimately prove to be an inadequate tool for the development of useful alternative methods. In order to properly address these deficiencies, it will be necessary to conduct basic research into howtobetter measure eye irritation potential, to make use ofdevelopments in QSAR analysis (Chamberlain and Barratt, 1993, as well as in in vitro 

### technology, and to assess the availability and utility of human workplace and marketplace experience data. The chemical and physical properties of the test materials used in this study were not given to the participating laboratories during the course of the practical work. This caused difficulties for some ofthe laboratories, since the testing of materials with alternative methods isnot normally conducted in the complete absence ofsuch information. For example, the solubility ofachemical in aqueous tissue culture media or its pH can dictate whether achemical isor is not compatible with a particular test method. In addition, it is known that the irritancy ofmaterials with certain chemical properties may be poorly predicted by agiven method. Thus, there isadanger that poor results with materials for which amethod isnot suited will mask good results for materials for which it is suitable. It will therefore be necessary in future studies to consider the degree ofblindness which is appropriate (sothat the tests being evaluated can be conducted properly and thus fairly assessed) and necessary (so that the materials cannot be identified before the completion ofthe study, and confidence in theintegrity ofthe evaluation can beassured). These problems are more easily solved when the range of toxicity required for the validation study is represented bymembers ofseriesofsubstances which are chemically related and which have similar physical properties. Anote ofcaution must berecorded with regard to the use of certain statistical methods in attempts to solve some ofthe difficulties associated with developing alternative methods. Statistical methods should only be seen as tools for assisting in the proper assessment of the results produced in validation studies. There is a growing tendency to use increasingly complex statistical methods asameans oftrying to identify associations between information provided by invivo

### and alternative methods by detecting relationships which are hidden within very noisy sets ofdata. The utility ofmodels developed on apost hoc basis must be verified by using rigorous procedures that provide convincing confirmation that they are themselves valid and generally useful, rather than being merely convenient forusewith the limited data set used to develop them. Finally, although the results ofthis study were not as positive as had been hoped and expected, the outcome does highlight the important problems that must be faced and overcome before nonanimal alternative methods can replace the invivo eye

### irritation test. Some ofthe many lessons learned
are already being put into practice. For example, the current COLIPA eye irritation test validation study has been designed to test only methods which incorporate clearly designed prediction models. In addition, the reference set of test substances is focused on ingredients and formulations with
a relatively narrow use, for example in cosmetic products. Thus, in the short term, the fastest progress will be made by evaluating alternative methods for more-circumscribed sets of test substances and by making use of testing strategies which involve the
use of benchmark controls. In the longer term, basic research must continue, in order to provide methods that will more accurately and more universally be able to predict eye irritation in humans.

Acknowledgements-The 

### Management Team for the EC/HO 

### studywouldliketoacknowledgethemajorcontributions madebymanyindividuals andinstitutions tothis complexendeavour,and,inparticular,tothank:EDivision oftheBritishHomeOffice,for encouraging the setting up ofthe study and for providing facilities for meetings ofthe Steering droup and the International Expert -Group; DGXIICI6 of the Eurouean Commission. for orovidine essential financial suppdrt; ECVAM for ‘suppl$ng sup: plementary financial support; the University ofNottingham forthefinancial management oftheproject, asECContractor; Dr Paul Brantom and his colleagues at BIBRA International, for thecoding and supply ofthe testmaterials; Dr David Love11and his colleagues at BIBRA, for the data collection and statistical analysis; DrArthur Walker andthe other members ofthe ECETOC Task Force and theChemicals Selection Committee, for all the effort they put into finding the 60test materials; the members of the Steering Group and theInternational Expert Group, fortheir advice; allconcerned in the 37participating laboratories, for their conduct ofthe practical work, and to their institutions, for their financial contributions; Dr Krys Ungar ofINVITOX, forassistance withthe testprotocols; the Molecular Devices Corporation, for financial support for one of the SM laboratories; the Millipore Corporation, for assistance with the supply of filter inserts for-the FL assay, and In Vitro International. for assistance with the SUDD~V of EYTEX kits; Dr Karen Atkinson and Dr Donald-Siraughan, for their helpful advice; and AMA Services and Dr Christoph Reinhardt, for assistance with the organization ofmeetings ofthe participating laboratories.918 M. Ball.s el al.

Gautheron P.. Dukic M., Alix D. and Sina J. F. (1992) Marenus K. D., Pape W. J. W., Roddy J. Schnetzinger R.. Silber P. M., Teal J. J., Weise S. L. and Gettings S. D. 

### (199 1)The CTFA evaluation of alternatives program: an

Bovine cornea1 opacity and permeability test: an invitro evaluation of in vitro alternatives to the Draize primary

assay of ocular irritancy. Fundamental andApplied Toxieye irritation test (Phase I) hydroalcoholic formulations; (Part 1) statistical methods. In Vitro Toxicology 4, 231 246.

i,ology 18, 4422449. Gettings S. D.. Dipasquale L. C.. Bagley D. M., Chudkowski M., Demetruhas J. L., Feder P. I., Hintze K. L., Marenus K. D., Pape W. J. W.. Roddy M., Schnetzinger R.. Silber P., Teal J. J. and Weise S. L. (1990) The CTFA evaluation of alternatives program: an evaluation of in vitro alternatives to the Drdize primary eye irritation test. In Vitro Toxicology 3, 293-302. Gordon V. C. and Bergman H. C. (1987) EYTEX, an in vitro method for evaluation of ocular irritancy. In Alternative Methods in Toxicology. Edited by A. M. Goldberg. Vol. 5. pp. 87-90. Mary Ann Liebert, New York. Kay J. J. and Calandra J. C. (1962) Interpretation of eye irritation tests. Journal 

### ofthe Society of Cosmetic Chemists 13, 281 289. Koeter H. B. W. M. (1994) Principles for a pragmatic approach to the regulatory acceptance of alternative tests. Toxicology in Vitro 8, 925930. Loprieno N., Bruner L. H., Carr G. J., Chamberlain M., Cottin M., De Silva 0. and Kato S. (1995) Alternatives in cosmetics testing. Toxicology in Vitro 9, 8277838. Luepke N. P. (1985) Hen’s egg chorioallantoic membrane test for irritation potential. FoodandChemical Toxicology 23, 2877291. Minitab (1992) Minitab Reference Manual Release 9. Minitab Inc., State College, PA. O’Brien K. A. F., Basketter D. A., Jones P. A. and Dixit M. (1994) An inGtro study of the eye irritation potential of
new shampoo formulations. To.xicology in Vitro 8, 257 -261. OECD (1987) Acute Eye Irritation/Corrosion. OECD Guideline 405 for Testing of Chemicals, 9 pp. In OECD Guidelinesfor Testing of Chemicals. OECD Publications Service, Paris. Pape W. J. W., Pfdnnenbecker U. and Hoppe U. (1987) Validation of the red blood cell test system as an in vitro assay for the rapid screening of irritation potential of surfactants. Molecular Toxicology 1,525-536. Prinsen M. K. and Koeter H. B. W. M. (1992) The enucleated eye test with eyes of slaughter animals as an alternative to the Draize eye irritation test with rabbits. Poster presented at 10th Anniversary CAAT Meeting, Johns Hopkins University. Baltimore, MD, April 1992. Ryan B. F., Joiner B. L. and Ryan T. A. (1985) Minitab Handbook. 2nd Ed. PWS Kent Publishing Company, Boston, MA. Shaw A. J., Clothier R. H. and Balls M. (1990) Loss of transepithelial impermeability of Madin-Darby canine kidney (MDCK) cells as a determinant of ocular irritancy potential. ATLA 18, 145-151. US EPA (1984) Labelling requirements for pesticides and devices, proposed rule. Federal Register 49, 37960. Weil C. S. and Scala R. A. (1971) Study of intra- and inter-laboratory variability in the results ofrabbit eye and skin irritation tests. Toxicology andAppliedPharmacology 19, 276-360. Williams S. J., Graepel G. J. and Kennedy G. L. (1982) Evaluation of ocular irritancy potential: interlaboratory variability and effect of dosage volume. Toxicology Letters 12, 235-241. REFERENCES
Atkinson K. A., Fentem J. H. and Balls M. (1994) ASurwI,

Baglky D. M., Botham P. A., G%dner J. R., Holland G , ofAlternathes totheDraizeEyeIrritation Testandoftheir

Kreiling R., Lewis R. W.. Stringer D. A. and Walker A. Current State of Validation. Report prepared for DG XI/C/6 of the European Commission, Contract

P. (1992) Eye irritation: reference chemicals data bank. 89/XI/A2-6. FRAME. Nottinaham.

Toxicology in Vitro 6, 4877491. Balls M., Blaauboer B., Brusick D.. Frazier J., Lamb D.. Pemberton M., Reinhardt C., Roberfroid M.. Rosenkranz H., Schmid B., Spielmann H., Stammati A.-L. and Walum E. (1990a) Report and recommendations of the CAAT/ERGATT Workshop on the vahdation of toxicity test procedures. ATLA i8, 313-326. Balls M.. Blaauboer B.J.. Fentem J. H.. Bruner L.. Combes R. D.; Ekwali B., Fielder R. J., Guillouzo A., Lewis R. W., Lovell D. P., Reinhardt C. A., Repetto G.. Sladowski D., Spielmann H. and Zucco F. (1995) Practical aspects of the validation of toxicity test procedures. The report and recommendations of ECVAM workshop 5. ATLA 23, 1299147. Balls M., Botham P., Cordier A., Fumero S., Kayser D.. Koeter H., Koundakjian P., Lindquist N. G., Meyer 0.. Pioda L., Reinhardt C., Rozemond H., Smyrniotis T.. Spielmann H., Van Looy H., van der Venne M.-T. and Walum E. (1990b) Report and recommendations of an international workshop on the regulatory acceptance of validated non-animal toxicity test procedures. ATLA 18, 3399344. Borenfreund E. and Puerner J. A. (1985) Toxicity determined invitroby morphological alteration and neutral red absorption. Toxicology Letters 24, 119.-224. Brantom P. G., Aspin P. and Thompson C. (1995) Supply, coding and distribution of samples for validation studies. ATLA 23, 348-351. Bruner L. H., Carr G. J., Chamberlain M. and Curren R. D. Validation of alternative methods for toxicity testing. Toxicology in Vitro. In press. Bruner L. H., Miller K. R., Owicki J. C., Parce J. W. and Muir V. C. (1991) Testing ocular irritancy int,itrowith the silicon microphysiometer. Toxicology inVitro5, 2777284. Burton A. B. D.. York M. and Lawrence R. S. (1981) The in vitro assessment of severe eye irritants. ‘Food and Cosmetics Toxicology 19, 471-480. Commission of the European Communities (I99I)Collabo- rativeStudy on theEvaluation ofAlternative Methods to the Eye Irritation Test, parts I and II. Dot. X1/632/91: V/E. I.13I.91. Commission of the European Communities, Brussels. Chamberlain M. and Barratt M. (1995) Practical apphcations of QSAR to invitrotoxicology illustrated by consideration of eye irritation. Toxicology in Vitro9, 543--547. CodeofFederal Regulations (1988) Title 16Section 1500.42: Federal Hazardous Substances Act Regulations, pp. 350-351. Curren R. D., Southee J. A., Spielmann H., Liebsch M., Fentem J. H. and Balls M. (1995) The role of prevalidation in the development, validation and acceptance of alternative methods. ATLA 23, 21I-217. Draize J. H., Woodard G. K. and Calvery H. 0. (1944) Methods for the study of irritation and toxicity of substances applied topically to the skin and mucous membranes. Journal of Pharmacology and Experimental Therapeutics 82, 377-390. ECETOC (1992) Eye Irritation-Reference Chemicals Data Bank. Technical Report No. 48. European Centre for Ecotoxicology and Toxicology of Chemicals, Brussels. Feder P. I., Lord0 R. A., Dipasquale L. C., Bagley D. M., Chudkowski M., Demetrulias J. L., Hintze K. L.,

### APPENDIX I

EC/HO Study-Membership of Steering Group, Expert Group and International Group Dr David Lewis (Central Toxicology Laboratory, Zeneca, Macclesfield, UK) Dr Hugo van Looy (OECD, Paris, France) DrDavid Love11

(BIBRA International, Carshalton, UK) INTERNATIONAL GROUP 

### Dr Wolfgang Pape (Beiersdorf AG, Hamburg, Germany) Membershipofthe Steering Group:
Professor Michael Balls (FRAME and University ofNottingham, UK) Mr Menk Prinsen (TNO, Zeist, The Netherlands) Dr Jean-FranGois Regnier (ATOCHEM, Paris, France)

Dr Philip Botham (Central Toxicology Laboratory, Zeneca, Macclesfield, UK) Dr Mark Chamberlain (Environmental Safety Laboratory, Unilever Research, Sharnbrook, UK) Dr Odile de Silva (L’Or&al, Aulnay-sous-Bois, France) Dr Lewis Smith (MRC Toxicology Unit, Leicester, UK)

Dr John Gardner (Shell Research Centre, Sittingbourne, UK) Dr Anna-Laura Stammati (ISS, Rome, Italy) Dr Winfried Steiling (Henkel KGaA, Diisseldorf, Germany)

Mr Tim Smyrniotis (DGXI/A/2, EC, Brussels, Belgium) DrNeil Wilcox (US Food &Drug Administration, Rockville, MD, USA)

Dr Donald Straughan (Home Office,London, UK) Dr Arthur Walker (ECETOC, Brussels, Belgium). APPENDIX 2
Additional participants at the June 1992 Meeting of theExpert Group: Details oftests involved in the EC/HO Study
1. The redbloodcell haemolysis test Mr Ian Archbold (Home Office, London, UK) Dr Monique Adolphe (EPHE, Paris, France) Dr Leon Bruner (Procter & Gamble, Cincinnati, OH, USA) a. Principle of themethod



### Dr Robin Fielder (Department ofHealth, London, UK) Dr Hermann Kogter (OECD, Paris, France) Professor Horst Spielmann (ZEBET and Free University of Berlin, Germany).
AdditionalparticipantsattheOctober1992Meetingof the International Expert Group:
MSKaren Atkinson (FRAME, Nottingham, UK) Dr Ih Chu (Bureau ofChemical Hazards, Ottawa, Ontario, Canada) The method isbased on that ofPape et al. 

### (1987) and Lewis et al. 

### (1993). Certain classes of chemical irritants may cause damage tocellplasma membranes and/or denaturation ofmembrane proteins and other cellular proteins. Such events can be correlated with the initial inflammatory response in tissue irritation and with changes in protein conformation, such as those that occur in opacification of the cornea. The biological endpoints of cell lysis and protein denaturation has been used singly or in combination to predict the ocular irritancy of certain classes of chemicals (mainly surfactants). b. Basicprocedure, endpoints and endpoint measurement 

### Dr David Clark (Environmental Safety Laboratory, Unilever Research, Sharnbrook, UK) Dr Rodger Curren (Microbiological Associates, Rockville, MD, USA) Professor Anthony Dayan (St Bartholemew’s Medical College, London, UK) Dr David Esdaile (RhBne-Poulenc, Valbonne, France) Dr Julia Fentem (FRAME, Nottingham, UK) Dr Pierre Gautheron (MSDChibret, Riom, France) Dr Kailash Gupta (US Consumer Product Safety Commission, Bethesda, MD, USA) Mr Michael Head (Home Office, London, UK) Dr Richard Hill (US Environmental Protection Agency, Washington, DC, USA) Dr Patricia Koundakjian (Health & Safety Membrane damage is assessed by measuring the leakage of haemoglobin from red blood cells incubated with test material under standard conditions. The haemoglobin is detected spectrophotometrically (at 541nm). Protein denaturation is measured by determining the reduction in absorbance at 541nm (oxyhaemoglobin absorption maximum) with increasingconcentration oftestsubstance. Alldeterminations
are made relative to concurrent control sample, totally lysed with distilled water. Initially, a range-finding assay is conducted over awide range oftest substance concentrations. There
can be various outcomes of this initial study:

Executive, Bootle, UK) i. No denaturation or lysis. ii. Lysis in the absence of denaturation. iii. Lysis and protein denaturation. iv. Denaturation alone. EC/HO 

### validation studyon alternativestotheDraizetest 919920 M. Balls etal.

The degree of any denaturation can be determined directly from the range-finding study at the predetermined concentrations used. Lysis is assessed accurately at concentration intervals selected from the results of the range-finding study.

c. Expression 

### qfresults Membrane damage (lysis) is expressed as the H,, value (the concentration causing 50% haemolysis relative to the totally lysed sample). Denaturation is expressed as Dr,,,, (the lowest concentration causing denaturation-a 10% decrease in absorbance at 541nm) and Dhlax (the maximum percentage denaturation seen at any concentration tested).
d. Application of results H,, and DLoware inversely correlated with MMAS; DMaxis positively correlated with MMAS. Most of the materials used in initial evaluations of this method were surfactants. The development and use of lysis and denaturation are therefore specific to this class of chemistry. In practice, the red blood cell test has been used with other non-animal approaches and structure activity information to build aprofile ofthe test chemical relative to standards of known ocular irritancy.

e. Dijiculties experienced and limitations of the method As with all cell-based assay systems, protocols must be prepared that are able to handle watersoluble and water-insoluble test materials. Very limited evaluations have been carried out of suitable vehicles for use with the red blood cell assay.

2. The EYTEX method

a. Principle of the method Small quantities of test sample, when presented to EYTEX reagent, produce aturbidity which isdirectly proportional to the irritancy of the sample. This turbidity is produced by changes in conformation and degree of hydration of the EYTEX reagent and mimics the response of the protein in the cornea during cornea1 injury or ocular irritation. The turbidity, measured in a spectrophotometer, is compared with that produced by eye irritant standards of known Draize score. The EYTEX Draize Equivalent (EDE) score is then determined from a calibration curve. b. Operation of the method Three protocols, the Upright Membrane Assay (UMA), Rapid Membrane Assay (RMA) and Alkaline Membrane Assay (AMA), were used in this study. The UMA protocol is abroad-range screening protocol for samples with a 10% dilution pH < 8.0. The AMA protocol is used for samples with 10% dilution pH > 8.0. The RMA protocol was used for surfactants and when a sample did not qualify in the UMA protocol. The shorter incubation time, 5hr cf. 24hr for the UMA protocol, minimized inhibition and interference effects. UMA, RMA and AMA kits were obtained from InVitro International (Irvine, CA, USA), care being taken to ensure the use only of kits from the same batch of EYTEX reagent. The EYTEX reagent is a lyophilized powder containing a range of proteins and lipids along with buffer salts, which is reconstituted by addition of distilled water. Calibration and quality control (QC) samples, dilution buffer activator and inhibition check reagents are also included in the kit. Optical density (OD) ismeasured on amodel 60/60 calorimeter (Jenway. Great Dunmow, Essex, UK) with a 400 nm interference filter.

c. Analysis of unknowns If the sample was designated a surfactant, a fivevolume assay was used. 20,30,50 and 100~1of 100% sample and 100~1 of a 10% dilution were analysed in the RMA. If the result did not qualify with the RMA protocol, the sample was not qualified for analysis. All other samples which were neutral or acid unknowns, were run at 20, 30, 50and 100~1with the UMA protocol, and, if not qualified, then run with the RMA protocol. If alkaline, the samples were run with the AMA protocol. If a sample could not be analysed at loo%, then it was not qualified by this method for inclusion in the validation programme. Generally, non-qualified samples would be run at a lower concentration, as determined by a concentration screening assay. This approach was not followed in this study, since the inviuodata were only available on 100% samples. Each sample was assayed in duplicate. The results were only accepted after achieving two qualified results in the appropriate protocol. Detailed instructions for performing each of the three protocols are given in the ‘Directions for Use’ (DFU) in Gordon (1993). All qualification assessments and calculations of the EDEs were carried out using the Data Analyses Quality Control Program (DAQC-ES), available from InVitro International, with automatic data entry and average range updating. Qualification of sample data is the foundation stone of the EYTEX system. It is the concept which
ensures the viability of intralaboratory and interlaboratory agreement since it forces the user to discard non-conforming results and follow the standard procedures precisely. Qualification is the process whereby an assay is considered technically valid if, and only if, it adheres to specified performance standards. These standards are the calibrators and QC samples used in each assay. Performance is acceptable only if the scores for these standards lie within predefined acceptance ranges initially defined in the DFU and subsequently based on the averageEC/HO validation study on alternatives to the Draize test 921



### of the last 10 qualified assays obtained with the untouched material in the top ofthe bullet system. After every 10 new assays, the acceptance -for example 100mg added, but only ranges for calibrators and QC samples are updated. 50mg accessible. The EYTEX system requires qualification of the assays and sample. The sample can qualify only if the assay, that is calibrators and QC samples, is satisfactory. Often, the assay can qualify, but not the sample. This can be due to numerous causes, for example physical reasons, such as membrane damage, or chemical reasons, such as inhibition or interference, where the shape of the dose-response
curve does not conform tothat required bytheDFU. Inhibition is the apparent reduction in OD with increasing dose of sample. It iscaused by the solubilizing effect of the sample itself (particularly with surfactants) on the coagulating EYTEX reagent, resulting in a lower estimation of irritancy. The EYTEX protocols are vague in this respect and should be tightened up. Interference and inhibition (particularly noticeable with surfactants) can cause severe underestimation. Overcoming this problem requires a concentration
screen tobecarried out before the assay todetermine the optimum test concentration for aqualified assay. This was not allowed for in this study-immediate non-qualification and exclusion followed. The concentration response is a function of chemical type rather than physical type and thus isdifficult to allow for when running blind samples. Sample qualification problems are normally overcome byrepeating the assay at alower concentration, selected from aprior concentration screen. However, concentration screening of samples was not allowed in this validation study for reasons given earlier. The results of an EYTEX assay is the EDE, read-off (or calculated by the DAQC-ES program) directly from a calibration curve of Draize 24-hr maximum score versus OD, plotted from the known calibration standard run at the same time as the sample. The EDE may then be used to predict the irritancy potential ofthe sample by comparison with in vivo data and classifications. Inhibition and interference are the most likely
causes of ‘low’scores ofmaterials with MMAS > 51. With the current EYTEX system, the ‘top’ calibration standard has aDraize 24-hr score of51,and this produces a turbidity which isvery near to complete absorbance for the spectrophotometer. Samples with MMAS > 51would therefore still only give an EDE of 251,as aresult giving aplateau at 51in the plot ofEDE versus invivo MMAS.

d. D@culties with the method The following are known to be problems: It is also possible that a sample with an MMAS much higher than 51,but which caused interference
or inhibition and subsequent reduction in OD, would be severely underestimated if inhibition was not recognized. Thus, it could be argued that the incorporation of invivodata >51MMAS isinvalid for the EYTEX system since this must have an effect
on any correlation studies. Some samples can attack the plastic cuvettes used in the measurements. Adsorption of the turbidity can occur on thecuvette surface. Here,
use of a special glass cuvette is recommended. Coloured samples often need to be measured at different wavelengths. Not all laboratories recognize when this isnecessary; this can lead to discrepancies in results. pH variation attheborderline region (8.0+ 1.0) could lead to one laboratory using the AMA (pH 2 8.0) and others using UMA or RMA (pH c 8.0) protocols. Handling of solids is difficult with the current bullet membrane holders. Depending on the density of the solid, it is sometimes difficult to get the required 100mg into the container. Different laboratories may treat thisdifficulty in different ways, for example: 

## (4 @I



# w Stop when the bullet is full, for example when 75mg in; physically press down the solid to allow
more sample in-from 75to 80-90 mg-but with the possibility of membrane damage;
or pile material up on top-if soluble, lower material can dissolve leaving a bridge of Despite all the above difficulties, EYTEX works well with many types of materials as long as the aforementioned precautions with a concentration
screen are taken into account.

e. Limitations ofuse ofthe EYTEX System Experience has shown that Mg-neutralized surfactants are greatly overestimated, particularly when testing on their own. This problem is not as great in formulation as it is with other surfactants or materials. Carbohydrate materials, particularly multicarboxylated ones, are also overestimated by the EYTEX system. Recognition ofthe above problems gives an indication ofwhy the EYTEX test gives the best results with samples which are: insoluble inwater; solutions;
or liquids, but relatively poor results with solids, surfactants and water-soluble materials.

3. The bovine corned opacity/permeability (BCOP) test



### a. Principle ofthe method In the BCOP test,bovine corneas from eyesfreshly collected from a local abattoir are used to assess the eye irritating properties of test materials. Two end-922 M. Ballset ul.

points are determined, the opacity and permeability of isolated corneas. The corneas are freshly prepared and mounted in special holders, which consist of an anterior and aposterior chamber. Both chambers are filled with simple culture medium and test material is applied to the anterior chamber of the holder. Corneas are exposed for 

### Ihr. Change in opacity was the only endpoint determined when the BCOP assay was originally developed. Later, measurement of permeability was added, as visualized by the application of a fluorescent dye.
h. Bask procedure, endpoints and endpoint measurement Opacitymeasurement. Change in light transmission passing through the cornea is determined in an opacitometer (Electra Design, Riom. France) and expressed as a numerical opacity value. The opacity values obtained for control and exposed corneas represent the absolute opacity for a given cornea. Permeability measurement. Determination of this endpoint is performed immediately after the opacity measurement. The medium was removed from both chambers of the holder. It is replaced by fresh medium in the posterior compartment and by 

### Iml fluorescein solution (0.4% for liquids and surfactants, 0.5% for solids) in the posterior chamber. Corneas
are then incubated in ahorizontal position for 90min at 37‘C. Medium is removed from the posterior chamber and the OD is determined in a spectrophotometer at 490 nm. Special protocols for solids and surfactants have been developed, in addition to the standard protocol for liquids.

c. Expression qfresults Opacity values are corrected for basal opacity. Each cornea of the experimental group, including positive controls, is corrected for the mean value of saline-treated corneas (negative control) and at the given time point (corrected values). In the permeability measurements, the mean OD of saline-treated corneas is determined and the individual value measured for each cornea iscorrected by the mean for saline treatment (corrected value). The BCOP score was derived empirically. It is calculated for each cornea according to the following equation:
BCOP score = opacity + (permeability OD value x 15)
For each test material, the final invitroscore is the
mean + SD determined with three corneas. d. Application ofresults The lead laboratory suggested the following classification scheme in the SOP for the EC/HO study, which is based on the Kay and Calandra classification scheme for data obtained invivoin the Draize eye irritation test in rabbits: from O-25 = mild irritant; from 25.1-55 = moderate irritant; from 55.1-80 = severe irritant; and r 80.1 = very severe irritant. The lead laboratory also suggested a cut-off value of 200 for BCOP data evaluation in the EC/HO validation study. The other Iaboratories agreed to this cut-off value since BCOP scores >80 give the same level of information as far as severe eye irritating properties are concerned. In an EU validation study carried out in 12laboratories with 52 test chemicals, an in vitro/in vivo correlation of 0.73 was obtained between BCOP and maximum average score (MAS) values (Gautheron 

### etal., 1994). A linear correlation between MAS and BCOP scores has not been assumed by those using the BCOP assay. The BCOP assay is in routine use for in-house safety assessment in laboratories in France and Belgium. It is also used for regulatory purposes in a few companies to classify and label chemicals as ‘severely irritating to the eye’ according to EU regulations (i.e. as R41).

e. D@cufties experienced andlimitationofthemethod In the EU validation study, all four false negatives
were solids and three of four false positives were liquids (Gautheron et al., 1994). Thus, the methodology may have to be modified to cover all the physical forms of test substances. Neutralization and buffering of solids by the culture medium, which is used to solubilize solids, may also have to be taken into account. There is
a tendency for ‘overestimation’ of the irritating properties of alcohols tested in the BCOP assay.

4. 

### The HET-CAM assay

a. Principle of themethod In the HET-CAM assay, test materials are applied to the vascularized chorioallantoic membrane (CAM) ofembryonated chicken eggs. It isassumed that acute irritating effects on the small vessels and protein membranes of this soft tissue membrane are similar to effects induced by the same chemicals in the eye. Preliminary results published in the IRAG (1993) validation exercise by the CAM-based assay subgroup indicated an acceptable correlation between endpoints and/or scores determined on the CAM and effects in different tissues of the rabbit eye in the Draize eye test, but only for surfactants. b. Basicprocedure, endpoints and endpoint measurement There are several variations of the original HET-CAM assay developed by Luepke (1985). In most ofthe protocols, three endpoints are determined for assessing the irritating properties of test materials
on the CAM, namely, haemorrhage, iysis and coagulation.EC/HO validation study on alternatives to the 

### Draizetest 923

Depending on the test material involved, several HETCAM assay protocols have been developed, in which either atime point isdetermined at each ofthe endpoints evaluated after application ofundiluted or 10% diluted testmaterial orthe threshold concentration ofappearance ofthe three endpoints isassessed. Different scoring systems have been developed in each ofthe HET-CAM assay protocols to take into account asmuch aspossible ofthe information given by the three endpoints. The Standard Operating Procedure (SOP) used to assess irritating potential in the HET-CAM assay in the EC/HO validation study is an in-house protocol developed by Henkel KGaA (Dusseldorf, Germany). In-house validation was based on surfactants and their derivatives with low eye irritation potential,
as shown in the data set for about 100 chemicals submitted for the IRAG validation exercise. Two protocols developed by Henkel were used in the EC/HO study, one for transparent test materials, through which reactions on the CAM can be observed. The other is for liquids and solids which are not transparent and thus donot permit such acareful observation of effects on the CAM. Protocol for transparent materials-reaction time method. 

### The test chemical isapplied to the CAM for sixeggsonday 9ofembryonation. The reaction times
are observed for the three endpoints, haemorrhage, lysisand coagulation, within a 5-min (300set) observation period and recorded in acomputer file.Acomputer program automatically calculates an irritation index for soluble materials. On each day of testing, the same procedure iscarried out with a5% solution oftheinternal reference chemical ‘Texapon ASV’, an anionic surfactant, which serves as a control for the performance ofthe HET-CAM assay and asabenchmark chemical for evaluating theirritation potentials of test materials. Protocol for non-transparent materials-endpoint assessment. 

### Test chemicals are applied to the CAM of six eggs on day 9 of embryonation. After 3min, the test material is carefully rinsed off the CAM, which, after another 30set, isexamined for the three endpoints, haemorrhage, lysis and coagulation. Each endpoint is scored in the following manner: 0= no reaction; 1= weak reaction; 2= mild reaction; and 3= strong reaction.

c. Expression ofresults Evaluation of reaction time method-calculation of the Q score. 

### Evaluation of irritation potential is determined bycomparing theirritation index ofatest chemical with that ofthereference chemical ‘Texapon ASV’, and isexpressed as the ‘Q score’. Ifthe effect of a chemical is identical to that of the benchmark Texapon, Q is 1.0.Ifit islower, the test material is lessirritating, and ifit ishigher, itismore irritating. Experience at Henkel suggests the following interpretations for the reaction time method: Q< 1.5= non-irritating material; Q> 1.5< 2.0= moderately irritating material; and Q> 2.0= severely irritating material. A cut-off value of2.5is suggested by the SOP for data evaluation ofthe HET-CAM assay within the EC/HO validation trial. Evaluation system for the endpoint assessment method--S score(basedonexperience atHenkel). 

### The most sensitive endpoint is used for evaluation and thisistheone providing thehighest scores.The scores recorded forthis endpoint are summarized forthe six eggs; the summarized maximum score of six eggs is the Sscore. Asthe highest single score for one eggis 3,the maximum score for six eggs is 18. Evaluation of the S score for non-transparent materials: S< 6=

### non-irritating material; S> 6< 1.5

=moderately irritating material; and S> 15= severely irritating material. No cut-off value isproposed in the SOP.

d. Application ofresults 

### The HETCAM is an established method in many cosmetics companies, particularly in France and Germany, for the in-house safety assessment of
raw materials and formulations. The invitro/in vivo 

### correlation has been very good in the area ofmild to non-irritating test materials. Different protocols are used in various in-house testing strategies. The HET-CAM is the most important invitro

### assay within various batteries used to assess eye irritation potential in many cosmetic companies. Regulatory authorities in Germany have agreed to accept data obtained in the HET-CAM assay for classifying and labelling chemicals as ‘severely irritating to the eye’ according the EU regulations (i.e. as R41). However, the data submitted for that purpose were obtained with a different protocol (Spielmann et al., 

### 1993).

e. Difficulties experienced and limitations of the method 

### The HET-CAM protocol used in the EC/HO validation trial for assessing the irritation potential of test chemicals relies entirely on a single benchmark chemical, an anionic surfactant, which appears to allow discrimination between non-irritant and mild irritant organic chemicals. No published information is available on how to evaluate the irritation potentials ofseverely irritating or corrosive chemicals. It isnot absolutely clear when to use the reaction time method, which generates Qscores, and when the endpoint method should be used, which generates S
scores.Moreover, no information has sofarbeen published on how data produced with the two methods should be compared. It is also not clear when and how dilutions should beused, or howtocompare the results obtained with different dilutions with data924 

### M. Balls efal



### generated intheDraize eyetestinuivo

### with undiluted i. The amount offluorescein which leaks across the materials. cellular barrier Sticky test materials cannot be tested in a reproducible manner in most CAM-based assays. (%FL) =z x 100 X


### 5. The fluorescein leakage test 

### where

u. Principle qfthemethod 

### This method isbased on that ofTchao (1988).The loss oftrans-epithelial impermeability ofaconfluent monolayer ofMadin-Darby canine kidney (MDCK) cells following exposure to irritant materials is measured by determining the degree of leakage of fluorescein across the cellmonolayer. In the FL test. MDCK cellsaregrown toconfluence onmicroporous filters and exposed to high concentrations of test material for Imin. The test isbased on the ability of the chemical to damage tight junctions in the confluent monolayer. The degree ofjunction disruption results in a proportionate increase in permeability, measured as the passage of the relatively non-toxic dye, fluorescein, across thebarrier. This ‘leakage’can be measured spectrophotometrically. The FL test is considered tomodel thedisruption oftheintegrity of the cornea1 epithelium by chemicals which may be potentially irritant to the eye. m= 

### the mean fluorescence leakage intensity
across the treated cellular barrier, .Y=the mean maximum leakage fluorescence intensity (through insert with no cells) and )‘ =the mean 0% leakage fluorescence intensity (across untreated control cellular barrier).
ii. The concentration of chemical which causes 20% damage to the cell layer:

FL Xl

## =(20-A)x t”,-MA)+M~



## (B-A) where

A = 

### %fluorescein leakage <20%; 3 = %fluorescein leakage > 20%; M, = 

### concentration (mg/ml) of A; and MB=

### concentration (mg/ml) of B.

b. Basic procedure, endpoint and endpoint measurement 

### MDCK cellsaremaintained inculture and exposed for a short time period, for example, Imin, to five fixed concentrations oftest compound. The damage caused is determined by the amount of fluorescein which leaks through the confluent layer over a set period of time. This is compared with two control values: the amount offluorescein that leaks through
an untreated confluent monolayer, referred to as0% leakage or the blank, and the amount offluorescein which leaks through an insert on which there are no cells, referred to as maximum leakage. The percentage ofleakage isexpressed relative to these controls for each of the set concentrations. The fluorescence intensity is determined by using a CytoFluorTM fluorescence measurement system (Millipore Ltd), at excitation and emission wavelengths of 485 and 530nm, respectively. Each chemical is tested in triplicate, and the test is repeated on at least three separate occasions, that is,using freshly-prepared test sample dilutions and different starting cell cultures. If the FL,, is not reached at a concentration greater than lOOmg/ml, inclusive of the undiluted material, then the maximum percentage fluorescein leakage should be quoted along with the concentration ofchemical causing it,forexample 100mg/ml (FL 18.5%), or undiluted sample with calculated concentration of 955mg/ml (FL 3.2%). Because of the individual characteristics of each Cytofluor, it is suggested that a sensitivity is used which willgive amaximum fluorescein leakage value of>4000(but <9999).For an assay tobeconsidered qualified, fluorescence values should be: 0% leakage, y< 300;x- y= 3500- 6000. d. Application ofresults 

### The FL,, value isused to rank the toxicities ofthe test chemicals. The lower the FL,, value, the more toxic the material. If only the initial effect is to be used for assessment, as in the EC/HO study, then theFL,, value can beused to classify the chemical in terms of its irritancy potential, that is, as severely irritant (R41), irritant (R36) ornon-irritant (no label), as suggested below:

c. Expression ofresults 

### Results areexpressed interms ofthe concentration (mg/ml) oftest sample which causes 20% fluorescein leakage (FL,,) across the treated cell layer, in comparison with the amounts of fluorescein that leak through an untreated confluent cell monolayer (0% leakage) and the microporous filter insert alone (maximum leakage). The FL,, value for each test concentration is calculated as follows: 

### 6) (ii) (iii) An FL,, of less than lOOmg/ml is likely to indicate R36 or R41. An FL*,,of greater than 750mg/ml or undiluted material islikely to indicate no label. Ifthe FL,, of the chemical lies between 100 and 750mg/ml, the chemical could be R41 if thereisfurther deterioration when theFL test is performed again after 72hr, or R36 if recovery is noted.

### EC/HOvalidation studyon alternativestotheDraizetest 925

e. D@culties experienced and limitations of the method 

### One ofthegreatest difficulties experienced concerns the handling of viscous, non-toxic materials, since they can be almost impossible to remove after the initial I-min exposure. As viscosity increases, there
can be an initial increase in leakage of fluorescein with increasing concentration, followed by adecrease with further increases in test chemical concentration. This results inaparabolic-shaped curve. Similar curves may also result through the binding ofchemicals, for instance cationic surfactants such as benzalkonium chloride, to the microporous membrane, which may impede the passage offluorescein through the filter. Suchmaterials may alsobind directly tothefluorescein solution itself. Strong acids or alkalis may also cause damage due to pH effects alone rather than to specific chemical toxicity. Care should be taken when transferring a filter insert between 24-well plates to ensure that bubbles do not form under the bottom of the insert. Such bubbles may impair thepassage ofnutrients from the medium to the cell monolayer, leading to restricted growth, or during the fluorescein leakage procedure, may impede the passage offluorescent, thus leading to an underestimation of leakage. During testing procedures, in particular during the washing/aspiration cycles,themicroporous membranes ofthe filter inserts can be damaged ifcare is not taken, leading to false results. This can be determined by examining the inserts before the beginning and end ofthe initial procedures. At the end ofthe assay the filters should be examined closely for damage. There arecertain limitations with theassay, mainly concerning the solubility of the compound to be tested: 

## (9

(ii)

(iii)

(iv)

(v) Only materials which are either in solution or suspension can betested by using the FL test; solids cannot be tested since they cannot be easily removed from the cell surface after the exposure period. Non-aqueous materials or materials insoluble in mineral oil cannot be tested, unless presented asspecificmicroemulsion formulations. Some materials are incompatible with the plastic O-ring or microporous membrane of the filter insert, for example acetic acid is incompatible with the HA microporous membrane, but not the Anopore membrane. Corrosive materials at the normal set dose ranges are likely to kill the cell monolayer; sinceboth theprofile and rate ofrecovery aids in interpretation of the data, mild materials
are most suitable for testing with this assay. Highly volatile materials need to be kept in contact with the cellular layer, for example by sealing with mineral oil. (vi) Certain materials, forexample cationic surfactants, can bind tothe microporous membrane and directly affect the degree of fluorescein leakage.

6. The isolated, enucleated chicken eye test (CEET)

a. Principle of themethod 

### The chicken hasbeen found tobethemost suitable species ofabattoir animal to act as an eye donor for the assessment of eye irritation potential of test materials. Since 1992,the CEET has been incorporated in standard contract toxicity testing atthe TN0 Nutrition and Food Research Institute asaprescreen for the Draize eyetest, with very satisfactory results. The effects of test materials are assessed following application tothecorneas ofenucleated chicken eyes. b. Basicprocedure, endpoints and endpoint measurement 

### Heads of spring chickens are collected at a local abattoir. Within 2hr of killing, enucleated eyes are placed in a superfusion apparatus, which keep the eyesin good condition for at least 6hr. The test compound isapplied onto the cornea ofatleast three eyes in one single dose of either 30pl (liquids, gels and pastes) or 30mg (solids) for 10sec. Before dosing, each eyeprovides its own baseline values for the assessment of the cornea1 effects. Control eyes, one per test run, are only used for checking the experimental conditions. The control and test eyes are examined for cornea1 thickness and swelling at 0, 30, 75, 120, 180and 240min after treatment, and results are recorded according to a fixed scoring system. Fluorescein retention by damaged epithelial cellsisscored at30min post-treatment only. Allexaminations are carried out with a slit-lamp microscope, such asisnormally used in human ophthalmoscopy.

c. Expression ofresults 

### The mean percentage ofcornea1 swelling and mean cornea1 opacity value for all test eyes are calculated for the observation points at 30, 75, 120, 180 and 240min. The mean fluorescein retention value for all test eyes is calculated for the observation point at 30min only. If desired, or for test substances that have adhered to the cornea, fluorescein retention
can be determined at 240min or whenever the test compound is removed. Morphological effects include ‘pitting’ of cornea1 epithehal cells, ‘loosening’ ofepithelium, ‘roughening’ of the cornea1 surface and ‘sticking’ of the test substance to the cornea. These findings can vary in severity and they may occur simultaneously. The classification of these findings is subjective and depends on the interpretation of the investigator. On the basis ofthe severity ofthe observed findings for cornea1 swelling, cornea1 opacity and fluorescein retention, the effectsare divided into four categories:926 

### M.Ballseral

I=none; II = slight; III =moderate; and IV= severe. Classification into the four categories is conducted according to the following method:
Cornea1swelling

### : Mean cornea1 swelling (%)

- 5-5 6-12 13-18 (> 75min after treatment (< 75min after treatment) 19-26 27-32 (> 75min after treatment) (<75min after treatment) >32 Category I II II III III III IV IV

Cornea1 opacity

### : Mean max opacity score 0.0-0.5 0.6-1.5 1.6-2.5 2.640 Category I II III IV
Fluorescein retention

### : Mean fluorescein retention score Category (30min after treatment) 0.0-0.5 I 0.6-l .5 II 1.6-2.5 III 2.6-3.0 IV d. Application of theresults 

### Based on the maximum mean scores defined for cornea1 swelling, cornea1 opacity and fluorescein retention by damaged epithelial cells, the irritation potential ofthe compound, ranging from not irritating to severely irritating, isassessed according to the CEET classification system. The ex oivo

### irritancy classification is assessed by reading the irritancy classification that corresponds to the combination of the categories obtained for cornea1 swelling, cornea1 opacity and fluorescein retention, which are presented in the scheme below.

ClassiJcation 

### A. Not irritating Combinations ofthe four categories 

### 3x1 2xI, 1x II
B. Slightly irritating a. 3xII 2xII, 1xI 1xI, 1x II, I x III’ b. 2xII, 1xIII 2x 1, 1xIV’
C. Moderately irritating 3xIII 2xIII, 1xII 2xIII, 1xIV 2xIII, 1xI’ 2xII, 1x IV’ 1x II, 1xIII, 1x IV1 D. Severely irritating 3x IV 2xIV, 1x III 2xIV, 1xII’ 2xIV, 1x I’ immediate cornea1 opacity score 3 cornea1 opacity score 4 severe loosening ofepithelium ‘Combinations of categories less likely to occur. To determine therelevance oftheCEET parameters in relation to the in viuo 

### tissue scores, statistical analyses of the CEET and in viuo 

### data can be performed by means of X/I’ plots with Pearson’s correlation coefficient. With the results ofthe CEET,
an irritation index can be calculated. The genera1 principle ofthis index isthe summation ofthemaximum mean scores ofthe three parameters measured, namely cornea1 swelling, cornea1 opacity and fluorescein retention. The opacity and fluorescein scores are equally weighted in the index, when compared with the maximum % swelling that can be obtained in this assay. At TNO, this isabout 60%. Therefore, the maximum mean score for the cornea1 opacity (score 4)and fluorescein retention (score 3)obtained with agiven compound are multiplied by a factor of 20. Thus, the irritation index could range from 0to 200. In addition, the individual components of the index are also compared with the inuiuo

### data. According to Directive 83/467/EEC, Part II (B)of Appendix 6, Dangerous Substances Directive, 5th Adaptation, the invivo

### irritancy grades are divided into three classes: non-irritating (NI), irritating (R36) and severely irritating (R41). Extrapolation from the ex viuo

### irritancy grade to the EU classification is carried out by using scientific judgement, and by redividing the original four categories to three. The combinations of the four CEET categories that are suggested for each of the three EU classes are: non-irritating (A+ Ba);irritating, R36 (Bb+ C);and severely irritating, R41 (D).

e. D@culties experienced and limitations of the method 

### Although the CEET is very straightforward and all kinds ofmaterials can be readily assayed, highly hydrophobic compounds and certain solids may need
a different test strategy because of the variation in contact with eye tissue that seems to occur in the inoivo

### rabbit eye test. With solids, modification and standardization of the exposure conditions in the inviuo

### rabbit eye test seem more appropriate than alteration of the invitro

### exposure conditions, since, with the present OECD and EC guidelines, exposure times in rabbits may range from 1min up to 24hr. With hydrophobic compounds, alternative test strategies have been explored successfully, consisting ofmultiple exposures orremoving theaqueous liquid from the cornea as much as possible, just before application, thus ensuring a more intense contact with the compound.

### EC/HOvalidation studyon alternativesto theDraizetest 927

A chicken abbatoir may not be in close proximity to the laboratory. Several options are available to overcome this problem: (a)moving the experimental set-up (which is small and does not require much space) to the slaughterhouse; (b) using end-of-lay birds instead of spring chickens; and (c)using other kinds of birds (e.g. turkeys). All data submitted are ‘absolute’ and are submitted unmodified for comparison with the in vivo 

### data. High numerical values are intended to correlate with high invivo

### irritancy.

e. D@culties experienced andlimitationofthemethod No 

### technical difficulties are usually experienced

7. Theisolated, enucleated rabbiteye test

a. Principle of themethod 

### in the performance of the test. It is ideally suited to investigations on undiluted test materials (solids, liquids and insoluble materials).
The effectsoftestmaterials are assessedbyapplication to the corneas of enucleated rabbit eyes. The eyes are removed from the test animals immediately after death and are mounted in moist, temperaturecontrolled chambers. After aperiod of stabilization, theeyesareexposed totheundiluted testmaterial for 10set, after which theeyesarethoroughly rinsed with saline. The effectsareassessed over a4-hr period after treatment. The main difficulty is that routine performance ofthe test involves evaluation of all the parameters measured during theperformance ofthetest and may involve further testing, depending on theresults ofan initial study. The data submitted forevaluation inthe EC/HO study were single parameters. Such data were highly unlikely to reflect the true overall response to the test material.

b. Basicprocedure, endpoints and endpoint measurement

Data submitted for

Method of comparison with What ismeasured determination in viva results Cornea1 opacity’ Draize Scoring System Mean opacity scores

(subjective) at 

### 1hrand 4hrafter treatment 

### In participating in theEC/HO study, the ‘narrative’

nature ofdata and itsevaluation became apparent as a weakness since the overall study expected a numerical “answer” for comparison against invivo

### data. Additionally, in-house customization oftheprocedure undermined the use of an all-embracing ‘single protocol’.

Percentage cornea1 Slit-lamp biomicroscope Comeal swellingat swellingoverpro- fittedwith adepth- 

### Ihr and 4hrafter treatment cornea1 measuring attachment, treatment thickness’ oran ultrasonic

pachymeter Assessment of Examination and No data submitted comeal epithelial assessment (subjective) damage’ ofdamage using slitlamp biomicroscope 

### The protocol was setup toidentify severeirritants. Most ofthe test materials applied were not severely damaging to the eye.Therefore, the responses in the system were minimal and too low to differentiate between many/most ofthe lower irritancy materials tested. Therefore, any overall correlation against all invivo

### data can bepredicted to bepoor. To evaluate lower irritancy materials, a second phase of testing would havebeen required. This wasconsidered bythe participating laboratories to be beyond the scope of the exercise. Penetration of fluorescein dye into cornea2 One drop ofl-2% No data submitted

fluorescein solution applied tocornea for 10set, after which excessdyerinsed away. Nature ofcomeal staining assessed subjectively immediately after treatment 

### 8. The silicon microphysiometer test

a. Principle of themethod

‘Assessments are carried out 30min after treatment and at 1,2, 3, and 4hr after treatment. 2Assessments arecarried out 30min after treatmmt and at4hrafter treatment.

c. Expression ofresults 

### For each test material, cornea1 opacity, measured 1hr and 4hr after treatment, and cornea1 swelling, measured 1hr and 4hr after treatment, are used as expressions ofthe irritancy ofthe test material. The four measurements are submitted for analysis individually against the MMAS for each test material. The results of each analysis are expressed as a correlation coefficient. The Silicon Microphysiometer (SM) (Molecular Devices Corp., Menlo Park, CA, USA) isbased on a light-addressable potentiometric sensor that allows indirect measurement ofreal-time changes in cellular metabolism. The instrument provides continuous monitoring ofthe rate at which living cells inside a flow-through chamber excrete acidic metabolites asa normal part of energy metabolism. The microphysiometer detects changes in cell metabolism that
arelikely toplay aroleinthelocal response ofocular cellstoirritants. In contrast to other commonly used invitro

### tests,themicrophysiometer assessesfunctional cell changes occurring at sublytic concentrations of test compounds.

d. Application ofresults b. Basic procedure, endpoint and endpoint measurement 

### An untreated control eye is used in each exper- In the SM test, the rate of cellular metabolism iment, to ensure that the system operated correctly. (acid metabolite production) ismeasured in murine928 

### M.Ballsetal.



### L929 fibroblasts in a flow-through chamber within themicrophysiometer instrument. Cells grown on culture inserts are exposed to increasing concentrations of test substances, diluted in culture medium, for approximately 810set/dose. The acidification rate is measured immediately after washout ofeach dilution oftest sample from thechamber. The endpoint ofthe test, the MRD,, value, is determined from doseresponse curves relating test substance concentration
on the X axis to acidification rate on the Yaxis. lysosomes ofliving cellsbecause ofthedifferential pH between theinside ofthe lysosome and the surrounding cytoplasm. The amount ofthe vital dye taken up bythe3T3cellsisdirectly proportional tothenumber of viable cells in the culture (Barstad et al., 

### 1991).

c. Expression ofresults 

### MRDso values were expressed in units oflog,, pg/ ml, where the MRD,, is defined as the dose of test substance required to produce a reduction in metabolic (acidification) rate to 50% of baseline control levels. Test materials are measured over a wide range of concentrations and the concentration yielding a50% reduction in NRU is used as the measure for comparison. The test is based on the observation that
somematerials which aredamaging totheeyeappear to be cytotoxic to a number of cell types in vitro. 

### Surface active agents would be expected to be cytolytic at different concentrations, depending on their irritancy potential. Mouse 3T3cellswere selected for this assay because oftheir ease ofmaintenance. h. Basic procedure, endpoint and endpoint measurement d. Application ofresults 

### Most of the materials tested during the development ofthe test were surfactants or surfactant-based products. The SM test has been proposed as a screening method for liquid, water-soluble surfactantcontaining materials, such as personal care and household cleaning products, to be used as part of
atiered testing process. From apractical standpoint, the primary use of the data is comparative. So, for example, a new shampoo would be tested in the invitro

### testtogether with abenchmark shampoo that: (1)is similar in chemical composition; (2)is accompanied by historical in vivo

### data; and (3) has safe market experience. In this way, invitro

### responses of the new product and benchmark are compared to predict whether the new product has the same, more orlessirritancy potential. An important aspect ofthis isthat the newproduct and benchmark need to have similar chemical composition. If a new product is widely different from the substances evaluated previously invitro,

### then aparallel testing approach isused to expand the validation database. To a lesser extent, the in vitro 

### data are used to estimate degrees ofirritancy within broad categories, that is innocuous-slight (e.g. high MRD,, values), slight-moderate-severe (e.g. low MRD,, values). The NRU assay has been adapted from the protocol ofBorenfreund and Puerner (1984). Mouse 3T3 cells are plated into each well ofa96-well tissue culture plate. The plates are incubated, and just before treatment depleted medium is removed from thewellsand 250p1freshmedium isadded tocontrol ‘untreated’ wellswhereas 250~1ofvarious concentrations oftest agents diluted in medium were added to test wells.The plates areincubated for 24hr at 37°C. The spent medium/test agent solutions are removed and replaced with fresh medium supplemented with neutral red dye in all wells except the blanks. 250~1 medium (without dye) is added to the blanks. The plates are then incubated for 3hr at 37°C and each wellthen received250p1wash/fix solution [anaqueous 1% formaldehyde-l % calcium chloride solution, for 2min (room temperature)]. The wash/fix solution isdecanted and each well receives a solvent solution (1% glacial acetic acid-50% ethanol) (100~1) for 20min at room temperature. Absorbances are measured at 550nm in amicroplate reader (after making the appropriate blank correction) and ‘percentage of untreated control’ values are calculated for each dilution of test agent. The ‘percentage of untreated control’ values versus the test agent concentrations
are then plotted (semi-log plot).

e. Dijkulties experienced and limitations of the method 

### c. Expression ofresults



### The test islimited in its ability to handle aqueousinsoluble substances.

9. The neutral red uptake test 

### The concentration of test material resulting in a 50% 

### inhibition of NRU (NRU,,) is determined by extrapolation from the dose-response curve. At least three valid trials are performed for each assay. The NRUS, values are given in pg/ml (mean + standard deviation) ofthe neat test material.

a. Principle ofthemethod d. Application ofresults 

### TheNeutral Red Uptake (NRU) assay with mouse 3T3 cells is a short-term monolayer culture test system which uses the cells as the target and cytotoxicity as the endpoint. The procedure isbased on the work ofBorenfreund and her colleagues. Neutral red has been shown to be selectively retained by the The exact uses of the assay to predict ocular irritation depends on the purpose ofthe testing and theexperience oftheuser. For personal careproducts, the assay has been used to select formulations for development and quality final products for use with/on human panelists (but probably not by directEC/HO validation study on alternatives to the Draize test 929

instillation into the eye). In some cases, the assay has free medium for normal human anchorage-dependent been used as the final safety test. cells. In Vitro Cellular and Developmental Biology 21, To predict an in uivo endpoint (such as ocular 160. irritation) from the invivodata, a graph of historical Borenfreund E.and Puerner J.A.(1984)Asimplequantitatanimal eye irritation data versus the 3T3 in vitro iveprocedure using monolayer cultures for cytotoxicity assays (HTD/NR-90). Journal ofTissueCulture Methods cytotoxicity data isusually constructed. The relation- 9, 119-124. ship between the variables is generally logarithmic; Gautheron P.,Giroux J., Cottin M., Audegond L., Morilla therefore, the invivodata are plotted on alinear scale A., Mayordomo-Blanc0 L., Tortajada A., Haynes G.,

on the y axis, while the cytotoxicity data are plotted Vericat J. A., Pirovano R., Gillio Tos E., Hagemann C., Vanparys P.,Deknudt G.,Jacobs G.,Prinsen M.,Kalweit on a log scale on the y axis. Materials whose in vivo S.and Spielmann H.(1994)Interlaboratory assessment of ocular %ritation potential is unknown are tested the bovine cornea1 opacity and permeability (BCOP) invitro and the projected invivoscore is extrapolated ~___..rn_~ >__I__ 

### 1 ,J._ ” 101,,92,

,- 

### . . 7..

. ,.. G; 

### I for EC Validation. assay. 1“xlc”r”gy m Ylrro 0, JO,-2 from tne grapn. It is tmportant to nave a sumcient jrdon V. (1993) EYTEX Protocol
database for various chemical classifications, since InVitro International, Irvine, CA. Interagency Regulatory Alternatives Group. Draft Report the relationship between cytotoxicity in the 3T3 cells of the IRAG Workshop on Alternatives for Ocular to the in uivoresponse appears to vary with chemical Irritancy, c/o Food and Drug Administration, Washingclass. ton, DC. Lewis R. W.. McCall J. C. and Botham P. A. (1993) A

e. D@culties experienced and limitations of the method comparison of two cytotoxicity tests for predicting the ocular irritancy of surfactants. Toxicology in Vitro 7, 155-158. False negative results can easily be generated ifcare is not taken to ensure that all materials tested are water soluble or at least water miscible. In addition, materials with appreciably high or low pH values are likely to be less toxic in the culture systems because of the buffering capacity of the culture medium. In particular, those materials with high acid or alkaline
reserve may cause problems in this type of assay. Reactive species, such as hypochlorite, may be underpredicted, because of reaction with culture medium.

REFERENCES Barstad R., Cortesi J.and Janus J. (1991)Use ofClonetics’ neutral red bioassay to optimize components of serumLuepke N. P. (1995)Hen’s egg chorioallantoic membrane testforirritation potential. Food andChemical Toxicology 23, 287-29 1. Pape W. J. W., Pfannenbecker U. and Hoppe U. (1987) Validation ofthe redblood celltest system asan invitro assay for the rapid screening of irritation potential of surfactants. Molecular Toxicology 1,525-536. Spielmann H., Kalweit S., Liebsch M., Wirnsberger T., Gerner I., Bertram-Neis E., Krauser K., Kreiling R., Miltenburger H. G., Pape W. and Steiling W. (1993) Validation study of alternatives to the Draize eye irritation test in Germany: cytotoxicity testing and HETCAM testwith 136industrial chemicals. Toxicology in Vitro 7, 505-510. Tchao R.(1988)Tram-epithelial permeability offluorescein invitro asanassay todetermine eyeirritants. InAlternativeMethods inToxicology. Edited by A. M. Goldberg. Vol. 6.pp. 271-283. Mary Ann Liebert, New York.