EURL ECVAM Test Submission Template (TST) · 1.4.1 Rationale for the selection of test items used for assessing BLR ... Pathway (AOP) for skin sensitization by the OECD (OECD documents

EUROPEAN COMMISSION JOINT RESEARCH CENTRE Institute for Health and Consumer Protection The European Union Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM)

U-SENS Test Submission Template Page 1 of 56

EURL ECVAM

Test Submission Template (TST)



TABLE OF CONTENTS

SUBMISSION OF CONFIDENTIAL INFORMATION........................................................................................ 4 LIST OF ABBREVIATIONS ........................................................................................................................... 4 SUBMITTER’S REQUEST TO ECVAM ....................................................................................................... 4

1. INFORMATION ON VALIDATION MODULES .......................................................................... 6

1.1 MODULE 1: TEST DEFINITION ............................................................................................. 6 1.1.1 Human health, environmental or other biological effects addressed by the test method .. 6 1.1.2 Scientific basis – biological and/or mechanistic relevance ................................................ 6 1.1.3 Intended purpose of the test method ................................................................................... 8 1.1.4 Evidence demonstrating the need for the test method ........................................................ 8 1.1.5 Technical specifications ...................................................................................................... 9 1.1.6 Test items used for developing and optimising the test method (protocol and PM) .........13 1.1.7 Cost and time estimates per test item .................................................................................14 1.1.8 Occurrence of non-qualified tests ......................................................................................14 1.1.9 Known limitations and drawbacks of the test methods .....................................................15 1.1.10 Intellectual Property Rights (IPRs) ...................................................................................15 1.1.11 History of test method development ...................................................................................15 1.1.12 Quality system(s) of the developing laboratory ..................................................................17

1.2 MODULE 2: WITHIN-LABORATORY REPRODUCIBILITY (WLR) .............................18 1.2.1 Rationale for the selection of the test items used for assessing WLR ...............................18 1.2.2 Assessment of within-laboratory reproducibility of experimental data ............................19 1.2.3 Identification and discussion of outlying values ...............................................................21 1.2.4 Quality system(s) of the testing laboratory ........................................................................22

1.3 MODULE 3: TRANSFERABILITY (TF) ................................................................................22 1.3.1 Rationale for the selection of the test items used for assessing the TF ............................22 1.3.2 Training required for transferring the test method ...........................................................23 1.3.3 Obstacles pertaining to transferability that are specific to the test method ......................23 1.3.4 Organisation of the transfer phase ....................................................................................24 1.3.5 Assessment of the transferability to another laboratory....................................................24 1.3.6 Quality system(s) of the other laboratory ...........................................................................25

1.4 MODULE 4: BETWEEN-LABORATORY REPRODUCIBILITY (BLR) ..........................25 1.4.1 Rationale for the selection of test items used for assessing BLR ......................................25 1.4.2 Assessment of reproducibility .............................................................................................26 1.4.3 Identification and discussion of outlying values ...............................................................28 1.4.4 Quality system(s) of the testing laboratories ......................................................................28

1.5 MODULE 5: PREDICTIVE CAPACITY (PC) .......................................................................29 1.5.1 Rationale for the selection of test items used for assessing PC .........................................29 1.5.2 Assessment of the predictive capacity of the test method ..................................................31 1.5.3 Identification and discussion of false predictions .............................................................33

1.6 MODULE 6: APPLICABILITY DOMAIN (AD) ....................................................................34 1.6.1 Applicability of the test method identified through testing ...............................................34 1.6.2 Limitations of the test method identified through testing .................................................35 1.6.3 Suggested Applicability Domain (AD) of the test method .................................................36

2. ESSENTIAL INFORMATION FOR A SPECIFIC VALIDATION PROCESS ..........................37

2.1 EXTERNAL VALIDATION STUDIES (NOT COORDINATED BY ECVAM) ......................................37 2.1.1 Study organisation and management (Project Plan) ........................................................37



2.1.2 Study objective and goals ...................................................................................................37 2.1.3 Summary of the study results .............................................................................................38 2.1.4 List of test items used in the validation study ....................................................................39 2.1.5 Study conclusions ...............................................................................................................39 2.1.6 Recommendations ..............................................................................................................40

3. ADDITIONAL INFORMATION .....................................................................................................42

3.1 ADDITIONAL INFORMATION ........................................................................................................42 3.2 LIST OF REFERENCES ..................................................................................................................50

4. ABBREVIATIONS USED IN THE TST ...............................................................................................50

5. NOTE REGARDING TERMS ...............................................................................................................51

6. REFERENCES ........................................................................................................................................53



Submission of confidential information

It should be noted that during the evaluation phase of test method submissions, EURL ECVAM will share

information contained in the TST with its Advisory Structure, e.g. the ECVAM Scientific Advisory

Committee (ESAC), and to the extent possible, with European regulatory authorities. Whoever gets access

to the TST will be bound to treat all information submitted to ECVAM in a confidential manner.

Nevertheless, ECVAM procedures involve that Background Review Documents on the evaluation of the test

method and its outcome are compiled and made publicly available which might imply disclosing

information/data submitted with the TST together with those generated during validation.

Therefore, if you consider some of the information provided in the TST as confidential (e.g. confidential

business information (CBI)), please clearly identify below those paragraphs where confidential information

has been entered. Briefly describe (not more than 100 words per paragraph) why this information is

considered confidential. Please specify if such confidential information may be made publicly available.

No confidential information provided.

List of abbreviations

Please list the abbreviation used in the submission

ATCC American Type Culture Collection

CRO Contract Research Organization

CV70 Calculated dose at which a substance reach the cytotoxicity threshold

(70% live cells)

DMSO Dimethylsulphoxide

EC150 Calculated dose at which a substance reach the CD86 positive threshold

(150% positive cells)

GLP Good Laboratory Practices

IATA Integrated Approaches to Testing and Assessment

INC INConclusive

LA Lactic acid

LLNA Local Lymph Node Assay

MUSST Myeloid U937 Skin Sensitization Test

NS Non Sensitizer

RPMI Complete culture medium (Roswell Park Memorial Institute)

S Sensitizer

S.I. Stimulation Index

SOP Standard Operating Procedure

TNBS Picrylsulfonic acid (or TriNitroBenzeneSulfonic acid)

TPF Test Presubmission Form

Submitter’s request to ECVAM



If you seek to enter the ECVAM validation process with this test submission, please indicate at what stage

in the validation process you think the test method should enter. For a description of the validation process

and the different types of validation, see the Explanatory Note on the TST. Otherwise, please specify any

other type of request to ECVAM by filling the appropriate text box.

Please tick where appropriate

Prevalidation

Prospective validation

Retrospective validation

Validation based on PS

Peer-review Peer-review of the data. Of both ring trial 2013

already reviewed by EURL-ECVAM (TM203-02) and

complementary data of the validation study 2014.

Other



1. INFORMATION ON VALIDATION MODULES The ECVAM modular approach to validation breaks down the information required for establishing the

scientific validity of a test method into independent modules allowing greater flexibility with regard to the

time of procuring information during a validation study.

1.1 MODULE 1: TEST DEFINITION

1.1.1 Human health, environmental or other biological effects addressed by the

test method

Please describe which human health, environmental or other biological effects the test method will

address, e.g. whether it can be used to predict repeated-dose toxicity in humans, to predict fish chronic

toxicity, to measure bioaccumulation, to be used in quality control of immunobiologicals etc.

Skin sensitization (delayed type hypersensitivity, contact dermatitis).

1.1.2 Scientific basis – biological and/or mechanistic relevance

Please describe the relationship between the test method and the effect of interest. This may include a

reference to a) the mechanistic relevance (e.g. the mechanism of action) and/or b) the biological relevance

(e.g. how well the test method models the target organ) and/or c) an empirically observed (correlative)

relationship to the effect of interest.

There is a general agreement on the key chemical and biological events underlying skin

sensitization. This knowledge has been formally described in an Adverse Outcome

Pathway (AOP) for skin sensitization by the OECD (OECD documents

ENV/JM/MONO(2012)10/PART1 and /PART2). This AOP captures the impact of skin

exposure and describes key events starting from the molecular initiating event i.e.

covalent binding of a chemical to skin protein (protein haptenation), via intermediate key

events like keratinocyte and dendritic cell, to the final determining event which is the

induction of hapten-specific T cells that after being challenged by the substance, will be

the effector cells in the clinical manifestation of skin sensitization: Allergic Contact

Dermatitis (ACD).

The U-SENS™ test method, formerly known as Myeloid U937 Skin Sensitization Test

(MUSST), was developed to address the key event 3 of the AOP.

The goal here was to develop a simple in vitro assay, which correctly predicts the skin

sensitization potential of chemicals, based on markers of DC activation in humans. In

terms of mimicking the in vivo process of DC activation, human-blood derived DCs like

monocyte derived DCs or CD34+ haematopoietic progenitor cells would be the best

candidates. However, due to the donor to donor variability and because of ethical issues,

these cells aren’t suitable to be used in a simple in vitro assay. Cell-lines are more

suitable for the development of in vitro tests, because of their higher stability and of the

easiness of maintenance. As such, several studies demonstrated so far that U937 cells

showed DC-like responses following exposure to sensitizers (up-regulation of surface



marker (e.g. CD86) and cytokine production (e.g. TNF-a)), although these cells have

monocytic origins.

During DC maturation, biomarkers such as CD40, CD54, CD80, CD83, CD86, and

HLA-DR surface antigens are up regulated (Aiba et al., 1997; Coutant et al., 1999;

Rousset et al., 2000). Among these, CD86 was reported by Ade et al (2006) to be the

most suitable and robust marker in U937 cells. In the U-SENS™ test method, the

modulation of the CD86 membrane marker in U937 cells is measured by flow cytometry

after a 45 hours exposure to test chemicals (at least 4 concentrations). In addition

previous studies with blocking antibody or with KO mice of CD86 molecule (a co-

stimulatory molecule) demonstrated that this molecule is essential for the induction of

skin sensitization and that the up-regulation of CD86 plays important roles in the

induction of ACD (reviewed in Christensen et al., 2011. APMIS 120, 1-27).

Other U937/CD86-based assays were also reported (Python et al., 2007; Bauch et al.,

2011; Natsch et al., 2013). Python et al (2007) proposed an assay based on specific

culture conditions (i.e. presence of interleukin-4) and on the analysis of at least two

markers out of three (CD86, IL1 beta or IL-8) measured at more than one time point.

Such conditions differed from the U937/CD86 assay used by Natsch et al. (2013) as well

as from the modified MUSST (mMUSST) described by Bauch et al. (2011). The U-

SENS™ test method, which was also developed as a U937/CD86-based assay, varies

with respect to the cell line origin, the doses selection strategy, the CD86 positive

threshold and/or the prediction model developed to categorize the substances. In

addition, another assay addressing the key event 3 has been developed such as the THP-1

cells-based h-CLAT assay, currently under EURL-ECVAM validation and which uses a

combination of two markers, CD86 and CD54 (Sakaguchi et al., 2010). U-SENS™ and

h-CLAT uses different cell lines that may have different metabolic competences. The

prediction models were also thought differently: h-CLAT requires one CD86 or CD54

positive dose whereas U-SENS™ required at least 2 CD86 positive doses with a dose-

response relationship (CD54 was used at the early stage of the development but not kept

because no added value was found). Thus, differences are to be expected even if both are

reliable and relevant. The U-SENS results were compared to the results of the 3 assays

used as surrogates for dermal dendritic cells reported by Urbisch et al. (2014), namely the

U937-CD86, the mMUSST and the h-CLAT assays (Piroird et al, 2015).

It is important to note that almost none of the currently regulatory accepted in vitro

methods can be claimed to be based on the use of test systems which fully represent the

in vivo situation.

Figure 1: U-SENS™ among the key events in the Adverse Outcome Pathway for Skin

Sensitization



1.1.3 Intended purpose of the test method

Please describe the intended purpose (i.e. practical use) of the test method (e.g. regulatory safety testing

under REACH, for cosmetics, for pharmaceuticals, or non-regulatory applications).

The assessment of skin sensitization potential is an important component of the safety

evaluation of substances and represents a standard requirement of chemical legislation in

the EU including the Classification Labelling and Packaging of substances and mixtures

(CLP) Regulation (EU, 2008), the REACH Regulation (EU, 2006) and the Cosmetics

Directive (2010).

The U-SENS™ test method is foreseen to be part of a battery or integrated testing

approach for replacement of the existing in vivo assays for hazard identification (contact

skin sensitizer vs. non sensitizer). It is also foreseen to be a part of an integrated approach

which will be able to fully replace the in vivo test methods (i.e. LLNA, Buehler and

Magnusson & Kligman) to ultimately make skin sensitization risk assessment decisions

possible without animal testing.

1.1.4 Evidence demonstrating the need for the test method

Please summarise the need for the test method in relation to existing methods in the context of regulatory

testing (relevant test guidelines and legislation) and the 3Rs. If applicable, describe whether the test

method represents an improvement compared to an existing method. Possible improvements include a)



better information (e.g. higher accuracy or addressing a mechanism of action), b) effectiveness in terms of

throughput (e.g. amenable to high-throughput testing), c) cost.

For demonstrating the safe use of cosmetic ingredients specifically in relation to the

Cosmetics Regulation, in vivo skin sensitization has been banned in the European Union.

The application of the Cosmetics Regulation might have wider ramifications for many

other industry sectors since the in vitro methods might appear in the test guidelines of the

Organisation for Economic Cooperation and Development (OECD). OECD test

guidelines have a very wide applicability, extending far beyond the evaluation of

cosmetic ingredients, notably the Registration, Evaluation, Authorisation and restriction

of Chemicals (REACH).

Current regulatory predictive tests for skin sensitization rely on the use of animals, these

include: a) the traditional guinea pig tests: Buehler Test and Guinea-pig Maximisation

Test (OECD TG406), b) the Local Lymph Node Assay (LLNA, OECD TG 429) and c)

its recently OECD adopted non-radioactive variants (OECD TG 429A, Ref.3 and OECD

TG 429B).

Considerable progress has been made in recent years towards the development of

alternative non-animal methods that address the key mechanisms. Given the restricted

AOP mechanistic coverage of each of the currently available non-animal test methods,

the current view therefore is a combination of non-animal methods (in silico, in chemico,

in vitro) within Integrated Approaches to Testing and Assessment (IATA) to fully

substitute the animal tests currently regulatory accepted.

The U-SENS™ test method has been specifically designed to address the key

mechanistic dendritric cell activation step involved in skin sensitization (key event 3).

1.1.5 Technical specifications

1.1.5.1 Protocol(s) of the test method

Please append the protocol(s) as used to generate the data submitted in this TST as Attachment 1a.

Furthermore please attach the protocol(s) in the DB-ALM protocol1 format as Attachment 1b. Please

specify how the protocol(s) relate to any existing DB-ALM protocol, if applicable, i.e. whether it is

identical or differing from the DB-ALM protocol. In case of deviations, please outline the major

components and/or steps that differ.

The SOP is appended in the DB-ALM protocol format. The SOP has already been used

in the intra-and inter-laboratory studies presented below.

1 The so-called “DB-ALM” protocols are ECVAM’s reporting format for the dissemination of a test

method protocol via the ECVAM database web service on alternative methods http://ecvam-

dbalm.jrc.ec.europa.eu/

http://ecvam-dbalm.jrc.ec.europa.eu/

http://ecvam-dbalm.jrc.ec.europa.eu/



The DB-ALM protocol has been written de novo and is not directly related to an existing

DB-ALM protocol.

The protocol(s) should contain a list and description of the materials needed, a description of what is

measured and how (specification of parameters/endpoints measured), as well as a (preliminary) prediction

model (PM), if applicable. In addition, a brief description of the following key elements of the protocol(s)

should be provided in the following paragraphs:

a) Brief description of the test system

Briefly specify the test system used (e.g. tissue model, specific cells grown to confluence, etc.).

The U-SENS™ test method is an in vitro cellular based-assay.

Human myeloid U937 cell line (Ref. /link CRL-1593.2) is commercially available from

the American Type Culture Collection (ATCC, www.atcc.org or www.lgcstandards-

atcc.org). This cell line is non-adherent and is used as a cell suspension in a water-based

culture medium (Sundström and Nilsson, 1976).

b) Parameters and endpoints measured

Please specify the parameter(s) (e.g. optical density) and endpoint(s) (e.g. cell viability, EC50)

measured to make predictions and describe how this parameter(s) is/are measured.

Since dendritic cell maturation upon exposure to a sensitizing agent is accompanied by

changes in surface marker expression, these surface markers are primary biomarkers of a

dendritic cell-based in vitro assay. The most frequently assessed markers are CD40,

CD54, CD80, CD83, CD86, and HLA-DR. These surface markers are up-regulated upon

dendritic cell maturation. CD86 expression marker is adequate for in vitro testing since

increases in CD86 expression are related upon in vitro exposure to contact sensitizers.

In the MUSST method the modulation of the CD86 membrane marker in U937 cells, a

human myeloid cell line used as a surrogate of DC, is measured by flow cytometry

following 45 hours of exposure to at least 4 concentrations of test chemical selected

amongst usable concentrations pre-defined in the SOP. The test method is designed to

discriminate between sensitising and non-sensitising chemicals whereby chemicals are

classified as sensitisers if the CD86-IgG1 percent of positive cells exceeds a defined

threshold (i.e. Stimulation Index ≥150) compared to the vehicle control at least to

consecutive tested concentration, in at least two independent measurements (i.e. run

repetitions). Cell viability is measured concurrently by Propidium Iodide staining and

CD86 values are considered for the prediction only if cell viability is above 70%.

c) Quality criteria applied to the test system

Please specify the quality criteria applied to the test system (e.g. appropriate stratification and

barrier function of a reconstructed human epidermis in each lot/batch).

For each run, acceptance criteria are defined for the test system.

At the end of the 45h incubation treatment period,

- the viability of untreated U937 cells should be > 90 % and



- the CD86 basal expression on untreated U937 cells should be comprised within the

range: ≥ 2% and ≤ 25%.

d) Positive control, negative control, benchmarks

Please indicate all concurrent controls used and specify if they are used as acceptance criteria

for the run (a run consists of one or more test items tested concurrently with a positive and a

negative control). Please include also the acceptance range for the control responses and,

where available, any historical data used to establish the acceptance range.

Positive Control(s)

The positive control(s) should consist of a test item(s) well known to elicit a positive response in

the test method.

The positive control is picrylsulfonic acid (TNBS), a well-known sensitizer. It is applied

with the same test settings as any unknown substance except that it is applied at a single

dose (50 µg/mL) and in triplicate. Acceptance criteria are applied to discard results if the

induction by TNBS is outside the acceptable range (described in SOP, Attachment 1a).

Negative Control(s)

The negative control(s) can consist of treatment with the vehicle used and/or a test item known

not to elicit a positive response in the test method.

The negative control is lactic acid (LA) a well-known non sensitizer. It is applied with

the same test settings as any unknown substance except that it is applied at a single dose

(200 µg/mL) and in triplicate. Acceptance criteria are applied to discard results if the

induction by LA is outside the acceptable range (described in SOP, Attachment 1a).

Benchmarks (if applicable) Benchmarks consist of test item(s) that produce a midrange response in the test method.

No benchmark control used (only normalisation to vehicle control).

e) Acceptance criteria applied to the results

Please specify the acceptance criteria for the experimental data.

The acceptance criteria defined for test substances and controls are as follows:

- Any RPMI medium control is accepted/qualified if IgG1 value ≥ 0.6% and <

1.5%

- For each vehicle control (RPMI or DMSO), an outlier is accepted if its value is

comprised between > 75% and < 125% of the mean of all the replicates for the vehicle

control

- For each single point, the CD86 expression is recorded only if the measured

viability is at least 70%.

Note that all controls (medium, vehicles, negative and positive controls) are run in

triplicates. See SOP in Attachment 1a for further details.



1.1.5.2 Data analysis and Prediction Model (PM)

Please specify how the raw data are processed and analysed. Please describe the (preliminary)

procedure to translate the test method results into predictions of effects on human health or the

environment. This procedure ideally should be a (preliminary) PM.

Data exploitation is performed with percentage of CD86-positive cells among the viable

cells, with systematic isotype control used to quantify and remove non-specific antibody

binding.

Results are expressed as stimulation indexes (S.I.) calculated as follows:

As reported in Figure 2, the prediction model of the MUSST classifies the substances as

sensitizers (S) or non-sensitizers (NS) in an experiment, which itself consisted of at least

two valid runs with individual conclusions.

• A S individual conclusion is attributed if the CD86 S.I. is at least 150% with a dose-

response relationship at non-cytotoxic doses, while an NS individual conclusion is

attributed if the CD86 S.I. is less than 150% at non-cytotoxic doses and if no

interferences such as poor solubility, color interference or cytotoxicity were observed.

Otherwise no S or NS individual conclusion can be attributed to the run.

• Once a majority of S or NS individual conclusions is reached (i.e. generally two S or

NS), the final S or NS U-SENS™ classification is determined.

• Otherwise, viability and CD86 means values of all valid runs are used to calculate a

sum of scores determined by the application of six rules in order to determine a final S or

NS U-SENS™ classification (Gomes et al., 2014). The prediction model is summarized

in Figure 2.

Figure 2: U-SENS™ chemical classification

% of CD86+ treated cells - % of IgG1

+ treated cells

% of CD86+ vehicle control cells - % of IgG1

+ vehicle control cells

x 100



Majority of NS runs

U-SENS classification :

NON-SENSITIZER

S scores < 1 S scores ≥ 1

Majority ofS runs

U-SENS classification :

SENSITIZER

Score

#1 Cytotoxic effect (mean viability ≤ 85%) at low doses (at least one dose ≤ 25 µg/mL) + 5

#2 CD86 induction (CD86 S.I.≥ 120%) at low doses (at least one dose ≤ 25 µg/mL) + 4

#3Concomitant CD86 induction ( ≥ +5 ) and viability decrease (viability ≤ -2)

between minimal and maximal non toxic dose+ 3

#4 Strong CD86 induction ( ≥ + 50) between minimal and maximal non toxic dose + 5

#5 No CD86 induction (CD86 S.I ≤ 120) at high doses (≥ 100 µg/mL) - 2

#6No or weak CD86 induction ( -30% < CD86 S.I. variation < 5%)

between minimal and maximal non toxic dose- 5

Rules (on doses range with viability mean ≥ 70%)

YES YESNO NO

The application of the 6 rules is illustrated with examples in Attachment 1c.

1.1.5.3 Expertise required for performing the test method protocol

Please describe the level of expertise and demonstrated proficiency required by the study personnel for

performing the test method protocol.

Any study personnel with expertise in running cell biological experiments, performing

dose-response tests on chemicals, and knowledge in conducting flow cytometry analysis

and using Excel should be able to run the test method.

1.1.6 Test items used for developing and optimising the test method (protocol and

PM)

Please indicate the number and basic physical/chemical properties of the test items used to develop and

optimise the test method. Please append the full list of these test items in the form of a table, including their

CAS numbers and basic physical/chemical properties and acquired data, as Attachment 2.

The historical protocol and prediction model were developed within L'Oréal's

laboratories using ~100 reference chemicals (animal and/or human clinical data). They



were then assessed and optimized within the COLIPA Skin Tolerance Project Team ring

study with a small set of chemicals (Ethylene diamine, ParaPhenylene Diamine (PPD),

Tri-NitroBenzene Sulfonic acid (TNBS), Eugenol, Isoeugenol, Lactic acid, Sodium

Dodecyl Sulfate (SDS), Salicylic acid). This ring trial was described in the EURL

ECVAM’s pre TST submitted in 2009.

Entering into the formal EURL-ECVAM pre-validation, protocol and PM were then

fixed. Having some reproducibility issues considering INConclusives calls (INC), the

prediction model was then optimized within L’Oréal allowing only 2 final calls,

Sensitiser vs Non Sensitiser.

1.1.7 Cost and time estimates per test item

Please give an estimate of the testing cost per test item, considering that the laboratory is equipped with all

necessary standard equipments and not considering labour cost. Please indicate as well an estimation of

the time required to complete data acquisition for a run and specify how many chemicals can be included

in a typical run.

Cost:

The consumables’ cost per test item excluding labor and fixed equipment has been

estimated at approximately 250 euros. Contract Research Organization (CRO) testing

costs are available upon request at Bioassay, CiToxLAB or WIL Research.

Time required:

3 days are required to perform one run: cell treatment with test items is performed on day

1 then harvest, staining and data acquisition on day 3.

A U-SENS™ experiment consisted of at least two independent runs in 2 different weeks.

2 to 3 weeks are required to overall predict as S or NS a chemical.

A trained experimenter can run at least 8 test items in one run and can perform two runs

in one week (up to 16 different tests items per week). Therefore, by using robotics, the

throughput might be enhanced and the labor per chemical decreased (up to 32 test items

par week).

1.1.8 Occurrence of non-qualified tests

On the basis of your experience/historical data please provide:

a) an estimate (e.g. in percentage) of the frequency in occurrence of non-qualified tests (i.e. tests which do

not meet the acceptance criteria),

b) an average of the number of tests which usually have to be performed to acquire the requested number

of qualified tests (as described in the protocol or prediction model).

On the basis of L’Oréal experience on hundreds substances,

a) The frequency in occurrence of non-qualified tests is about 3%.

b) An average of 3 runs is required to get a U-SENS™ classification (Sensitizers/Non-

Sensitizers).



In the ring trial 2013, once the test method was set up and running in the different

laboratories (Bioassay, CiToxLAB, L’Oréal and WIL Research), none of the 4

laboratories reported non-qualified tests (TM203-02 already reviewed by EURL-

ECVAM).

For the Validation study 2014, the frequency in occurrence of non-qualified tests reported

by L’Oréal and WIL Research was 0.8%. The occurrence reached 10.1% for CiToxLAB

and 25.9% for Bioassay, percentage affected by a systematic external factor within the

laboratory (related in the independent statistical report).

1.1.9 Known limitations and drawbacks of the test methods

Please specify any known limitations of the test method beyond those addressed by the Applicability

Domain (Module 6). Examples of possible limitations and drawbacks:

■ The test method requires expensive equipment and/or is based on an expensive test system

■ Equipment / test system needed is no longer commercially available

■ Etc.

The test method requires a flow cytometer which is a relative expensive equipment.

The flow cytometer should regularly undergo maintenance and daily/weekly cleaning

procedures should be completed.

The facility where the flow cytometer is located should keep a controlled temperature

~20°C (air conditioned) whenever the flow cytometer is on, in order to avoid drift in

CD86 measurement. This is especially important when using a plate sampler.

1.1.10 Intellectual Property Rights (IPRs)

Please state whether any component of the test method (e.g. protocol, test system, equipment) is patented,

copyright protected, trade-marked or registered. Please specify who is holding the IPRs.

There are no IPRs on the test method.

The U937 cell line can be freely used for research purposes.

Dr. K. Nilsson is restricting the commercial use of this cell line to the payment of a

license fee. This can be either a one year license or a lifelong license.

Kenneth Nilsson MD, PhD

Professor of Cellular Pathology, Director of Rudbeck Laboratory

Dept of Genetics and Pathology, Rudbeck Laboratory, SE-75185 Uppsala, Sweden

Tel.: (+46) 18-611 38 23

Fax: (+46) 18-55 89 31

E-mail: [email protected]

1.1.11 History of test method development

Please provide any information on the process of developing the test method that might be of relevance for

its validation.

mailto:[email protected]



The historical protocol of the U-SENS™ test method was developed for internal

screening purposes, with the prediction model based on expert judgment. The protocol

and the prediction model were then optimized and standardised under the name of

MUSST. A successful Cosmetics Europe’ ring study allowed the assay to enter in 2009 a

formal EURL-ECVAM pre-validation study. Following the No-Go decision of the

EURL-ECVAM at the end of the B1 phase of the pre-validation (discrepancies in the

reproducibility caused only by « Inconclusive » or INC conclusions), L’Oréal took the

opportunity given by EURL-ECVAM to revise the prediction model and provide SOP

modifications with convincing scientific rationale supported by a retrospective analysis.

A new PM was therefore built using a statistical approach based on a scoring technique

(Gomes et al., 2014) with the following specifications: suppress the INC category

without having an impact on the technical part of the current SOP (i.e. using the same 2

read-outs), by maintaining similar sensitivity and specificity performances and without

increasing the rate of false negatives for the strong/extreme in LLNA.

The strategy to improve the prediction model was to propose additional rules to allow a

“S/NS” classification for the test items previously classified as INC without impacting

the classification of the classified chemicals. The learning set was composed of all 60

INC test items included in the L’Oréal’s portfolio. As these chemicals are proprietary

chemicals, the data set would not be disclosed. The parameters used for the statistical

study were viabilities and CD86 S.I. for each tested dose for all validated runs (2 to 5

runs). The means of viabilities and CD86 S.I. for each tested dose among all validated

runs were calculated in order to weigh equally the test items and to handle with a higher

variability of the viabilities and CD86 S.I. between runs in the learning set of INC. As a

result, all these parameters (doses, mean viability, CD86 induction) were found to be

useful, as they were in the previous/historical prediction model but with different

thresholds. The rationale behind the defined statistical rules was evident:

- sensitizing alert/positive score for rule 1: cytotoxic effect at low doses, rule 2: CD86

induction at low doses, rule 3: concomitant CD86 induction and viability decrease and

rule 4: strong CD86 induction

- no alert/negative score for rule 5: no CD86 induction at high doses and rule 6: no or

weak CD86 induction.

The milestones are summarized in figure 3.

Figure 3: milestones of U-SENS™ since 2002



1.1.12 Quality system(s) of the developing laboratory

Please state the quality system(s) in place, if any, in the laboratory that developed the test method (e.g.

GLP, ISO, GCCP). For GLP-like conditions, please specify the extent and area of compliance.

L’Oréal’s research laboratory that developed the U-SENS™ test method does not have

formally implemented GLP. However, the following requirements (Balls, et al., 1995)

were applied:

• Qualified personnel, and appropriate facilities, equipment and materials were available

• Records of the qualifications, training and experience, and a job description for each

professional and technical individual, were maintained.

• For each study, an individual with appropriate qualifications, training and experience

was appointed to be responsible for its overall conduct and for any report issued.

• Instruments used for the generation of experimental data were inspected regularly,

cleaned, maintained and calibrated according to established SOPs, if available, or to



manufacturers' instructions. Records of these processes were kept, and made available for

inspection on request.

• Reagents were labelled, as appropriate, to indicate their source, identity, concentration

and stability. The labelling included the preparation and expiry dates, and specific storage

conditions.

• All data generated during a study were recorded directly, promptly and legibly by the

individual(s) responsible. These entries were attributable and dated.

• All changes to data shall be identified with the date and the identity of the individual

responsible, and a reason for the change shall be documented and explained at the time.

1.2 MODULE 2: WITHIN-LABORATORY REPRODUCIBILITY

(WLR)

1.2.1 Rationale for the selection of the test items used for assessing WLR

Please describe the criteria applied for selecting the test items used for assessing WLR. Please specify the

extent to which these test items represent the range of observed effects (e.g. non-toxic to highly toxic effect).

If possible, please specify the chemical classes and basic physical/chemical properties covered by your

selection of test items. Please append the full list of these items in the form of a table, including their CAS

number and relevant properties, as Attachment 3.

Selection criteria were

- Availability of reliable in vivo LLNA reference data: sensitizers (S) and non-sensitizers

(NS),

- Commercial availability: all tests items were sourced from Sigma Aldrich,

- Diversity in terms of chemical properties with different reactivity toward proteins (as

described by Aptula and Roberts (2006) and determined with Toxtree software) and with

ingredients used in Cosmetics and non-cosmetic chemicals.

Either liquids or solids were evaluated but the physical state was not a criterion for

selecting the tests items because this parameter is not relevant for the test method.

Ring trial 2013 (TM203-02 already reviewed by EURL-ECVAM)

21 test items were evaluated for this intra-laboratory reproducibility (WLR) ring trial.

Fourteen of them (#1-14) were also evaluated for the between-laboratory reproducibility

(BLR). The main rationale for their selection was primarily to select a majority of test

items (12/14), for which potential interfering factors could be observed (e.g. color

interferences with cytometry parameters or poor solubility) based on our historical data.

Most of the above selected test items are sensitizers. The 7 remaining test items (#15-21)

were selected preferentially amongst non-sensitizers in order to balance the entire set of

substances. For this preliminary study, the WLR set of 21 test items was composed of 11

sensitizers and 10 non-sensitizers in the LLNA.



Validation study 2014 (complementary data submitted to EURL-ECVAM)

Adopting the study design of the EURL-ECVAM study in terms of number of test items,

15 substances were evaluated for this intra-laboratory reproducibility (WLR) formal

study. As the preparatory study was focussed on sensitizers, a majority of non-sensitizers

was selected in this study: 6 sensitizers versus 9 non-sensitizers in the LLNA.

One test item (glycerol) has been included in the 2 studies. So, a total of 35 tests items

were used for assessing WLR, including 17 S and 18 NS, 13 non-cosmetics and 22

cosmetics ingredients (like dyes, fragrances, preservatives and actives), 12 non-reactive

chemicals and 23 chemicals belonging to at least one of the classes described by Aptula

and Roberts (2006) of type of reactivity: Michael acceptor, Schiff base formation, acyl

transfer agent or SN (substitution nucleophilic).

1.2.2 Assessment of within-laboratory reproducibility of experimental data

Please provide an assessment of the within-laboratory reproducibility of experimental data, i.e. the

agreement among results obtained from testing the same test items over time using the same protocol in

one laboratory. Please specify possible sources of variability. Please append the data in the form of tables

and/or figures, as Attachment 4.

The main determinant of the test method reliability assessment was the concordance of

classification, sensitizer vs. non-sensitizer.

In addition, the 2 overall reads-outs: EC150 (estimated concentration that produces a

CD86 stimulation index of 150) and CV70 (estimated concentration that induces 30%

cytotoxicity or a remaining viability of 70%) were evaluated. According to the SOP,

these overall values must be calculated for an experiment only if applicable and if the

results between the runs are concordant. If not, for the needs of the analysis, the overall

EC150 and CV70 values were enforced i.e. calculated whenever it was possible without

consideration of concordance between the individual runs. When the positive threshold

(150%) and viability threshold (70%) were not reached, the value of the maximum tested

dose (200 µg/mL) was used. For substances reaching the viability threshold but not the

positive threshold, the overall CV70 value was also attributed by default to the overall

EC150.

Ring trial 2013: 21 test items within L’Oréal The assessment of the within-laboratory reproducibility (WLR) on 2 independent runs

was already reviewed by EURL-ECVAM in 2013. Afterwards, an independent additional

experiment was conducted on the 21 test items within L’Oréal allowing the analysis of

the WLR on 3 independent experiments (instead of 2 in the TPF).

The same prediction was obtained for 20 out of 21 test items with the exception of

chlorobenzene (#9), resulting in WLR of 95%.



The means and the standard deviations of the EC150 and CV70 values were calculated

on the 3 experiments for the 21 tests items, showing the high reproducibility of these 2

read-outs.

Validation study 2014: 15 test items within 4 laboratories The test items were acquired, weighed, coded and distributed by an independent Study

Product Coordinator (VitroScreen). In order to be tested in three independent

experiments per laboratory, three differently coded samples were provided.

Data analysis was conducted by an independent Study Data Coordinator (Sebastian

Hoffmann consulting + services), with whom the participating laboratories were allowed

to communicate during the testing and data analysis only and to whom exclusively all

study results had to be submitted. The statistical analysis of the reproducibility was

conducted blind: the code was broken only for the predictive performance analysis.

The WLR was primarily assessed based on the concordance of classifications within the

4 laboratories based on 15 repeatedly tested substances.

As stated in the independent statistical report: “Both L’Oréal and WIL Research

produced reproducible results for all substances (WLR of 100%). Bioassay reported

discordant results for Methylmethacrylate only, resulting in a WLR of 93.3%, while

CiToxLAB had concordant classifications for 11 substances, i.e. a WLR of 73.3%.

Averaging these reproducibility values over the four laboratories, the MUSST showed

good WLR of 91.7%.

In addition, results demonstrates that in almost all cases a laboratory selected the same

vehicle for a test substance. Only at WIL Research, 3 test substances (Ethylene diamine,

Hexane, Vinylidene dichloride) were tested with both solvents. In these cases, the solvent

did not have any impact on the classification.”

For each laboratory, the means and the standard deviations of the EC150 and CV70

values calculated on the 3 experiments for the 15 tests items, showed a high

reproducibility of these 2 read-outs within the four laboratories.

Note:

Knowing that seven non-coded test items evaluated in the ring trial study 2013 for the

WLR assessment (#15-21) by L’Oréal were included in the validation study 2014 (coded)

with a test substance for the WLR assessment (Glycerol) and 6 test substances for the

BLR assessment (methyl salicylate, vanillin, sulfanilic acid, 4-hydroxybenzoic acid,

bromobutane and citric acid), reproducibility over these independent studies over the 2

years was assessed, showing concordant prediction.

Automation



As an add-on, L’Oréal forwarded all coded samples of the study 2014 to an internal high-

throughput laboratory that had developed an automated U-SENS™ version. Except for

the solubility testing (information provided by the L’Oréal lead laboratory), this

laboratory conducted the same testing as the other four laboratories.

The WLR was also assessed based on the concordance of classifications obtained

automatically on the 15 repeatedly tested substances.

As indicated in the independent statistical report: “… the automation data from L’Oréal

were in terms of concordance (93.33%) as well as regarding CV70 and EC150 values

equally reproducible”.

Overall WLR

The main results for the evaluation of the WLR focused on the concordance of the

predictions (sensitizer versus non sensitizer) as determined by the results of three

independent experiments are summarised in the table below and reported in Alépée et al.

(2015):

Study Test items Laboratory

Ring trial

2013

21 tests items

(11 S + 10 NS)L'Oréal 20/21 = 95%

L'Oréal 15/15 = 100%

Bioassay 14/15 = 93%

CiToxLAB 11/15 = 73%

WIL Research 15/15 = 100%

automation 14/15 = 93%

WLR

34/35 = 97%

Validation

study 2014

15 coded items

(6 S + 9 NS)

55/60 = 92%

69/75 = 92%

1.2.3 Identification and discussion of outlying values

Please identify and discuss any outlying values.

Not within-laboratory reproducible U-SENS™ classifications:

Chlorobenzene (#9, study 2013)

This test item has poor water solubility and is known to interact with cell membranes.

These 2 potential interfering factors can explain the non-reproducible classifications

(NS/NS/S*) within L’Oréal.

Methylmethacrylate (#5, study 2014)

Not reproducible classifications were obtained by Bioassay (NS*/S*/S). Two out of 3

classifications were obtained by applying the rules because no majority of S or NS runs

were found. This was also the case within L’Oréal (lead lab) and by automation which

could be explained by the fact that this test item is volatile. Some variability might indeed

occur during the weighing/dilutions initial steps but, unless technical issue, not during the

cell treatment with chemicals (the 96-well plates were systematically covered with a



sealing tape to prevent possible collateral effects of volatile chemicals, which was

confirmed on volatile substances such as perfume ingredients).

Benzyl alcool (#15, study 2014)

Not reproducible classifications were obtained by CiToxLAB (NS/S/S) and by

automation (S*/S/NS*). These results could also be explained by the fact that this

fragrance allergen is volatile.

Lactic acid, streptomycin sulphate and polyethylene glycol (respectively #7, #13 and #14

of study 2014)

Not reproducible classifications were obtained by CiToxLAB for these 3 tests items

classified as non-sensitizers in the 3 experiments performed by the other laboratories. The

S classifications were obtained by applying the rules because no majority of S or NS runs

were found. These results suggest that the assay seems to be more sensitive when

performed in this laboratory.

NS * or S*: classifications obtained by applying the rules.

1.2.4 Quality system(s) of the testing laboratory

Please state the quality system(s) in place, if any, in the testing laboratory (e.g. GLP, ISO, GCCP). For

GLP-like conditions, please specify the extent and area of compliance.

The WLR results were conducted in the spirit of Good Laboratory Practices (GLP).

Three testing facilities (CiToxLAB, Bioassay and WIL Research), compliant with GLP

rules, performed the studies in accordance with those rules.

L’Oréal’s laboratory that developed the U-SENS™ test method did not have formally

implemented GLP but meet the basic principles of GLP (see details in section 1.1.12).

1.3 MODULE 3: TRANSFERABILITY (TF)

1.3.1 Rationale for the selection of the test items used for assessing the TF

Please describe the criteria applied for selecting the test items used for assessing transferability. Please

specify the extent to which the test items represent the range of observed effects (e.g. non-toxic to highly

toxic effect). If possible please specify the chemical classes and basic physical/chemical properties covered

by your selection of test items. Please append the full list of these test items in the form of a table, including

their CAS number and relevant properties, as Attachment 5.

The selection of tests items for assessing transferability was first based on their in vivo

LLNA classification (i.e. sensitizer versus non sensitizer) so that the set contains at least

one sensitizer and one non sensitizer.

Then other criteria were applied:



- Inclusion of at least one substance inducing color interferences with cytometry

parameters so that the naïve laboratory manages the cytometer’s settings to apply in this

case.

- Inclusion of at least one substance inducing cytotoxicity.

- Inclusion of at least one DMSO-soluble chemical.

- Inclusion of at least one chemical requiring an adjustment of the doses between runs in

order to check the presence or absence of a dose-dependent induction of CD86.

- Chemicals commercially available.

Therefore, the 5 selected chemicals were

- For the testing of test items with predefined doses e.g. the “transfer run”:

1) 2,4,6-Trinitrobenzenesulfonic acid (TNBS) classical positive (sensitizer) reference

which is also the positive control of the U-SENS™ test method (thus allowing a quality

check by comparing data obtained with TNBS as test item and data obtained with TNBS

as positive control).

2) Lactic acid (LA) well known negative (non-sensitizer) reference which is also the

negative control of the U-SENS™ test method (thus allowing a quality check by

comparing data obtained with LA as test item and data obtained with LA as negative

control).

3) 1,4-Phenylenediamine (PPD) sensitizing oxidation dye inducing color interferences

and cytotoxicity effect.

4) Abietic acid (AA) sensitizer soluble in DMSO and inducing cytotoxicity.

- For the overall evaluation of a test item:

5) 4,4,4-Trifluro-1-phenylbutane-1,3-dione a sensitizer soluble in DMSO, inducing

cytotoxicity and requiring an adjustment of the doses between the first and the second run

in order to check the presence of a dose-dependent induction of CD86.

1.3.2 Training required for transferring the test method

Please provide an estimation of the amount of training that is necessary to establish the test method in a

naïve laboratory (i.e. a laboratory which is familiar with the techniques involved but not with the test

method). If available, please append the training protocol as Attachment 6

One training week (from Tuesday morning to Friday evening) within L’Oréal’s facilities

was most of the time necessary to establish the test method in a naïve laboratory. It

included a practical training in which (i) L’Oréal showed the main steps of the protocol

(ii) then the trainers performed the same steps. It also included depth discussions about

the detailed protocol and a practical example-based workshop on dose selection and

conclusion.

1.3.3 Obstacles pertaining to transferability that are specific to the test method



Please provide a summary of expected obstacles or difficulties that may impact on the transferability of the

test method, e.g. level of complexity of some procedures in the protocol(s), etc.

The U-SENS™ test method is based on measurements performed using a flow cytometer,

generally sensible equipment. That is why the flow cytometer should regularly undergo

maintenance and daily/weekly cleaning procedures and the involved study personnel

being skilled in flow cytometry procedures to avoid any issue related to an external

impact factor during the U-SENS™ experiment.

Some practice was required in order to master the U-SENS™ test method. It was

important that the study personnel practice the U-SENS™ test method back in their

laboratory, after the training, by performing 2 runs per week for 3 to 6 weeks.

1.3.4 Organisation of the transfer phase

Please explain how the transfer phase was organised, including the criteria applied to assess success of

transfer (see 2.3.5). If available, please append the transfer protocol as Attachment 7..

The practical transfer phase was organised as follow:

Back in their laboratory, after the training week, each technician involved in the practical

work performed 2 runs per week.

The analysis transfer phase was organised as follow:

It was expected that within a 6 weeks period each operator obtained a valid, concordant

and reproducible transfer run each week over 3 consecutive weeks (or 4 consecutive

weeks including max 1 invalid run) i.e.:

• Fulfill the U-SENS™ acceptance criteria (e.g. regarding cell viability and CD86 basal

expression),

• Show capacity to accurately select or discard controls,

• Avoid any drift of CD86 expression,

• Get dose-dependent increase of CD86 expression with the reference sensitizers and no

dose dependent increase of CD86 expression with the reference non sensitizer,

• Get reproducible values for the controls and their corresponding doses considered as

“test item”.

It was also expected that within a 4 weeks period each operator obtained a valid and

accurate classification of the 4,4,4-Trifluoro-1-phenylbutane-1,3-dione.

During the second or third week of the practice time, one L’Oréal representative visited

the study personnel’s lab to oversee the experiment and advised them on any technical

aspect of the procedure.

Regarding the dose selection and conclusion understanding, case study examples were

provided by L’Oréal. The laboratories defined the doses selection and conclusions with

90% correct answers (L’Oréal acceptance criteria met).

1.3.5 Assessment of the transferability to another laboratory



Please provide an assessment of the transferability of the submitted test method to another laboratory. If

available, please append the transfer report as Attachment 8...

The transfer of the U-SENS™ test method to Bioassay and WIL Research (ex Ricerca)

was validated in 2011 (Phase AII of the EURL-ECVAM formal prevalidation).

The transfer of the U-SENS™ test method was validated for CiToxLab in 2013.

Before entering to the ring trial study 2013, all laboratories (Bioassay, CiToxLAB and

WIL Research), were trained one day in February 2013 on the SOP.

1.3.6 Quality system(s) of the other laboratory

Please state the quality system(s) in place, if any, in the other laboratory (e.g. GLP, ISO, GCCP). For


The 3 laboratories (Bioassay, CiToxLAB and WIL Research) involved in the WLR/BLR

reproducibility studies were GLP accredited.

L’Oréal’s laboratory did not have formally implemented GLP but meet the basic

principles of GLP (see details in section 1.1.12)

1.4 MODULE 4: BETWEEN-LABORATORY REPRODUCIBILITY

(BLR)

1.4.1 Rationale for the selection of test items used for assessing BLR

Please describe the criteria applied for selecting the test items used for assessing BLR. Please specify the



selection of test items. Please append the full list of these test items in the form of a table, including their

CAS number and relevant properties, as Attachment 9.

As for the assessing WLR, selection criteria were reliability of LLNA reference data,

commercial availability, and diversity in terms of chemical properties (see section 1.2.1).

Ring trial 2013 (TM2013-02 already reviewed by EURL-ECVAM)

Fourteen test items (#1-14), also evaluated for assessing WLR, were used for assessing

BLR (see 1.2.1). The main rationale for their selection was primarily to select a majority

of test items (12/14), for which potential interfering factors could be observed (e.g. color

interferences with cytometry parameters or poor solubility), based on our historical data.

Most of the above selected test items were sensitizers.

A L’Oréal unit was responsible for the purchase, independent coding and shipping of the

14 tests items to the participating laboratories. The personnel involved in the chemical

coding and distribution were independent from the personnel involved in the conduct of



the ring trial within L’Oreal. The 14 randomly coded chemicals were sent to all testing

facilities.

Validation study 2014 (complementary data submitted to EURL-ECVAM)


24 substances were evaluated for this BLR formal study.

As a larger number of sensitizers were evaluated during the ring trial study, a majority of

non-sensitizers were selected for the validation study (8 sensitizers versus 16 non-

sensitizers) to balance the entire set of chemicals.

Overall, a total of 38 coded substances were selected for assessing BLR. The set was

well-balanced with 19 sensitizers and 19 non-sensitizers. It includes 14 non cosmetics

and 24 cosmetics substances (like dyes, fragrances, preservatives, and actives), 14

substances classified as “no binding” and 24 substances belonged to at least one of the

classes described by Aptula and Roberts (2006) of type of reactivity: Michael acceptor,

Schiff base formation, acyl transfer agent or SN (substitution nucleophilic).

1.4.2 Assessment of reproducibility

Please provide an assessment of the between-laboratory reproducibility of experimental data, i.e. the

agreement among results obtained from testing the same test items using the same protocol in different

laboratories. Usually at least three laboratories are requested to properly evaluate between-laboratory

reproducibility. Please specify possible sources of variability. Please append the data in the form of tables

and/or figures as Attachment 10.

As the WLR, the BLR was primarily evaluated by comparing the classification between

the laboratories. For the substances tested three times, choosing the more frequent (or

median) classification derived the final result.

Ring trial 2013: 14 test items within 4 laboratories

As indicated in section 1.2.2, the tests items were coded and sent by L’Oréal to all

participants laboratories. The substances were then tested blinded in all laboratories.

Note that the third experiment performed by L’Oréal for the WLR assessment didn’t

change the final result obtained and considered for the BLR assessment on the 14

chemicals tested.

As indicated in the TPF TM2013-02 already reviewed by EURL-ECVAM, 11 out of the

14 substances were consistently classified (S/NS) by the 4 laboratories resulting in a BLR

of 79%. Adding automation as a fifth laboratory would not have had any impact on this

BLR assessment.

Validation study 2014: 24 test items within 4 laboratories

The test items were acquired, weighed, coded and distributed by an independent Study

Product Coordinator (VitroScreen). Data analysis was conducted by an independent



Study Data Coordinator (Sebastian Hoffmann consulting + services), with whom the

participating laboratories were allowed to communicate during the testing and data

analysis only and to whom exclusively all study results had to be submitted. The

statistical analysis of the reproducibility was conducted blind: the code was broken only

for the predictive performance analysis.

Twenty one out of the 24 substances were consistently classified (S/NS) by the four

laboratories resulting in a BLR of 88%. As indicated in the statistical report, “this high

reproducibility was underlined by highly consistent EC150 and CV70 values”.

Adding automation as a fifth laboratory would not have had any impact on this BLR

assessment.

Taking in account the 2 studies, 32 out of 38 substances were identically classified in all

four laboratories, resulting in a BLR of 84%.

For each laboratory, the means and the standard deviations of the EC150 and CV70

values were calculated based on the median of the EC150 values obtained in the same

laboratory or, if not applicable, on the single EC150 values obtained by each laboratory.

The between-laboratory reproducibility of the 2 individual read-outs can be considered as

high for EC150 to very high for CV70. Besides, as quantitative information that could

complement the similar quantitative information brought by other assays in Integrated

Testing Strategies to predict potency, the individual read-outs and their variability should

be analysed with regards to the cut-offs determined.

Overall BLR

The main results for the evaluation of the BLR focused on the concordance of the

predictions (sensitizer versus non sensitizer) are summarised in the table below and

reported in Alépée et al. (2015):

Study Test items Laboratories

Ring trial

2013

14 coded items

(11 S + 3 NS)

Bioassay, CiToxLAB,

L'Oréal (± automation)

& WIL Research

11/14 = 79%

BLR

32/38 = 84%

Validation

study 2014

24 coded items

(8 S + 16 NS)

Bioassay, CiToxLAB,


& WIL Research

21/24 = 88%



1.4.3 Identification and discussion of outlying values

Please identify and discuss any outlying values.

Not between-laboratory reproducible U-SENS™ classifications:

6-Methyl coumarin (#05, study 2013): fragrance classified as NS in the LLNA. This test

item was predicted NS only by Bioassay and S in the 3 other laboratories (and

automation). Knowing that some reproducibility issues have been also reported by 3

laboratories, the poor water solubility of this test item might explain this outcome.

Chlorobenzene (#09, study 2013): non cosmetic chemical classified as NS in the LLNA

and in humans (Basketter et al., 2014). This test item was predicted S only by CiToxLAB

and consistently classified NS in the 3 other laboratories (and automation). This test item

has poor water solubility and is known to interact with cell membranes. These 2 potential

interfering factors might eventually explain the non-reproducible classifications in a

laboratory.

Benzyl benzoate (#13, study 2013): fragrance classified as weak sensitizer in the LLNA

but NS in humans (Basketter et al., 2014). This test item was predicted S by 2

laboratories (CiToxLAB and L’Oréal) but NS by the 2 others laboratories (Bioassay and

WIL Research), and by automation. Solubility issues, reported by all laboratories might

explain these discordant classifications. At the concentration of 0.4 g/mL, this chemical

was neither soluble in RPMI or DMSO.

Streptomycin sulphate (#13, study 2014): non cosmetic chemical classified as NS in the

LLNA and in humans (Basketter et al., 2014). This test item was predicted S in

CiToxLAB (in 2 out of 3 experiments, see section 1.2.3) and consistently classified NS in

the 3 other laboratories. The reason for this is unknown.

Benzyl alcool (#15, study 2014): cosmetic ingredient classified as NS in the LLNA. This

test item was predicted S by CiToxLAB (and by automation) in 2 out of 3 experiments

whereas it was consistently classified NS by Bioassay, L’Oréal and WIL Research in the

3 independent experiments performed. These results could be explained by the fact that

this fragrance allergen is volatile.

Vanillin (#19, study 2014): fragrance classified as NS in the LLNA and in humans

(Basketter et al., 2014). This test item was predicted NS by 2 laboratories (Bioassay and

WIL Research) but S by the 2 others laboratories (CiToxLAB and L’Oréal +/-

automation). These results could also be explained by the fact that this substance is

volatile.

1.4.4 Quality system(s) of the testing laboratories



Please state the quality system(s) in place, if any, in the testing laboratories (e.g. GLP, ISO, GCCP). For


The 3 laboratories (Bioassay, CiToxLAB and WIL Research) involved in the WLR/BLR

reproducibility studies were GLP accredited. L’Oréal’s laboratory did not have formally

implemented GLP but meet the basic principles of GLP (see details in section 1.1.12).

1.5 MODULE 5: PREDICTIVE CAPACITY (PC)

1.5.1 Rationale for the selection of test items used for assessing PC

Please describe the criteria applied for selecting the test items used for assessing PC.. Please specify the



selection of test items. If some of these test items were also used to develop the prediction model, please

indicate which. Please append the full list of these test items in the form of a table, including their CAS

number and relevant properties, as Attachment 11.

In order to analyze the predictivity of the U-SENS™ test method as well as to generate

data that could be used for data integration activities, a set of 175 substances has been

evaluated by L’Oréal.

A primary eligibility criterion for the chemical selection was the availability of robust in

vivo data to allow a proper comparative evaluation of in vitro results. As such,

availability of both human (Categorisation of Chemicals According to Their Relative

Human Skin Sensitising Potency – Basketter et al, 2014) and/or LLNA (OECD Test

Guideline 429) in vivo skin sensitization classification data were considered. The Human

data was the main criterion considered for the prediction. According to human, LLNA

and EU-CLP classifications, all potency classes, from extreme sensitizer to non-sensitizer

were represented. The respective distributions are summarised in Figure 5.

Note that 123 out of these 175 substances were previously considered for assessing PC in

the TPF already reviewed by EURL-ECVAM (TM2013-02).

Figure 5: in vivo skin sensitization classification of the 175 substances



All tested substances were mono-substances except one preservative (CAS N° 55965-84-

9, Methyl Chloroisothiazolinone / Methyl Isothiazolinone, MCI/MI).

Furthermore, the substances were assigned to various ingredients classes, depending on

their use as determined internally. About 70% belonged to classes relevant for cosmetic

industries. The most prevalent were fragrances (29%), preservatives (15%) and dyes

(8%) (Figure 6).

Finally, protein reactivity determined by Toxtree software was reported (Figure 7). About

65% of all 175 substances belonged to at least one of the five protein binding classes

described by Aptula and Roberts (2006): Michael acceptor, Schiff base formation, acyl

transfer agent, SN2 (substitution nucleophilic bi-molecular) or SNAr (nucleophilic

aromatic substitution).

Figure 6: Chemical classes of the 175 substances

Figure 7: Protein Binding classes of the 175 substances



1.5.2 Assessment of the predictive capacity of the test method

Please provide all available information on the predictive capacity of the test method. Please describe the

accuracy of the proposed test method with respect to its ability to measure or predict the effect of interest.

The accuracy values (i.e., overall accuracy, sensitivity, specificity, positive and negative predictive values,

false positive and negative proportion) of the proposed test should be compared to that obtained for the

appropriate reference test method (if available) and/or other data or information, especially from the

species of interest (if available). Please append the data in the form of tables and/or figures, as Attachment

12.

Predictive capacity in the inter-laboratory studies

The predictive capacity (PC) of the U-SENS™ test method on the set of 24 tests items of

the validation study 2014 was defined in the independent statistical report. The

parameters describing the predictive capacity were calculated by means of 2x2

contingency tables. Specificity, sensitivity and accuracy were derived by comparing the

final classifications with the reference results that were based on LLNA data, with the

exception of Xylene – a false positive in the LLNA compared to humans (Basketter et al.,

2014) – that was therefore considered negative. As indicated in the report, “All eight

sensitisers were classified as such by all laboratories resulting in a sensitivity of 100%.

The specificity ranged was lowest at CiToxLAB with 81.25% and highest at WIL

Research and Bioassay (100%). Consequently, the accuracy ranged from 87.50% at

CiToxLAB to 95.83% L’Oréal and 100% at WIL Research and Bioassay. On average,

the specificity was 93.75%, the sensitivity 100% and the accuracy 95.83%.”

A similar analyse was performed in order to determine the PC on the set of 38 coded test

items evaluated either in the ring trial 2013 and in the validation study 2014.

The parameters describing the predictive capacity were calculated by means of 2x2

contingency tables. Specificity, sensitivity and accuracy were derived by comparing the

final classifications with the reference results. All 19 sensitisers were classified as such

by 2 laboratories (CiToxLAB and L’Oréal) resulting in a sensitivity of 100% whereas



one of those (benzyl benzoate, a weak sensitizer in LLNA) was misclassified by 2

laboratories (Bioassay and WIL Research) resulting in a sensitivity of 95%. The

specificity ranged was lowest at CiToxLAB with 74% and highest at Bioassay (100%).

Consequently, the accuracy ranged from 87% at CiToxLAB to 95% at L’Oréal and WIL

Research and 97% at Bioassay. On average, the specificity was 89%, the sensitivity 97%

and the accuracy 93%.

Predictive capacity on the extended list of substances (175) evaluated by L’Oréal

Ideally, the real gold standard for establishing an in vitro sensitization predictive test

should be human data. But due to the good degree of correlation between EC3 values and

intrinsic human potency, LLNA remains definitively a strong reference and often

constitutes the basis of choice for the evaluation of reliability of new in vitro tests for

hazard identification of sensitization. Of the 175 substances constituting the database,

166 substances had LLNA data whilst 101 had human data. A total of 92 substances had

both human and LLNA data.

The hazard identification of potent and frequent sensitizers (human categories 1 to 4) was

perfectly performed by U-SENS™, with a sensitivity of 100%. Irrespective of the data

set (N≥74) analyzed, the sensitivity of U-SENS™ against either human or LLNA data

was equal to or above to 89%. When confronted to the 101 human data set, with S

ranging from class 1 to 5 and NS in class 6 (Basketter et al., 2014), U-SENS™ showed a

high sensitivity of 89%, a specificity of 65% and an overall accuracy of 85%.

When focusing on the 92 substances subset for which both human and LLNA data were

available, the predictive capacity of U-SENS™ was comparable with respect to both

referentials, with of 90% sensitivity, 60% specificity and 85% accuracy with regards to

human data and 92% sensitivity, 55% specificity, and 84% accuracy with regards to

LLNA. Despite the lower specificity, we concluded that the predictive ability of U-

SENS™ is comparable for both human and LLNA data.

With the aim of evaluating the overall predictive capacity of U-SENS™ on the largest set

of available data (human and LLNA), the prediction was then determined on the 175

substances.

The reference data were considered as follows:

- The human class was firstly considered. The substances classified in vivo in the classes

1 to 5 were considered as sensitizers and the substances classified in class 6 were

considered as non-sensitizers.

- If no Human class was attributed to the substance, the LLNA classification was then

considered.

The following Cooper statistics were calculated based on these data given a specificity of

79%, a sensitivity of 89%, an overall accuracy of 87% and a kappa of 62.

Overall PC



The main results for the evaluation of the PC are summarised in the table below:

1.5.3 Identification and discussion of false predictions

Please identify and discuss any false predictions (e.g. false positives and false negatives).

7 false positives:

Membrane disrupting substances can theoretically lead to false positive results due to a

non-specific increase of CD86 expression induced by release of intracellular soluble

factors or cell surface receptors. Indeed, 3 out of 7 U-SENS™ false positives relative to

the in vivo reference classification were surfactants (#86: sodium lauryl sulfate; #90:

octanoic acid, #96: Tween 80). Also phenol (#97), which is known to interact with cell

membranes and therefore also used as a disinfectant, was classified as sensitizer.

Two fragrances, diethyl phthalate (#92) and 6-methyl coumarin (#165), and a non-

cosmetic ingredient, the diethyl toluamide (#99), were also classified false positives. The

reasons for misclassifications remind unclear.

15 false negatives:

Phthalic anhydride (#113), a strong LLNA sensitizer and a human respiratory sensitizer,

is known to undergo rapid hydrolysis (half-life less than a minute at 25°C) to the

presumably non sensitizer phthalic acid (OECD 2005), upon contact with water. The

hydrolysis, which can be assumed to take place in the U-SENS™ cell culture medium

incubated at 37°C, but not during the topical application in the LLNA (using acetone/

olive oil-based vehicles), may potentially explain the false-negative result of phthalic

anhydride in vitro. This is the only false negative identified as Strong Sensitizer in

LLNA.

4 out of 15 substances were classified Moderate or Weak in the LLNA (no Human class):

3,4-Dihydrocoumarin (#135), diethylenetriamine (#137), 1-bromoeicosane (#138) and

oxalic acid (#151).

9 out of 15 substances were classified in the human potency category 5 (Basketter et al.,

2014) which criteria is a “rare cause of ACD except perhaps in special circumstances,

e.g. use in topical medicaments”. Most of these substances are ingredient used in

Cosmetics: anisyl alcool (#61), isopropyl myristate (#67), methyl salicylate (#71), 4-



aminobenzoic acid (#73), hydrocortisone (#76), propylene glycol (#77), isopropanol

(#78) and butylene glycol (#83), except pyridine (#70). Most of them are non-reactive

according to Toxtree (7 substances #67, #70, #71, #73, #77, #78 and #83).

1.6 MODULE 6: APPLICABILITY DOMAIN (AD)

1.6.1 Applicability of the test method identified through testing

Please identify the applicability of the test method on the basis of experimental evidence. In the case of

chemicals, indicate the chemicals and/or chemical categories (e.g. based on functional groups and/or

physicochemical properties) for which the test method makes reliable and relevant predictions.

A wide diversity of use categories and chemical reactivities was selected in order to

evaluate the applicability domain of the U-SENS™ test method. The database composed

of 175 substances was composed of cosmetics and non-cosmetics ingredients in a ratio of

70/30. Several classes of cosmetics ingredients (fragrances, dyes, preservatives, actives,

surfactants and UV filter) potentially inducing interferences in the U-SENS™ test

method (volatility, color, cytotoxicity, solubility reproducibility), several reactivity

classes (Michael acceptors, Schiff base formation, bi-molecular and aromatic

nucleophilic substitutions and acyl transfer agents according to Toxtree (Patlewicz et al.,

2008)) amongst which pre- or pro-haptens were therefore evaluated.

When focusing on the false negative and false positive substances, no specific class can

be pointed out or excluded from the applicability domain, the misclassified substances

being equally distributed among all classes.

Indeed, the predictive capacity of the U-SENS™ test method was comparable regardless

of the reactivity classes with accuracies of 88% for chemicals classified as acyl transfer

agent (2/16 misclassified) or nucleophilic substitutions (2/17 misclassified), 93% for

chemicals classified as Schiff base formation (2/27 misclassified) and 98% for chemicals

classified as Michael acceptor (1/43 misclassified). While the accuracy obtained for the

chemicals classified as non-reactive toward proteins (“no binding”) is weaker (45/58 =

78) especially with 7 borderline in vivo sensitizers (i.e. classified in the Human potency

category 5, (Basketter et al., 2014, #67, #70, #71, #73, #77, #78 and #83) that were

misclassified.

Substances that have been reported to be pre-haptens like 1,4-dihydroquinone (#27), 3-

metylcatechol (#107), isoeugenol (#18), and 1,4-phenylenediamine (#5), or pro-haptens

like geraniol (#54), cinnamic alcool (#40), aniline (#57), 2-aminophenol (#14), 1-

naphthol (#120), eugenol (#38), and 2-methoxy-4-methylphenol (#136) (Bertrand et al.,

1997; Smith and Hotchkiss, 2001; Smith-Pease et al., 2003) were all correctly predicted

by the MUSST, showing that the U937 cells are well equipped to allow either

spontaneous oxidation or metabolic activation.



The question of the pertinence of testing lipophilic chemicals with high octanol-water

partition coefficients in a water based cell assay has been pointed out, suggesting criteria

of exclusion from the applicability domain of another dendritic cell activation assay

(Takenouchi et al., 2013). In the present study, the U-SENS™ test method was able to

correctly predict all of these tested substances: abietic acid (#39), hexyl cinnamic

aldehyde (#62), benzyl benzoate (#63), undec-10-enal (#142), 12-bromo-1-dodecanol

(#143), 1-bromohexane (#148), benzyl cinnamate (#153) and cyclamen aldehyde (#156).

Color interference with the fluorescent flow cytometry measurement of coloring

substances like dyes can also lead to false negative results. However, none of the 15 U-

SENS™ false negatives relative to the in vivo reference classification were dyes nor did

induce such interference. Beside, all the 13 tested dyes were correctly classified

sensitizers in the U-SENS™ test method.

1.6.2 Limitations of the test method identified through testing

Please identify on the basis of experimental evidence the limitations of the test method. In the case of

chemicals, indicate the chemicals and/or chemical categories (e.g. based on functional groups and/or

physicochemical properties) for which the test method has been shown not to be applicable to.

Technical limitations

- Solubility: the tests substances have to be dissolved in a solvent compatible with the

cell culture conditions. Therefore, for substances that not enough soluble in the final

buffered aqueous medium with or without pre-solubilisation in DMSO, precipitation can

occur leading the actual applied concentration to be inaccurate (most of the time lower

than expected) and then to potentially false negative results (no experimental evidence in

the submitted data). Solubility issues can also harm the reproducibility of the results

(examples: dimethylaminopropylamine (#22) discussed in section 1.2.3, 6-methyl

coumarin (# 165), chlorobenzene (#160) and benzyl benzoate (#63) discussed in section

1.4.3).

- Stability: as with many in vitro methods, substances which are not stable in the test

conditions because of hydrolysis or other chemical reactions cannot be reliably tested

(example: phthalic anhydride (PC #113) discussed in section 1.5.3).

- Interferences with flow cytometry analysis: some substances can colour the cells.

Hair dye components are obvious examples of such chemicals. Depending on the

wavelength, this colour can interfere with the fluorescent flow cytometry measurement.

The isotype control well used for each concentration is there also to correct such

phenomenon to some extent. Indeed, it prevents false positive results. However, in some

cases, too strong a colour can mask the induced CD86 increase leading to false negative

results. Moreover, the colour can interfere with viability determination preventing

accurate CD86 expression measurement. In such cases, the data should not be taken into

account. No experimental evidence was found in the submitted data however there is



clear evidence according to in house experience that fluorescent chemicals cannot be

evaluated with the U-SENS™ test method.

- Volatility: a sealing tape is used during incubation to prevent possible loss of test

substances or collateral effects. Nevertheless, as in many other methods, the loss of test

substances during the previous steps may cause unreliable experimental results in U-

SENS™ (examples: methylmethacrylate (#58) and 4-allylanisole (#152) discussed in

section 1.2.3)

Limitation with regard to applicability

- Membrane disrupting substances: can theoretically lead to false positive results due

to a non-specific increase of CD86 expression induced by release of intracellular soluble

factors or cell surface receptors. Indeed, 3 out of 7 U-SENS™ false positives relative to

the in vivo reference classification were surfactants (#86: sodium lauryl sulfate; #90:

octanoic acid, #96: Tween 80). Also phenol (#97), which is known to interact with cell

membranes and therefore also used as a disinfectant, was identified as a false positive.

#: refers to the number attributed in the table of 175 test items.

1.6.3 Suggested Applicability Domain (AD) of the test method

Please define to the extent possible the (preliminary) AD of the test method on the basis of the information

given in 1.6.1 and 1.6.2. Indicate whether the AD is considered to be wider than the one experimentally

demonstrated and provide justification for this.

The U-SENS™ test method is applicable to all mono-substances or mixtures that are

soluble in the aqueous testing conditions and compatible with flow cytometry analysis,

except membrane disrupting substances (like surfactants). False negatives cannot be

excluded with poor-water soluble substances (like some polymers or vegetal extracts) or

colouring substances (like fluorescent dyes or some other dyes). Finally, results should be

interpreted with care for substances that may interfere with CD86 induction pathways

due to their own biological activity (like some topical drugs or some vegetal extracts).

Besides, due to the fact that mixtures cover a wide spectrum of categories and

composition, and that only limited information is currently available in the public domain

on the testing of mixtures, in cases where evidence can be demonstrated on the non-

applicability of the test method to a specific category of mixtures, the U-SENS™ test

method should not be used for that specific category of mixtures.



2. ESSENTIAL INFORMATION FOR A SPECIFIC

VALIDATION PROCESS

2.1 External Validation Studies (not coordinated by ECVAM)

All validation studies, also those which are not coordinated by ECVAM, should follow some good

validation principles. The following sections of the TST (from 2.1.1 to 2.1.5) apply to all validation studies

not coordinated by ECVAM including external retrospective validation studies and external performance

standards-based validation studies.

2.1.1 Study organisation and management (Project Plan)

For external validation studies (not coordinated by ECVAM) a detailed project plan, describing the study

organisation and management should be produced prior to the initiation of the study and provided as

Attachment 13 (see Explanatory Note to the TST on pages 2-3). Please briefly summarise here below how

the study was designed (e.g. number of participating laboratories, number of replicates within a single

experiment, number of independent repetitions, etc.) and managed.

The ring trial included 21 substances tested in 3 independent experiments by the lead

laboratory, L’Oréal. As study product coordinator, an independent unit of L’Oréal

weighed, coded and distributed 14 out of 21 chemicals that were tested once in 3 other

laboratories: Bioassay, CiToxLAB and WIL Research. As an add-on, the 21 tests items

were tested once on an automated U-SENS™ version. A pre-submission was submitted

to EURL-ECVAM in 2013, leading to a Go decision to proceed to the validation study in

2014.


24 substances were evaluated during the validation study 2014. The test items were

acquired, weighed, coded and distributed by an independent Study Product Coordinator.

Data analysis was conducted by an independent Study Data Coordinator, with whom the

participating laboratories were allowed to communicate during the testing and data

analysis only and to whom exclusively all study results had to be submitted. The

statistical analysis of the reproducibility was conducted blind: the code was broken only

for the predictive performance analysis. All these test items were evaluated once by four

laboratories, Bioassay, CiToxLab, L’Oréal and WIL Research. Fifteen out of twenty-four

substances were tested in 3 independent experiments by all laboratories with three

differently coded samples provided.

As an add-on, all coded samples were tested once on the automated MUSST version,

except for the solubility testing (information provided by the L’Oreal lead laboratory).

2.1.2 Study objective and goals

Please specify the objective and goals of the study (e.g. evaluation of the transferability of the test method,

evaluation of WLR and/or BLR, and/or assessment of PC) here below.



The test method has already been submitted to EURL-ECVAM in 2009 and judged

already at that time to be biologically and mechanistically relevant, and sufficient

optimised and standardised to enter an EURL ECVAM validation process. In fact the test

method was included in an EURL ECVAM coordinated validation study involving the

assessment of other two test methods (DPRA and h-CLAT). Following the evaluation by

the Validation Management Group of the experimental results generated by four

laboratories during the first phase of the blind testing aimed to provide preliminary

information on the BLR, the MUSST test method (recently renamed U-SENS™) was

withdrawn from the EURL ECVAM study due to the poor reproducibility, mainly due to

the high frequency of inconclusive classifications.

Subsequently L’Oréal undertook optimisation work of aspects of the test method, mainly

to define a prediction model (PM) to identify a substance only as sensitizers or non-

sensitizers. As previously defined, a substance was overall predicted as S or NS in an

experiment in case of a majority of S or NS runs (i.e. generally two S or NS). The

improvement was defined for the substances previously classified as inconclusive, where

a sum of scores determined by the application of six rules on viability and CD86 means

values was calculated in order to come to a final classification (Gomes et al., 2014).

L’Oreal coordinated an external ring trial in 2013 to evaluate the transferability and

reproducibility of the updated test method in order to obtain a preliminary assessment of

the reliability of the test method. A preliminary assessment of PC was also done on a set

of 123 substances tested in house. After the pre-submission of the results (TM2013-02),

L’Oréal was invited to progress to the next step of the EURL-ECVAM submission

process.

The validation study was then conducted more formally with an independent product

study coordination and an independent study data coordination, following EURL-

ECVAM recommendations to increase the sample size for the evaluation of the BLR, to

extend the WLR assessment to three independent experiments in more than the one

laboratory and provide a calculation of the PC based on the prediction generated with

coded test items. In addition, the PC was calculated on an expanded set of a total of 175

substances tested in house. The test method reliability was primarily assessed regarding

the classification, sensitizer vs. non-sensitizer. As an add-on the reliability of the

automated test method was also assessed.

2.1.3 Summary of the study results

Please briefly summarise the study main results, from the information included in the other sections of the

TST, in light of the objectives and goals set for the study (e.g. agreement of the results for WLR and BLR

when experimental data have been generated using the same test items and adhering to the same protocol,

accuracy of the test method to measure or predict the effect of interest).



Module

Ring trial

2013

21 tests items

(11 S + 10 NS)L'Oréal 20/21 = 95%

L'Oréal 15/15 = 100%

Bioassay 14/15 = 93%

CiToxLAB 11/15 = 73%

WIL Research 15/15 = 100%

automation 14/15 = 93%

Module 3

Transferability

Ring trial

2013

14 coded items

(11 S + 3 NS)

Bioassay, CiToxLAB,


& WIL Research

11/14 = 79%

Specificity Sensitivity Accuracy

Bioassay 100% 95% 97%

CiToxLAB 74% 100% 87%

L'Oréal 89% 100% 95%

WIL Research 95% 95% 95%

Mean 90% 98% 94%

automation 84% 95% 89%

U-SENS™

database

175 tests items

(141 S + 34 NS)L'Oréal 79% 90% 88%

Results

Module 2

WLR

WLR

34/35 = 97%

Validation

study 2014

15 coded items

(6 S + 9 NS)

55/60 = 92%

69/75 = 92%

Module 4

PC

Ring trial

2013

+

Validation

study 2014

38 coded items

(19 S + 19 NS)

Bioassay, CiToxLab and WIL Research were ready to enter in the ring trials to assess the WLR (module

4) and BLR (module 4).

Module 4

BLR

BLR

32/38 = 84%

Validation

study 2014

24 coded items

(8 S + 16 NS)

Bioassay, CiToxLAB,


& WIL Research

21/24 = 88%

2.1.4 List of test items used in the validation study

Please provide as Attachment 14, a table listing the test items used in the validation study and specify for

each test item whether it has been used for a) test method development, b) WLR and/or BLR assessment

and c) predictive capacity assessment.

The list of the 175 test items used for the PC assessment was provided. In this list, the

tests items used for the TF, the WLR and BLR were identified.

2.1.5 Study conclusions

Please provide your conclusions regarding the outcome of the study [e.g. is the test method easily

transferable to other laboratories? Is the test method generating reproducible results within a single

laboratory and between laboratories? Is the test method sufficiently accurate compared to the reference

data (e.g. in vivo data)/ target accuracy and reliability values (for performance standards-based validation

studies)?], in the light of the study objectives and in consideration of the extent to which such conclusions

are supported by the study results.



The U-SENS™ test method is modelling the dendritic cell activation upon exposure to

chemicals. Like dendritic cells, upon contact with sensitizers, U937 human myeloid cells

are activated and increase the CD86 expression. Cell viability is assessed using

propidium iodide exclusion. Both parameters are measured by flow cytometry and used

to classify a substance as a sensitizer or a non-sensitizer.

The aim of this study was to demonstrate the transferability and reliability of the U-

SENS™ test method in four laboratories and define its predictivity.

The transferability of the U-SENS™ test method was demonstrated through a ring study

(in 2013) and a more formal validation study (in 2014) with three laboratories. Briefly,

38 coded chemicals were tested. The intra-laboratory reproducibility (WLR) study was

assessed based on 15 coded chemicals tested in 3 independent experiments in 4

laboratories, resulting in a WLR of 92%. Thirty two out of the 38 coded chemicals were

consistently classified (sensitizer vs non sensitizer) by all laboratories resulting in an

inter-laboratory reproducibility (BLR) of 84%. Moreover, an automated evaluation study

conducted in parallel showed similar WLR and BLR levels. A sensitivity of 98%,

specificity of 90% and accuracy of 94% combining the 2 studies were obtained, knowing

that assessing predictive capacity was not a primary objective.

In fact, the predictive performance of the U-SENS™ test method was assessed in detail

by comparing it comprehensively with human and LLNA data of a total of 175

substances. The U-SENS™ test method had a specificity of 79%, a sensitivity of 90%

and an accuracy of 88%.

Taken together, this information indicates the potential of the U-SENS™ test method to

contribute to the discrimination between sensitizers and non-sensitizers, although use of

U-SENS™ as a standalone method for this purpose will not be recommended as stated as

well for all preceded validated test methods addressing this endpoint.

2.1.6 Recommendations

Considering the study objectives and outcome, please provide recommendations, where applicable,

regarding a) possible improvements of the test method (e.g. in relation to the SOP, prediction model etc.),

b) future activities to be undertaken to better characterise the performance of the test method in view of its

envisaged use (e.g. better characterisation of the PC by testing additional coded chemicals), c) the possible

current use of the test method (e.g. screening method, partial replacement method as part of a testing

strategy, full replacement method), d) any other recommendation on future activities.

The U-SENS™ test method addressing one biological mechanism of the skin

sensitisation pathway (AOP key event 3) is foreseen to be combined with complementary

information and evaluated in the context of Integrated Approaches to Testing and

Assessment (IATA). In such context, the U-SENS™ test method is part of a decision

strategy for skin sensitization hazard identification based on in silico, in chemico, and in

vitro data analysed using a statistic “staking” meta-model (Gomes et al., 2012). The

decision strategy has been already submitted to OECD as a case study in the context of

the draft guidance document on the evaluation and application of IATA for skin

sensitisation



The U-SENS™ test method is also foreseen to be a part of an integrated test battery

which will be able to fully replace the in vivo test methods (i.e. LLNA, Buehler and

Magnusson & Kligman) to predict the sensitizing potential of the chemicals in humans

(risk and safety assessment).

In such context, the U-SENS™ test method is part of The European Cosmetics Industry

Trade Association current (Cosmetics Europe) program. Following the evaluation of 16

non-animal test methods using 10 substances (Reisinger et al., submitted), the U-SENS™

test method has been selected for the testing strategy composition on more than 100

substances, for which both LLNA and human data are available. The potential

contribution of read-out parameters (EC150 and CV70) - instead of currently applied

prediction models - to the strategy will be explored. This will allow re-assessment of

already proposed testing strategies with new data. Ultimately, the testing strategy -

combined with bioavailability and skin metabolism data and exposure consideration – is

envisaged to allow establishment of a data integration approach for skin sensitization

safety assessment of cosmetic ingredients.



3. ADDITIONAL INFORMATION

3.1 Additional information

Please add any additional information that was not covered in the TST.

Follow up on ESAC recommendation & OECD Expert Working Group

meeting: Addendum - December 2016

Background

The test method as described above has been submitted to EURL ECVAM in November

2014 and has been peer-reviewed by the independent EURL Scientific Advisory

Committee (ESAC) in 2016 (EC EURL ECVAM, 2016). ESAC concluded that in terms

of test performance, the U-SENS™ test method appears to be comparable to the currently

available validated animal-free test methods in general, and to the h-CLAT method

specifically. ESAC therefore stated that the U-SENS™ test method was ready to be

considered for regulatory use in the context of an IATA for skin sensitisation and remains

a useful tool for screening and early decision making during product development, within

the applicability domain defined in the validation study (OECD, 2016). However, ESAC

had concerns with the complexity of the prediction model and the predictivity of non-

sensitisers (specificity of 33 %) of the 'six rules' for resolving inconclusive results. Given

that the 'six rules' appear to change 'inconclusive' to 'sensitisers' in the majority of cases,

the test developers are recommended to consider removing these 'six rules' from the

prediction model and to consider any inconclusive result as positive by default. This

would significantly simplify the prediction model and would allow standardising the

maximum number of runs per experiment to three.

Accordingly to the ESAC recommendation, the prediction model was revised and a

simplified version was presented at the OECD Expert Working Group meeting in

November 2016. The group agreed that the ESAC recommendation related to the

prediction model simplification was satisfactorily addressed. It was clarified that the

validation report will be revised with the addition of an addendum including the data that

were presented to support the simplification.

The present module presents the data using the revised prediction model, and the

recalculated relevance and reliability of the method (e.g. within and between laboratory

reproducibility and performance of the assay compared to the LLNA and to human data).



The Prediction Model

Data exploitation is performed with percentage of CD86-positive cells among the viable

cells (cell viability ≥70%). The stimulation index (S.I.) of CD86 is calculated (treated

cells versus control cells). The prediction model of the U-SENS™ classifies the test

chemical as NEGATIVE or POSITIVE, which itself consisted of at least two valid runs

(performed on a different day) with individual conclusions.

The prediction model was simplified as described in the Figure 1.

First experiment and CD86 S.I. ≥

150% only at the highest

concentration

Negative

CD86 S.I. ≥ 150% with dose-response

No Conclusion

CD86 S.I. less than 150% at all

concentrations and no

interference

Positive

Interference(s)and/or CD86 S.I. ≥

150% without dose-

response

INConclusive

NegativeNo Conclusion Positive Positive

BEFORE

AFTER

RUN

Figure 1: Schematic diagram of the individual run conclusions before and after the

simplification the Prediction Model

Initially, the run was concluded 'inconclusive', if the S.I. of CD86 was equal to or greater

than 150% without any dose-response relationship at non-cytotoxic tested dose (with cell

viability ≥ 70%) or an interference (cytotoxicity, solubility or colour) was observed.

Therefore, a 'six rules' interpretation was needed to derive a single prediction

(NEGATIVE or POSITIVE) from at least two independent runs.

In the actual prediction model (following ESAC recommendation, referred to ‘After’ in

Figure 1), these 'six rules' were removed from the prediction model and any inconclusive

result is therefore considered as positive by default.

It is important to note that three individual conclusions remained identical:

- The run is concluded NO CONCLUSION (NC), if, in the first run, the S.I. of CD86 is

higher or equal to 150% at the highest non-cytotoxic concentration only.



- The individual conclusion is considered Negative (N) if the S.I. of CD86 is less than

150% at all non-cytotoxic concentrations (cell viability ≥ 70%) and if no interference

(cytotoxicity, solubility or colour) is observed.

- The individual conclusion is considered Positive (P) if the S.I. of CD86 is equal to or

greater than 150% with a dose-response relationship at non-cytotoxic tested dose (with

cell viability ≥ 70%)

An U-SENS™ prediction is considered NEGATIVE if at least two independent runs are

Negative (N) (Figure 2). An U-SENS™ prediction is considered POSITIVE if at least

two independent runs are Positive (P). There is an exception if, in the first run, the S.I. of

CD86 is higher or equal to 150% at the highest non-cytotoxic concentration only. The run

is then concluded NO CONCLUSION (NC), and additional concentrations (between the

highest non cytotoxicity concentration and the lowest cytotoxicity concentration) should

be tested in additional runs. A run NC conducts automatically to the need of at least 2

more runs, and to a fourth run in case runs 2 and 3 are not concordant(N and/or P

independently), (Figure 2). Follow up runs will be considered positive even if only one

non cytotoxic concentration gives a CD86 equal or above 150%, since the dose setting

has been adjusted for the specific test chemical. The final prediction will be based on the

majority result of the three or four individual runs (i.e. 2 out of 3 or 2 out of 4) (Figure 2).



Two first

runs

N & N

Third run

Not

required

Third run

not

required

POSITIVE NEGATIVE

Two first

runs

Third run

NC & P

NC & N

N & P

P & N

NC & P & P

N & P & P

P & N & P

NC & N & N

N & P & N

P & N & N

P & P

Fourth run

POSITIVE

NC & N & P

NC & P & N

NC & N & P & P

NC & P & N & P

NC & N & P & N

NC & P & N & N

POSITIVENEGATIVE NEGATIVE

Third run

Not

required

Third run

Not

required

Figure 2: Prediction model used in the U-SENS™ test method

The data

The data of two available multicentre studies - a trial conducted in 2013 and a validation

study carried out in 2014 - have been used for the reanalysis using the simplified

prediction model. In the validation, all laboratories tested 24 chemicals, 15 of which in

three independent experiments and the remaining nine chemicals in one experiment. In

the 2013 study, L’Oréal tested 21 chemicals in three independent experiments each,

while the other laboratories tested 14 of these 21 chemicals in one experiment. In total,

321 experiments, representing the complete data set; were resampling for the analysis

using the simplified prediction model (see Attachment 1).

Considering the simplified prediction model, the U-SENS classification remained

identical for 315 out of 321 experiments. This resulted in a concordance of 98.1% when

applying the original or simplified prediction model. Table 1 summarises the runs

highlighting the 6 cases of replacement of INC-results that gives a different final

classification. Two substances (methyl methacrylate and benzyl benzoate) were

discordantly classified leading as former false negatives (FN) that are now regarded as

true positives (TP). In addition, three substances (hexane, benzoic acid and polyethylene



glycol in one experiment) with a former true negative (TN) classification become false

positives (FP).

Table 1: The 6 cases of replacement of INC results impacting the final classification.

Run

1

Run

2

Run

3

Run

4

Run

5

Final

classification

Run

1

Run

2

Run

3

Final

classification

80-62-6 Methylmethacrylate Bioassay N INC INC P P NEGATIVE N P P POSITIVE

120-51-4 Benzyl benzoate Bioassay INC INC - - - NEGATIVE P P - POSITIVE

120-51-4 Benzyl benzoate Wil Research INC INC - - - NEGATIVE P P - POSITIVE

110-54-3 Hexane CiToxLab INC INC - - - NEGATIVE P P - POSITIVE

65-85-0 Benzoic acid CiToxLab N P INC INC - NEGATIVE N P P POSITIVE

25322-68-3 Polyethylene glycol CiToxLab INC P N P N NEGATIVE P P - POSITIVE

P: Positive individual run conclusion; N: Negative individual run conclusion; INC: Inconclusive run conclusion

True Negatives ->

False Positives

CASRN Name Laboratories IMPACT

ORIGINAL PM ACTUAL PM

False Negatives ->

True Positives

Relevance and reliability of the U-SENS™

The main results for the evaluation of the within (WLR) - and between (BLR) -laboratory

reproducibility focused on the concordance of the predictions (Positive, P versus

Negative, N) as determined by the results of three independent runs (see Attachment 1)

are summarised in Tables 2 and 3, respectively.

The WLR was assessed in four laboratories: the same 15 coded substances were tested in

the validation study in all laboratories in 2014, and 21 additional substances were tested

in the lead laboratory only in 2013 (Table 2). The WLR for the validation set was 91.5%.

Applying the simplified prediction model, this resulted in an average WLR of 90.0%

demonstrating the robustness of the U-SENS™ against the actual prediction model. Note

that the WLR of the L’Oréal laboratory in the earlier study remained identical and was

comparably high (95.2%).

Table 2: Within-laboratory reproducibility using the original or actual simplified

prediction model

Chemicals Nb 1 lab Chemicals Nb 4 labs

Original PM 21 95,2% 15 91.5%

Actual PM 21 95,2% 15 90,0%

PM: Prediction Model

Ring trial 2013 Validation 2014

The BLR was evaluated by comparing the classification between laboratories. For the

substances tested three times, the more frequent (or median) classification was considered

for this analysis. Overall 84.2% (32/38) substances were identically classified in all four

laboratories independently of the prediction model (Table 3). The proportion of

substances concordantly classified between laboratories slightly decreased from

21/24=87.5% using the original prediction model to 20/24= 83.3% using the actual PM,



and slightly increased from 11/14=78.6% to 12/14=85.7% for the earlier study,

respectively. Using the actual prediction model, the benzyl benzoate, formerly classified

dis-concordantly between laboratories becomes similarly classified in all laboratories,

and the polyethylene glycol becomes misclassified in one laboratory.

Table 3: Between-laboratory reproducibility in 4 laboratories using the original or

actual simplified prediction model

Chemicals

Nb

Ring Trial

(2013)

Chemicals

Nb

Validation

(2014)

Overall (38

chemicals)

Original PM 14 78,6% 24 87,5% 84.2%

Actual PM 14 85,7% 24 83,3% 84.2%

PM: Prediction Model

The parameters specificity and sensitivity used to characterise the predictive capacity of

the U-SENS™ were calculated by means of 2x2 contingency tables comparing

laboratories’ classifications with the reference in vivo results. The specificity and

sensitivity remained identical at Bioassay and L’Oréal using the actual prediction model

compared to the previous PM (Table 4). The specificity range was lowest at CiToxLab

with 68% (13/19 instead of 14/19 substances well classified), and the sensitivity was

higher at Wil Research with 100% (originally 18/19 well classified). To compare to the

original PM, no additional false negative classification could be made. In contrast, a false

positive prediction and a true positive prediction were observed. On average based on 38

substances, the specificity was 88% and the sensitivity 99% using the simplified PM.

Table 4: Predictive capacity over the 38 substances tested in the inter-laboratory studies

using the original or actual simplified prediction model



Specificity % Sensitivity %

(19 NS) (19 S)

Original PM 100 95

Actual PM 100 95

Original PM 74 100

Actual PM 68 100

Original PM 89 100

Actual PM 89 100

Original PM 95 95

Actual PM 95 100

Original PM 90 98

Actual PM 88 99OVERALL 1 FP + 1 TP

PM: Prediction Model; NS: Non-sensitizer in vivo; S: Sensitizer in vivo; P: POSITIVE; N:NEGATIVE; FP: False

Positive; FN: False Negative; TP: True Positive; TN: True Negative

Citoxlab 1 N (TN) => P (FP)

L'Oreal No impact

Wil Research 1 N (FN) => P (TP)

Impact on U-SENS

Classification

Bioassay No impact

Performance of the U-SENS™ compared to the LLNA and to human data

Subsequent to the validation study and to increase the evidence base for the U-SENS™

performance, analysis was performed on 175 substances for which the data were already

published in Piroird and co-workers in 2015 using the original PM. The predictive

capacity was recalculated using the simplified prediction model. Of the 175 substances

constituting the database, 166 substances had LLNA and a total of 92 substances had

both human and LLNA data (see Attachment 2).The hazard identification of potent and

frequent sensitizers (human categories 1-4) was perfectly performed by the U-SENS™

test method, with a sensitivity of 100%. Irrespective of the data set (N≥58) analysed, the

sensitivity of the method against either human or LLNA data was equal or above to 91%

(Figure 3A). When confronting the 101 human data set with S ranging from class 1 to 5

and NS in class 6, the U-SENS™ test method showed a high sensitivity of 89%, a

specificity of 65% and an overall accuracy of 85% (Figure 3B). Focusing on the 166

substances subset for which LLNA data were available, the predictive capacity of the

method was comparable with respect to human data.

Figure 3: Predictive performance of the U-SENS™ assay compared to human and LLNA

data using the simplified prediction model. Human categories were dichotomised by

considering categories 5-6 (Basketter et al, 2014) as NS (3A) or category 6 only as NS

(3B).N: number of substances. The values in parenthesis are the number on substances correctly predicted

out of the evaluated substances. SP: specificity; SE: sensitivity; Acc: accuracy.



N = 92

&

N = 101SP: 47% (20/43) SE: 100% (58/58)Acc: 77% (78/101)Kappa: 50%

N = 175 [101 + 74]SP: 55% (33/60) SE: 96% (110/115)Acc: 82% (143/175)Kappa: 56%

N = 74N = 9

N = 166SP: 65% (24/37) SE: 91% (118/129) Acc: 86% (142/166)Kappa: 57%

Human classes 1-4 SHuman classes 5-6 NS

Fig 3A

N = 166SP: 65% (24/37) SE: 91% (118/129) Acc: 86% (142/166)Kappa: 57%

N = 92

&

N = 101SP: 65% (11/17) SE: 89% (75/84)Acc: 85% (86/101)Kappa: 50%

N = 175 [101 + 74]SP: 71% (24/34) SE: 90% (127/141)Acc: 86% (151/175)Kappa: 58%

N = 74N = 9

Human classes 1-5 SHuman class 6 NS

Fig. 3B

Conclusions

Considering all inconclusive results as sensitiser by default instead of applying the 'six

rules' slightly decrease the number of false negatives with only an equally small increase

of false positives. The U-SENS™ assay, using the simplified prediction model, relies on

a more conservative approach with respect to the original prediction model. The within-

and between-laboratory reproducibility were comparable with respect to the original

prediction model. Similarly, the predictive performance parameters specificity and

sensitivity were equivalent to the respective point estimates.



The OECD Expert Working Group in November 2016 therefore considers that the ESAC

recommendation related to the prediction model simplification was satisfactorily

addressed, and that the test method is ready to be considered for regulatory use.

3.2 List of references

Please provide a list of scientific or other appropriate references, briefly describing their relevance with

regard to the submitted test method. Please include all publications that provide background information

on the test method’s biological and mechanistic relevance. If available, please include publications that

provide direct information of the performance of the proposed test method. In cases of submissions of

putative similar or updated test methods, please include publications relating to the validated reference test

method(s) on which – if available – the performance standards (PS) are based. Please append publications

as electronic files (pdf or scans of paper copies) as Attachment 17.

EC EURL ECVAM. (2016). ESAC Opinion No. 2016-03 on the L'Oréal-coordinated

study on the transferability and reliability of the U-SENS™ test method for skin

sensitisation testing. EUR 28178 EN; doi 10.2787/815737. Available at:

[http://publications.jrc.ec.europa.eu/repository/handle/JRC103705].

OECD. (2016). Series on Testing & Assessment No. 256: Guidance Document On The

Reporting Of Defined Approaches And Individual Information Sources To Be Used

Within Integrated Approaches To Testing And Assessment (IATA) For Skin

Sensitisation, Annex 1 and Annex 2. ENV/JM/HA(2016)29. Organisation for Economic

Cooperation and Development, Paris. Available at:

[https://community.oecd.org/community/iatass].

4. Abbreviations used in the TST

AD Applicability Domain

BLR Between Laboratory Reproducibility

ECVAM European Centre for the Validation of Alternative Methods

ESAC ECVAM’s Scientific Advisory Committee

GCCP Good Cell Culture Practice

GLP Good Laboratory Practice

IPRs Intellectual Property Rights

PC Predictive Capacity

PM Prediction Model

PS Performance Standards

TF Transferability

TST Test Submission Template



WLR Within Laboratory Reproducibility

5. Note regarding terms

Below is a list of terms related to test method validation, as defined in OECD Guidance

Document No 34 (OECD, 2005) or defined for the purpose of the TST (identified with an

*).

*Benchmark: A test item that produces a midrange response in the test method, i.e. to

assess variability of the test system over time. Please note that if positive controls elicit a

too strong response, they cannot be used as benchmark.

Between-laboratory reproducibility: A measure of the extent to which different

qualified laboratories, using the same protocol and testing the same substances, can

produce qualitatively and quantitatively similar results.

*Biological relevance: Relates to the extent to which the test methods models or

reproduces the biological properties of target organ/system or species of interest (e.g.

mechanism of action, cell types, cytoarchitecture).

Endpoint: The biological or chemical process, response, or effect, assessed by a test.

False negative: A substance incorrectly identified as negative or non-active by a test

method, when in fact it is positive or active.

False negative rate: The proportion of all positive substances falsely identified by a test

method as negative. It is one indicator of test method performance.

False positive: A substance incorrectly identified as positive or active by a test, when in

fact it is negative or non-active.

False positive rate: The proportion of all negative (non-active) substances that are

falsely identified as positive. It is one indicator of test performance.

*Negative Control: The vehicle used and/or a test item known not to elicit a positive

response in the test method.

*Non-qualified test: A test that does not meet the acceptance criteria defined in the

protocol.

Performance standards: Standards, based on a validated test method, that provide a

basis for evaluating the comparability of a proposed test method that is mechanistically

and functionally similar. Included are (1) essential test method components; (2) a



minimum list of reference chemicals selected from among the chemicals used to

demonstrate the acceptable performance of the validated test method; and (3) the

comparable levels of accuracy and reliability, based on what was obtained for the

validated test method, that the proposed test method should demonstrate when evaluated

using the minimum list of reference chemicals.

*Positive Control: A test item well known to elicit a positive response in the test

method.

*Predictive capacity: The ability of a test method to make relevant predictions on

defined biological effects (e.g. human health effects).

Prediction Model: a formula or algorithm (e.g., formula, rule or set of rules) used to

convert the results generated by a test method into a prediction of the (toxic) effect of

interest. Also referred to as decision criteria. A prediction model contains four elements:

(1) a definition of the specific purpose(s) for which the test method is to be used; (2)

specifications of all possible results that may be obtained, (3) an algorithm that converts

each study result into a prediction of the (toxic) effect of interest, and (4) specifications as

to the accuracy of the prediction model (e.g., sensitivity, specificity, and false positive

and false negative rates). Prediction models are generally not used in in vivo

ecotoxicological tests.

*Qualified test: A test that meets the acceptance criteria defined in the protocol.

Relevance: Description of relationship of the test to the effect of interest and whether it

is meaningful and useful for a particular purpose. It is the extent to which the test

correctly measures or predicts the biological effect of interest. Relevance incorporates

consideration of the accuracy (concordance) of a test method.

Reliability: Measures of the extent that a test method can be performed reproducibly

within- and between laboratories over time, when performed by using the same protocol.

It is assessed by calculating intra- and inter-laboratory reproducibility.

Reproducibility: The agreement among results obtained from testing the same substance

using the same test protocol (see Reliability).

*Run: A run consists of one or more test items tested concurrently, and if applicable,

also with a positive and a negative control.

Sensitivity: The proportion of all positive/active substances that are correctly classified

by the test. It is a measure of accuracy for a test method that produces categorical results,

and is an important consideration in assessing the relevance of a test method.

Specificity: The proportion of all negative/inactive substances that are correctly

classified by the test. It is a measure of accuracy for a test method that produces



categorical results and is an important consideration in assessing the relevance of a test

method.

*Test: The use of a test method for testing a single test item within a single experiment

(can be composed of one single measurement or several measurements conducted in

parallel, i.e. “replicates”).

*Test Item: Any entity to be tested with the test method. These may be single

substances, mixtures, biologicals, etc.

Test method: A process or procedure used to obtain information on the characteristics of

a substance or agent. Toxicological test methods generate information regarding the

ability of a substance or agent to produce a specified biological effect under specified

conditions. Used interchangeably with “test” and “assay”.

*Test System: A test method is usually composed of three elements: (i) test system, (ii)

protocol, (iii) prediction model. The test system is the biological/chemical system that is

exposed to the test items to obtain experimental data.

Transferability: The ability of a test procedure to be accurately and reliably performed

in independent, competent laboratories.

*Variability: Within- and between laboratory variability are also referred to as within-

and between laboratory reproducibility. Although reproducibility is generally the

preferred term, it refers to the same concept as variability, often used in the literature. The

latin prefixed intra- and inter- are often replaced with the English translation within- and

between.

Within-laboratory reproducibility: A determination of the extent that qualified people

within the same laboratory can successfully replicate results using a specific protocol at

different times.

6. References Ade, N., Martinozzi-Teissier S., Pallardy M., Rousset F., 2006. Activation of U937 cells by

contact sensitizers: CD86 expression is independent of apoptosis. J Immunotoxicol.

2006;3(4):189-97.

Aiba, S., Terunuma, A., Manome, H., Tagami, H., 1997. Dendritic cells differently respond to

haptens and irritants by their production of cytokines and expression of co-stimulatory molecules.

Eur. J. Immunol. 27:3031–3038.



Alépée, N., Piroird, C., Aujoulat, M., Dreyfuss, S., Hoffmann, S., Hohenstein, A., Meloni, M.,

Nardelli, L., Gerbeix, C., Cotovio, J., 2015. Prospective multicentre study of the U-SENS test

method for skin sensitization testing. Toxicol. In Vitro accepted.

Aptula A.O. and Roberts D.W., 2006. Mechanistic applicability domains for non-animal-based

prediction of toxicological end points: general principles and application to reactive toxicity.

Chem. Res. Toxicol., 19, 1097-1105.

Balls M, Blaauboer BJ, Fentem JH, Bruner L, Combes RD, Ekwall B, Fielder RJ, Guillouzo A,

Lewis RW, Lovell DP, Reinhardt CA, Repetto G, Sladowski D, Spielmann H & Zucco F (1995)

Practical Aspects of the Validation of Toxicity Test Procedures. The Report and

Recommendations of ECVAM Workshop 5. ATLA 23: 129-147.

Bauch, C., Kolle, S.N., Fabian, E., Pachel, C., Ramirez, T., Wiench, B., Wruck, C.J., van

Ravenzwaay, B., Landsiedel, R., 2011. Intralaboratory validation of four in vitro assays for the

prediction of the skin sensitizing potential of chemicals. Toxicol. In Vitro 25 (6), 1162–1168.

Basketter, D., Alépée, N., Ashikaga, T., Barroso, J., Gilmour, N., Goebel, C., Hibatallah, J.,

Hoffmann, S., Kern, P., Martinozzi-Tessier, S., Maxwell, G., Reisinger, K., Sakaguchi, H.,

Schepky, A., Tailhardat, M., Templier, M., 2014. Categorization of Chemicals According to

Their Relative Human Skin Sensitizing Potency. Dermatitis 25(1), 11-21.

Bertrand, F., Basketter, D. A., Roberts, D. W., Lepoittevin, J.P., 1997. Skin sensitization to

eugenol and isoeugenol in mice: Possible metabolic pathways involving ortho-quinone and

quinone methide intermediates. Chem. Res. Toxicol. 10, 335–343

Council Directive 76/768/EEC of 1976-07-27 recently updated as Cosmetics Regulation:

REGULATION (EC) No 1223/2009

Coutant, K. D., de Fraissinette, A. B., Cordier, A., Ulrich, P., 1999. Modulation of the activity of

human monocyte-derived dendritic cells by chemical haptens, a metal allergen, and a

staphylococcal superantigen. Toxicol. Sci. 52:189–198.

EU, 2006. Regulation (EC) No 1907/2006 of the European Parliament and of the Council of 18

December 2006 concerning the Registration, Evaluation, Authorisation and Restriction of

Chemicals (REACH), establishing a European Chemicals Agency, amending Directive

1999/45/EC and repealing Council Regulation (EEC) No 793/93 and Commission Regulation

(EC) No 1488/94 as well as Council Directive 76/769/EEC and Commission Directives

91/155/EEC, 93/67/EEC, 93/105/EC and 2000/21/EC. Official Journal No L 396, p. 1-1355

EU, 2008 Regulation (EC) No 1272/2008 of the European Parliament and of the Council of 16

December 2008 on classification, labelling and packaging of substances and mixtures, amending

15 and repealing Directives 67/548/EEC and 1999/45/EC, and amending Regulation (EC) No

1907/2006. Official Journal No L 353, p. 1-1355



Gomes, C., Noçairi, H., Thomas, M., Collin, J.F., Ibanez, F. , Saporta, G., 2012. Stacking

prediction for a binary outcome. COMPSTAT, 20th International Conference on Computational

Statistics, Limassol, Cyprus. 2012: 271-282.

Gomes, C., Nocairi, H., Thomas, M., Collin, J.-F., Saporta, G., 2014. A simple and robust scoring

technique for binary classification. Artificial Intelligence Research. 3(1), 52-58.

ICCVAM, “Interagency Coordinating Committee on the Validation of Alternative Methods. The

Murine Local Lymph Node Assay: a test method for assessing the allergic contact dermatitis

potential of chemicals/compounds. The results of an independent peer review evaluation

coordinated by the ICCVAM an the NICEATM,” National Institute of Environmental Health

Sciences, NIH Publication no. 99-4494, http://www.iccvam.niehs.nih.gov/.

Natsch, A., Ryan, C.A., Foertsch, L., Emter, R., Jaworska, J., Gerberick, F., Kern, P., 2013. A

dataset on 145 chemicals tested in alternative assays for skin sensitization undergoing

prevalidation. J. Appl. Toxicol. Apr 9 (Epub).

OECD. 1992. Skin Sensitisation, Test Guideline No. 406, Guidelines for Testing of Chemicals,

OECD, Paris. Available at: [http://www.oecd.org/env/testguidelines]

OECD. (2005). Guidance document on the validation and international acceptance of new or

updated test methods for hazard assessment, Series on Testing and Assessment, No. 34. OECD,

Paris.

OECD. 2010. Skin Sensitization: Local Lymph Node Assay, Test Guideline No. 429, Guidelines

for the Testing of Chemicals, OECD, Paris. Available at:

[http://www.oecd.org/env/testguidelines]

OECD (2012a). The Adverse Outcome Pathway for Skin Sensitisation Initiated by Covalent

Binding to Proteins. Part 1: Scientific Evidence. Series on Testing and Assessment No. 168.

Accessible at:

http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=ENV/JM/MONO(2012

)10/PART1&docLanguage=En

OECD (2012b). The Adverse Outcome Pathway for Skin Sensitisation Initiated by Covalent

Binding to Proteins. Part 2: Use of the AOP to Develop Chemical Categories and Integrated

Assessment and Testing Approaches. Series on Testing and Assessment No. 168. Accessible at:

http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=ENV/JM/MONO

(2012)10/PART2&docLanguage=En

Patlewicz, G., Jeliazkova, N., Safford, R.J., Worth, A.P., Aleksiev, B., 2008. An evaluation of the

implementation of the Cramer classification scheme in the Toxtree software. SAR QSAR

Environ, Res. 19(5-6), 495-524.

Python, F., Goebel, C., Aeby, P., 2007. Assessment of the U937 cell line for the detection of

contact allergens. Toxicol. Appl. Pharmacol. 220, 113-124.

http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=ENV/JM/MONO%20(2012)10/PART2&docLanguage=En

http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=ENV/JM/MONO%20(2012)10/PART2&docLanguage=En



Reisinger, K., Hoffmann, S., Alepee, N., Ashikaga, T., Barroso, J., Elcombe, C., Gellatly, N.,

Galbiati, V., Gibbs, S., Groux, H., Hibatallah, J., Keller, D., Kern, P., Klaric, M., Kolle, S.,

Kuehnl, J., Lambrechts, N., Lindstedt, M., Millet, M., Martinozzi-Teissier, S., Natsch, A.,

Petersohn, D., Pike, I., Sakaguchi, H., Schepky, A., Tailhardat, M., Templier, M., van Vliet, E.,

Maxwell, G. 2014. Systematic evaluation of non-animal test methods for skin sensitisation safety

assessment. Toxicol. In Vitro, 29, 259-270.

Rousset, F., Verda, D., Arrighi, J. F., Peguet-Navarro, J., Cottin, M., 2000. A strategy for the

prediction of skin sensitization: An alternative to animal testing. In: Proceedings of the 3rd World

Congress on Alternatives and Animal Use in the Life Sciences. Progress in the Reduction,

Refinement and Replacement of Animal Experimentation 31:635–642.

Sakaguchi, H., Ryan, C., Ovigne, J.M., Schroeder, K.R., Ashikaga, T., 2010. Predicting skin

sensitization potential and inter-laboratory reproducibility of a human cell line activation test (h-

CLAT) in the European cosmetics association (COLIPA) ring trials. Toxicol. In Vitro 24 (6),

1810–1820.

Smith, C. M. and Hotchkiss, S. A. M., 2001. Allergic Contact Dermatitis: Chemical and

Metabolic Mechanisms. Ed.Taylor and Francis, London, UK.

Smith-Pease, C. K., Basketter,D. A., Patlewicz, G.Y., 2003. Contact allergy: The role of skin

chemistry and metabolism. Clin. Exp. Dermatol 2, 177–183.

Sundström, C., Nilsson, K. (1976). Establishment and characterization of a human histiocytic

lymphoma cell line (U-937). Int. J. Cancer 17, 565-577.

Takenouchi, O., Miyazawa, M., Saito, K., Ashikaga, T., Sakaguchi, H., 2013. Predictive

performance of the human Cell Line Activation Test (h-CLAT) for lipophilic chemicals with high

octanol-water partition coefficients. J Toxicol Sci. 38,599-609.

United Nations UN (2013). Globally Harmonized System of Classification and Labelling of

Chemicals 3 (GHS). Fifth revised edition. New York & Geneva: United Nations Publications.

ISBN: 4 978-92-1-117006-1. Available at: 5

[http://www.unece.org/trans/danger/publi/ghs/ghs_rev05/05files_e.html].

Attachment 1: Complete data set from both validations studies using the simplified prediction model

2013 2014 2013 2014inter-

lab

overall

(175)Run 1 Run 2 Run 3 Run 4

Bioassay NC P P - POSITIVE 13 3


Bioassay P P - - POSITIVE 14 3

CiToxLab NC P P - POSITIVE 18 3

CiToxLab P P - - POSITIVE 17 1

CiToxLab P P - - POSITIVE NA 6

L'Oréal P P - - POSITIVE NA 3

L'Oréal NC P P - POSITIVE 13 3


Wil Research NC P P - POSITIVE 12 1





Bioassay NC P P - POSITIVE 153 NA


CiToxLab P P - - POSITIVE NA NA

CiToxLab P P - - POSITIVE 193 NA


L'Oréal NC P P - POSITIVE NA NA

L'Oréal NC P P - POSITIVE 121 NA

Wil Research P P - - POSITIVE NA 67




Bioassay NC P P - POSITIVE NA NA

Bioassay P P - - POSITIVE NA NA



CiToxLab NC P P - POSITIVE 52 NA

L'Oréal P P - - POSITIVE 39 14

L'Oréal NC P P - POSITIVE NA 21


Wil Research P P - - POSITIVE 51 15



3-Dimethylaminopropylamine

#03 #03 √ #33 107-15-3 Ethylene diamine

#9 615-50-9 Toluene diamine sulphate

#02 #02 √ #22 109-55-7

Individual Run conclusion

U-SENS classification Mean CV70 Mean CD86

#01 #01 √

WLR BLR PC

CASRN Name Laboratories

57


2013 2014 2013 2014inter-

lab

overall


Bioassay P P - - POSITIVE NA 12






L'Oréal P P - - POSITIVE NA NA




Wil Research P P - - POSITIVE NA NA


Bioassay N P P - POSITIVE NA NA

Bioassay N P P - POSITIVE NA NA

Bioassay N P P - POSITIVE NA 123






L'Oréal N P P - POSITIVE NA 151

Wil Research NC P P - POSITIVE NA 130




Bioassay NC P P - POSITIVE NA 2


CiToxLab NC P P POSITIVE 8 1







Wil Research P P - - POSITIVE 6 NA




WLR BLR PC


2682-20-4 Methylisothiazolinone (MI)#09 #09 √ #7

108-46-3 Resorcinol

#05 #05 √ #58 80-62-6 Methylmethacrylate

#04 #04 √ #48

58


2013 2014 2013 2014inter-

lab

overall










Bioassay N N - - NEGATIVE NA NA

Bioassay N P N - NEGATIVE NA NA


CiToxLab N N - - NEGATIVE NA NA



L'Oréal N P N - NEGATIVE NA NA

L'Oréal N N - - NEGATIVE NA NA


Wil Research N N - - NEGATIVE NA NA







CiToxLab P N N - NEGATIVE NA NA








Laboratories



WLR BLR PC

CASRN Name

50-21-5 Lactic acid#07 #07 √ #93

104-54-1 Cinnamic alcohol

#06 #06 √ #91 110-54-3 Hexane

#17 √ #40

#16 √ #5 106-50-3 1,4-Phenylenediamine

59


2013 2014 2013 2014inter-

lab

overall





CiToxLab N P N - NEGATIVE NA NA



L'Oréal P N N - NEGATIVE NA NA


L'Oréal NC N N - NEGATIVE NA NA




























WLR BLR PC




81-07-2 Saccharin

#11 #11 √ #167 75-35-4 Vinylidene dichloride

#10 #10 √ #163

#08 #08 √ #94 56-81-5 Glycerol/Glycerin*

60


2013 2014 2013 2014inter-

lab

overall





CiToxLab N P P - POSITIVE NA NA

CiToxLab P N N NEGATIVE NA NA








Bioassay NC N N - NEGATIVE NA NA



CiToxLab P N P - POSITIVE NA NA





















Laboratories



WLR BLR PC

CASRN Name

25322-68-3 Polyethylene glycol#14 #14 √ #174

65-85-0 Benzoic acid

#13 #13 √ #172 3810-74-0 Streptomycin sulfate

#12 #12 √ #168

61


2013 2014 2013 2014inter-

lab

overall





CiToxLab NC P N N NEGATIVE NA NA


CiToxLab NC P P - POSITIVE NA NA

L'Oréal N P N - NEGATIVE NA NA





Wil Research N P N - NEGATIVE NA NA


CiToxLab N P N - NEGATIVE NA NA




CiToxLab NC P P - POSITIVE NA 183





















WLR BLR PC


99-96-7 4-Hydroxybenzoic acid *

#23 √ #164 109-65-9 1-Bromobutane*

#22 √ #162

1330-20-7 Xylene

#21 √ #161 121-57-3 Sulfanilic acid*

#20 √ #88

119-36-8 Methyl salicylate*

#19 √ #72 121-33-5 Vanillin*

#18 √ #71

#15 #15 √ #175 100-51-6 Benzyl alcohol

62


2013 2014 2013 2014inter-

lab

overall








L'Oréal P P - - POSITIVE 1 NA






















Bioassay NC P N P POSITIVE NA NA






Bioassay NC P P - POSITIVE NA 13






Laboratories



WLR BLR PC

CASRN Name

3344-77-2 12-Bromo-1-dodecanol#08 #08 √ #143

141-05-9 Diethyl maleate

#07 #07 √ #35 93-99-2 Phenyl benzoate

#06 #06 √ #21

591-27-5 m-Aminophenol

#04 #04 √ #116 108-45-2 m-Phenylenediamine

#03 #03 √ #127

77-92-9 Citric acid*

#02 #02 √ #11 1166-52-5 Lauryl gallate

#24 √ #173

63


2013 2014 2013 2014inter-

lab

overall


Bioassay P P - - POSITIVE 0 NA






Bioassay P P - - POSITIVE 2 NA






Bioassay NC P P - POSITIVE 3 NA

CiToxLab NC P P - POSITIVE 3 NA





Bioassay P P - - POSITIVE NA NA


















WLR BLR PC




69-72-7 Salicylic acid#01 #01 √ #89

120-51-4 Benzyl benzoate

#014 #014 √ #153 140-67-0 4-Allylanisole

#13 #13 √ #63

35691-65-7 Methyldibromoglutaronitrile

#12 #12 √ #36 137-26-8 Tetramethylthiuram disulfide

#11 #11 √ #17

#10 #10 √ #109 100-11-8 4-Nitrobenzyl bromide

64


2013 2014 2013 2014inter-

lab

overall




L'Oréal N P P - POSITIVE NA NA



Wil Research P N P - POSITIVE NA 62


CiToxLab P N P - POSITIVE NA NA



L'Oréal P N P - POSITIVE NA NA


L'Oréal NC P N N NEGATIVE NA NA





L'Oréal NC P P - POSITIVE NA NA
















* Tested in both studies; WLR: Within-laboratory reproducibility; BLR: Between-laboratory reproducibility; PC: Predictive capacityNC: First run with No Conclusion when CD86 is positive at the highest non-cytotoxic concentration onlyP: run with CD86 positive and/or interference(s) observed;N: run with no CD86 positive or interference observed; NA: Not ApplicableIn red, final conclusion impacted by the revision of the prediction model (initially classified as NEGATIVE)

WLR BLR PC




109-65-9 1-Bromobutane*

#21 #161 121-57-3 Sulfanilic acid*

#20 #164

56-81-5 Glycerol/Glycerin*

#19 #162 99-96-7 4-Hydroxybenzoic acid*

#18 #94

121-33-5 Vanilin*

#17 #173 77-92-9 Citric acid*

#16 #72

108-90-7 Chlorobenzene

#15 #71 119-36-8 Methyl salicylate*

#09 #09 √ #160

#05 #05 √ #165 92-48-8 6-Methylcoumarin

65

Attachment 2 : Database of 175 substances used in the evaluation of the predictive performance of the U-SENS™ assay

N° Substance CAS number

Ingredient class

Toxtree Protein Binding classa

Human potency

cat.b

LLNAc U-SENS Human versus LLNA /

U-SENSf

EC3 (%)

Potency cat.d

CLP cat.

Data sourcee

Vehicle Class EC150 (µg/mL)

CV70 (µg/mL)

1 Tetrachlorosalicylanilide 1154-59-2 Preservatives Acyl Transfer agent 1 0.04 Extreme Cat. 1A 6 DMSO POSITIVE 2 2

2 2,4-Dinitrochlorobenzen DNCB 97-00-7 non cosmetic SNAr 1 0.05 Extreme Cat. 1A 6 DMSO POSITIVE 1 1

3 Diphenylcyclopropenone 886-38-4 non cosmetic Michael Acceptor 1 0.05 Extreme Cat. 1A 3 DMSO POSITIVE 0.2 1.4

4 Potassium dichromate 7778-50-9 non cosmetic No binding 1 0.08 Extreme Cat. 1A 6 RPMI POSITIVE 0.9 0.9

5 1,4-Phenylenediamine 106-50-3 Dyes (Oxidation)

Michael Acceptor 1 0.11 Strong Cat. 1A 3 RPMI POSITIVE 2 21

6 Dimethyl fumarate 624-49-7 non cosmetic Michael Acceptor 1 0,35 Strong Cat. 1A 3 RPMI POSITIVE 1 27

7 Methylisothiazolinone (MI pure) 2682-20-4 Preservatives Michael Acceptor / SN2

1 0.4 Strong Cat. 1A 3 RPMI POSITIVE 1 6

8 Glutaraldehyde (act. 50%) 111-30-8 Preservatives Schiff base formation

2 0.1 Strong Cat. 1A 6 RPMI POSITIVE 83 >200

9 Toluene diamine sulphate 615-50-9 Dyes (Oxidation)

Michael Acceptor 2 0.2 Strong Cat. 1A 3 RPMI POSITIVE 2 12

10 Gold chloride 13453-07-1 non cosmetic No binding 2 0.3 Strong Cat. 1A 3 RPMI POSITIVE 0.1 0.1

11 Lauryl gallate 1166-52-5 Others Michael Acceptor 2 0.3 Strong Cat. 1A 6 DMSO POSITIVE 0.7 0.7

12 Propyl gallate 121-79-9 Fragrances Michael Acceptor 2 0.32 Strong Cat. 1A 9 RPMI POSITIVE 2 33

13 2-Nitro-1,4-phenylenediamine 5307-14-2 Dyes (Direct) Michael Acceptor 2 0.4 Strong Cat. 1A 6 DMSO POSITIVE 5 115

14 2-aminophenol 95-55-6 Dyes (Oxidation)

Michael Acceptor 2 0.4 Strong Cat. 1A 9 DMSO POSITIVE 0.1 8

15 Formaldehyde (act. 37%) 50-00-0 Preservatives Schiff base formation

2 0.4 Strong Cat. 1A 3 DMSO POSITIVE 6 6

16 Methyl heptine carbonate 111-12-6 Fragrances Michael Acceptor 2 0.5 Strong Cat. 1A 7 DMSO POSITIVE 39 70

17 Methyldibromo glutaronitrile 35691-65-7 Preservatives Michael Acceptor / SN2


18 Isoeugenol 97-54-1 Fragrances Michael Acceptor 2 1.2 Moderate Cat. 1A 6 DMSO POSITIVE 45 115

19 Glyoxal (act. 40%) 107-22-2 Preservatives No binding 2 1.4 Moderate Cat. 1A 6 RPMI POSITIVE 33 93

20 Cinnamic aldehyde 104-55-2 Fragrances Michael Acceptor 2 2 Moderate Cat. 1B 3 DMSO POSITIVE 1 8

66



Ingredient class


Human potency

cat.b


U-SENSf

EC3 (%)

Potency cat.d

CLP cat.

Data sourcee


CV70 (µg/mL)

21 Diethyl maleate 141-05-9 non cosmetic Michael Acceptor 2 2.1 Moderate Cat. 1B 3 DMSO POSITIVE 7 30

22 3-Dimethylaminopropylamine 109-55-7 non cosmetic Schiff base formation

2 2.2 Moderate Cat. 1B 6 RPMI POSITIVE 103 >200

23 1,2-Benzisothiazolin-3-one 2634-33-5 Preservatives Acyl Transfer agent / SN2

2 2.3 Moderate Cat. 1B 6 DMSO POSITIVE 0.4 3

24 Thioglycerol 96-27-5 Others No binding 2 3.6 Moderate Cat. 1B 3 RPMI POSITIVE 88 >200

25 Lyral 31906-04-4 Fragrances Schiff base formation

2 17.1 Weak Cat. 1B 6 DMSO POSITIVE 6 24

26 Metol 55-55-0 Dyes (Oxidation)

Michael Acceptor 3 0.8 Strong Cat. 1A 6 RPMI POSITIVE 0.3 3

27 1,4-Dihydroquinone 123-31-9 Actives Michael Acceptor 3 0.11 Strong Cat. 1A 6 RPMI POSITIVE 1 6

28 Chlorpromazine 50-53-3 non cosmetic Schiff base formation


29 Benzoyl peroxide 94-36-0 Actives Acyl Transfer agent 3 0.3 Strong Cat. 1A 3 DMSO POSITIVE 27 33

30 Hydroxyethyl acrylate 868-77-9 Others Michael Acceptor 3 1.4 Moderate Cat. 1A 3 RPMI POSITIVE 40 >200

31 Bisphenol A-diglycidyl ether 1675-54-3 non cosmetic SN2 3 1.5 Moderate Cat. 1A 6 DMSO POSITIVE 10 26

32 2-Mercaptobenzothiazole 149-30-4 non cosmetic Acyl Transfer agent 3 1.7 Moderate Cat. 1A 6 DMSO POSITIVE 40 80

33 Ethylene diamine 107-15-3 Others Schiff base formation

3 2.2 Moderate Cat. 1B 6 RPMI POSITIVE 16 58

34 Farnesol 4602-84-0 Fragrances Schiff base formation

3 4.8 Moderate Cat. 1B 3 DMSO POSITIVE 8 34

35 Phenyl benzoate 93-99-2 Preservatives Acyl Transfer agent 3 5.2 Moderate Cat. 1B 3 DMSO POSITIVE 101 >200

36 Tetramethylthiuramdisulfide 137-26-8 non cosmetic No binding 3 6 Moderate Cat. 1B 3 DMSO POSITIVE 0.1 3

37 Citral 5392-40-5 Fragrances Schiff base formation

3 13 Weak Cat. 1B 6 DMSO POSITIVE 4 13

38 Eugenol 97-53-0 Fragrances Michael Acceptor 3 13 Weak Cat. 1B 6 DMSO POSITIVE 29 142

39 Abietic acid 514-10-3 non cosmetic No binding 3 15 Weak Cat. 1B 6 DMSO POSITIVE 37 66

40 Cinnamic alcohol 104-54-1 Fragrances Michael Acceptor 3 21 Weak Cat. 1B 6 DMSO POSITIVE 21 110

41 Imidazolidinyl urea 39236-46-9 Preservatives Acyl Transfer agent 3 24 Weak Cat. 1B 6 RPMI POSITIVE 11 28

42 Coumarin 91-64-5 Fragrances Michael Acceptor 3 30 Weak Cat. 1B 3 DMSO POSITIVE 152 >200

67



Ingredient class


Human potency

cat.b


U-SENSf

EC3 (%)

Potency cat.d

CLP cat.

Data sourcee


CV70 (µg/mL)

43 Butyl glycidyl ether 2426-08-6 non cosmetic SN2 3 31 Weak Cat. 1B 6 RPMI POSITIVE 149 >200

44 Chlorhexidine gluconate 55-56-1 Preservatives Acyl Transfer agent 4 na na na na DMSO POSITIVE 4 4

45 Bronopol 52-51-7 Preservatives No binding 4 na na na na RPMI POSITIVE 2 6

46 Hexyl salicylate 6259-76-3 Fragrances No binding 4 0.18 Strong Cat. 1A 7 DMSO POSITIVE 27 27

47 Iodopropynyl butylcarbamate 55406-53-6 Preservatives Acyl Transfer agent 4 0.87 Strong Cat. 1A 7 DMSO POSITIVE 2 4

48 Resorcinol 108-46-3 Dyes (Oxidation)

Michael Acceptor 4 5.5 Moderate Cat. 1B 7 RPMI POSITIVE 5 173

49 Amyl cinnamic aldehyde 122-40-7 Fragrances Michael Acceptor 4 11 Weak Cat. 1B 3 DMSO POSITIVE 13 27

50 Lillial 80-54-6 Fragrances Schiff base formation


51 Hydroxycitronellal 107-75-5 Fragrances Schiff base formation


52 Benzocaine 94-09-7 Preservatives No binding 4 22 Weak Cat. 1B 3 DMSO POSITIVE 103 >200

53 Amylcinnamyl alcohol 101-85-9 Fragrances Michael Acceptor 4 25 Weak Cat. 1B 3 DMSO POSITIVE 15 40

54 Geraniol 106-24-1 Fragrances Schiff base formation

4 26 Weak Cat. 1B 6 RPMI POSITIVE 54 134

55 Linalool 78-70-6 Fragrances No binding 4 30 Weak Cat. 1B 6 DMSO POSITIVE 41 >200

56 Ethyleneglycol dimethacrylate 97-90-5 non cosmetic Michael Acceptor 4 35 Weak Cat. 1B 3 DMSO POSITIVE 81 >200

57 Aniline 62-53-3 Dyes (Oxidation)

No binding 4 89 Weak Cat. 1B 6 RPMI POSITIVE 63 >200

58 Methylmethacrylate 80-62-6 non cosmetic Michael Acceptor 4 90 Weak Cat. 1B 7 DMSO POSITIVE 157 >200

59 Anethole 104-46-1 Fragrances Michael Acceptor 5 2.3 Moderate Cat. 1B 6 DMSO POSITIVE >200 >200

60 Benzyl salicylate 118-58-1 Fragrances Acyl Transfer agent 5 2.9 Moderate Cat. 1B 7 DMSO POSITIVE 66 66

61 Anisyl alcohol 105-13-5 Fragrances Michael Acceptor / SN2

5 5.9 Moderate Cat. 1B 7 DMSO NEGATIVE >200 >200 M

62 Hexyl cinnamic aldehyde 101-86-0 Fragrances Michael Acceptor 5 8 Moderate Cat. 1B 3 DMSO POSITIVE 5 22

63 Benzyl benzoate 120-51-4 Fragrances Acyl Transfer agent 5 17 Weak Cat. 1B 6 DMSO POSITIVE >200 >200

64 Pentachlorophenol 87-86-5 non cosmetic SNAr 5 20 Weak Cat. 1B 6 DMSO POSITIVE 21 21

68



Ingredient class


Human potency

cat.b


U-SENSf

EC3 (%)

Potency cat.d

CLP cat.

Data sourcee


CV70 (µg/mL)

65 Benzaldehyde 100-52-7 Fragrances Schiff base formation


66 Diethanolamine 111-42-2 Others No binding 5 40 Weak Cat. 1B 3 RPMI POSITIVE 27 >200

67 Isopropyl myristate 110-27-0 Others No binding 5 44 Weak Cat. 1B 6 DMSO NEGATIVE >200 >200 M

68 Citronellol 106-22-9 Fragrances No binding 5 43.5 Weak Cat. 1B 7 DMSO POSITIVE 25 >200

69 Limonene (not oxidised) 138-86-3 Fragrances No binding 5 69 Weak Cat. 1B 3 DMSO POSITIVE 26 43

70 Pyridine 110-86-1 non cosmetic No binding 5 72 Weak Cat. 1B 6 RPMI NEGATIVE >200 >200 M

71 Methyl salicylate 119-36-8 Preservatives No binding 5 NC NS no cat. 6 DMSO NEGATIVE >200 >200 L&M

72 Vanillin 121-33-5 Fragrances Schiff Base Formation / Michael Acceptor

5 NC NS no cat. 6 DMSO POSITIVE 50 >200 L

73 4-Aminobenzoic acid 150-13-0 UV filter No binding 5 NC NS no cat. 4 DMSO NEGATIVE >200 >200 L&M

74 Propyl paraben 94-13-3 Preservatives No binding 5 NC NS no cat. 9 RPMI POSITIVE 24 122 L

75 Benzalkonium chloride 8001-54-5 Preservatives NA 5 NC NS no cat. 3 RPMI POSITIVE 0.1 1 L

76 Hydrocortisone 50-23-7 Actives Schiff base formation

5 NC NS no cat. 3 DMSO NEGATIVE >200 >200 L&M

77 Propylene glycol 57-55-6 Others No binding 5 NC NS no cat. 6 RPMI NEGATIVE >200 >200 L&M

78 Isopropanol 67-63-0 Others No binding 5 NC NS no cat. 6 RPMI NEGATIVE >200 >200 L&M

79 Phenoxyethanol 122-99-6 Preservatives No binding 5 NC NS no cat. 3 DMSO POSITIVE 176 >200 L

80 Sorbic acid 110-44-1 Preservatives Michael Acceptor 5 na na na na DMSO POSITIVE 115 >200

81 Triclosan 3380-34-5 Preservatives No binding 5 na na na na DMSO POSITIVE 4 5

82 Triethanolamine 102-71-6 Actives No binding 5 na na na na RPMI POSITIVE 189 >200

83 Butylene glycol 107-88-0 Others No binding 5 na na na na RPMI NEGATIVE >200 >200 M

84 Cetrimide 57-09-0 non cosmetic No binding 5 na na na na RPMI POSITIVE 0.8 0.8

85 Tocopherol 59-02-9 Others No binding 6 7.4 Moderate Cat. 1B 3 RPMI NEGATIVE >200 >200 L

86 Sodium lauryl sulfate 151-21-3 Surfactants SN2 6 14 Weak Cat. 1B 6 RPMI POSITIVE 55 76 L&M

87 DMSO 67-68-5 non cosmetic No binding 6 72 Weak Cat. 1B 6 RPMI NEGATIVE >200 >200 L

88 Xylene 1330-20-7 non cosmetic No binding 6 96 Weak Cat. 1B 5 DMSO NEGATIVE >200 >200 L

69



Ingredient class


Human potency

cat.b


U-SENSf

EC3 (%)

Potency cat.d

CLP cat.

Data sourcee


CV70 (µg/mL)

89 Salicylic acid 69-72-7 Preservatives No binding 6 NC NS no cat. 6 DMSO NEGATIVE >200 >200

90 Octanoic acid 124-07-2 Surfactants No binding 6 NC NS no cat. 6 RPMI POSITIVE 70 >200 M

91 Hexane 110-54-3 non cosmetic No binding 6 NC NS no cat. 6 RPMI NEGATIVE >200 >200

92 Diethyl phthalate 84-66-2 Fragrances No binding 6 NC NS no cat. 6 DMSO POSITIVE 121 >200 M

93 Lactic acid 50-21-5 Actives No binding 6 NC NS no cat. 6 RPMI NEGATIVE >200 >200

94 Glycerol/Glycerin 56-81-5 Actives No binding 6 NC NS no cat. 6 RPMI NEGATIVE >200 >200

95 1-Butanol 71-36-3 Others No binding 6 NC NS no cat. 6 RPMI NEGATIVE >200 >200

96 Tween 80 9005-65-6 Surfactants NA 6 NC NS no cat. 3 RPMI POSITIVE 9 200 M

97 Phenol 108-95-2 Preservatives No binding 6 NC NS no cat. 3 DMSO POSITIVE 22 102 M

98 Dextran 3371-50-4 non cosmetic Schiff base formation

6 NC NS no cat. 3 RPMI NEGATIVE >200 >200

99 Diethyl toluamide 94271-03-1 non cosmetic No binding 6 NC NS no cat. 3 DMSO POSITIVE 53 >200 M

100 Sorbitol 50-70-4 Others No binding 6 na na na na RPMI NEGATIVE >200 >200

101 Glucose 50-99-7 Others No binding 6 na na na na RPMI NEGATIVE >200 >200

102 2,4-Dinitrofluorobenzene 70-34-8 non cosmetic SNAr na 0.032 Extreme Cat. 1A 13 RPMI POSITIVE 1 4 -

103 Oxazolone 15646-46-5 non cosmetic Acyl Transfer agent na 0.003 Extreme Cat. 1A 6 DMSO POSITIVE 145 >200 -

104 MCI/MI (act. 1.5%) 55965-84-9 Preservatives Michael Acceptor / SN2

na 0.005 Extreme Cat. 1A 12 RPMI POSITIVE 11 34 -

105 7,12-Dimethylbenz[α]anthracene 57-97-6 non cosmetic SN2 na 0.006 Extreme Cat. 1A 6 RPMI POSITIVE 47 >200 -

106 p-Benzoquinone 106-51-4 Dyes (Direct) Michael Acceptor na 0.01 Extreme Cat. 1A 6 RPMI POSITIVE 2 15 -

107 3-Methylcatechol 488-17-5 Fragrances Michael Acceptor na 0.02 Extreme Cat. 1A 14 RPMI POSITIVE 0.3 4 -

108 Bandrowski's base 20048-27-5 Dyes (Direct) No binding na 0.04 Extreme Cat. 1A 7 DMSO POSITIVE 1 3 -

109 4-Nitrobenzyl bromide 100-11-8 non cosmetic SN2 na 0.05 Extreme Cat. 1A 6 DMSO POSITIVE 0.4 0.4 -

110 Methylnitrosourea 684-93-5 non cosmetic SN2 na 0.05 Extreme Cat. 1A 6 RPMI POSITIVE 13 >200 -

111 Cyanuric chloride 108-77-0 non cosmetic SNAr na 0.09 Extreme Cat. 1A 6 RPMI POSITIVE 15 68 -

112 p-aminophenol 123-30-8 Dyes (Oxidation)

Michael Acceptor na - Strong Cat. 1A 10 RPMI POSITIVE 2 6 -

70



Ingredient class


Human potency

cat.b


U-SENSf

EC3 (%)

Potency cat.d

CLP cat.

Data sourcee


CV70 (µg/mL)

113 Phthalic anhydride 85-44-9 non cosmetic Acyl Transfer agent na 0.16 Strong Cat. 1A 1 DMSO NEGATIVE >200 >200 D

114 Benzyl bromide 100-39-0 non cosmetic SN2 na 0.2 Strong Cat. 1A 6 DMSO POSITIVE 8 15 -

115 2,4,6-Trinitrobenzenesulfonic acid 2508-19-2 non cosmetic No binding na 0.36 Strong Cat. 1A 13 RPMI POSITIVE 10 >200 -

116 3-Phenylenediamine 108-45-2 Dyes (Oxidation)

Michael Acceptor na 0.49 Strong Cat. 1A 6 RPMI POSITIVE 4 137 -

117 CD3 25646-71-3 non cosmetic Michael Acceptor na 0.6 Strong Cat. 1A 6 RPMI POSITIVE 1 4 -

118 Squaric acid diethyl ester 5231-87-8 non cosmetic Schiff base formation

na 0.9 Strong Cat. 1A 10 DMSO POSITIVE 32 71 -

119 1-Phenyl-1,2-propanedione 579-07-7 Others Schiff base formation

na 1.3 Moderate Cat. 1A 6 DMSO POSITIVE 35 77 -

120 1-Naphthol 90-15-3 Dyes (Oxidation)

Michael Acceptor na 1.3 Moderate Cat. 1A 6 DMSO POSITIVE 3 31 -

121 2-Hydroxyethyl acrylate 818-61-1 non cosmetic Michael Acceptor na 1.4 Moderate Cat. 1A 6 RPMI POSITIVE 2 11 -

122 Nonanoyl chloride 764-85-2 Surfactants Acyl Transfer agent na 1.8 Moderate Cat. 1A 6 DMSO POSITIVE 22 46 -

123 N,N-bis(2-hydroxyethyl)-p-phenylenediamine sulfate

54381-16-7 Dyes (Oxidation)

Michael Acceptor na 1.04 Moderate Cat. 1A 13 RPMI POSITIVE 8 29 -

124 Methyl-2-nonynoate 111-80-8 Fragrances Michael Acceptor na 2.5 Moderate Cat. 1B 6 DMSO POSITIVE 18 105 -

125 3,3,5-trimethylhexanoyl chloride 36727-29-4 non cosmetic Acyl Transfer agent na 2.7 Moderate Cat. 1B 6 DMSO POSITIVE 17 48 -

126 Phenylacetaldehyde 122-78-1 Fragrances Schiff base formation

na 3 Moderate Cat. 1B 6 DMSO POSITIVE 7 17 -

127 3-Aminophenol 591-27-5 Dyes (Oxidation)

Michael Acceptor na 3.2 Moderate Cat. 1B 9 DMSO POSITIVE 11 128 -

128 diethyl sulfate 64-67-5 non cosmetic SN2 na 3.3 Moderate Cat. 1B 6 RPMI POSITIVE 22 >200 -

129 Benzylideneacetone 122-57-6 Fragrances Michael Acceptor na 3.7 Moderate Cat. 1B 6 RPMI POSITIVE 3 7 -

130 3-Propylidenephthalide 17369-59-4 Fragrances Acyl Transfer agent na 3.7 Moderate Cat. 1B 6 DMSO POSITIVE 29 >200 -

131 Squaric acid 2892-51-5 non cosmetic Schiff base formation

na 4.3 Moderate Cat. 1B 14 RPMI POSITIVE 63 >200 -

132 a-Methyl cinnamic aldehyde 101-39-3 Fragrances Michael Acceptor na 4.5 Moderate Cat. 1B 6 DMSO POSITIVE 9 >200 -

133 Nickel sulfate 10101-97-0 Others No binding na 4.8 Moderate Cat. 1B 11 RPMI POSITIVE 16 55 -

134 trans-2-Hexenal 6728-26-3 Fragrances Michael Acceptor na 5.5 Moderate Cat. 1B 6 RPMI POSITIVE 4 51 -

71



Ingredient class


Human potency

cat.b


U-SENSf

EC3 (%)

Potency cat.d

CLP cat.

Data sourcee


CV70 (µg/mL)

135 3,4-Dihydrocoumarin 119-84-6 Fragrances Acyl Transfer agent na 5.6 Moderate Cat. 1B 6 DMSO NEGATIVE >200 >200 D

136 2-Methoxy-4-methyl-phenol 93-51-6 Fragrances Michael Acceptor na 5.8 Moderate Cat. 1B 6 DMSO POSITIVE 13 159 -

137 Diethylenetriamine 111-40-0 Others Schiff base formation

na 5.8 Moderate Cat. 1B 6 RPMI NEGATIVE >200 >200 D

138 1-Bromoeicosane 4276-49-7 non cosmetic SN2 na 6.1 Moderate Cat. 1B 6 RPMI NEGATIVE >200 >200 D

139 2-Phenylpropionaldehyde 93-53-8 Fragrances Schiff base formation

na 6.3 Moderate Cat. 1B 6 DMSO POSITIVE 4 12 -

140 4-Chloroaniline 106-47-8 non cosmetic No binding na 6.5 Moderate Cat. 1B 2 DMSO POSITIVE 1 182 -

141 Dihydroeugenol 2785-87-7 Fragrances Michael Acceptor / SN2


142 Undec-10-enal 112-45-8 Fragrances Schiff base formation

na 6.8 Moderate Cat. 1B 6 RPMI POSITIVE 9 29 -

143 12-Bromo-1-dodecanol 3344-77-2 non cosmetic SN2 na 6.9 Moderate Cat. 1B 6 DMSO POSITIVE 9 28 -

144 Safranal 116-26-7 Fragrances Schiff Base Formation / Michael Acceptor


145 Methyl methanesulphonate 66-27-3 non cosmetic SN2 na 8.1 Moderate Cat. 1B 6 RPMI POSITIVE 2 33 -

146 Tween 21 9005-64-5 Surfactants NA na - Weak Cat. 1B 10 RPMI POSITIVE 68 >200 -

147 Farnesal 19317-11-4 Fragrances Schiff base formation

na 12 Weak Cat. 1B 6 DMSO POSITIVE 6 6 -

148 1-Bromohexane 111-25-1 non cosmetic SN2 na 10 Weak Cat. 1B 6 DMSO POSITIVE >200 183 -

149 2-Ethylhexyl acrylate 103-11-7 non cosmetic Michael Acceptor na 10 Weak Cat. 1B 7 DMSO POSITIVE 15 200 -

150 2,3-Butanedion 431-03-8 Fragrances Schiff base formation

na 11 Weak Cat. 1B 6 RPMI POSITIVE 11 103 -

151 Oxalic acid 144-62-7 Others No binding na 15 Weak Cat. 1B 6 DMSO NEGATIVE >200 >200 D

152 4-Allylanisole 140-67-0 Fragrances Michael Acceptor na 18 Weak Cat. 1B 6 DMSO POSITIVE 98 >200 -

153 Benzyl cinnamate 103-41-3 Fragrances Michael Acceptor / SN2

na 18.4 Weak Cat. 1B 7 DMSO POSITIVE 177 >200 -

154 4,4,4-Trifluro-1-phenylbutane-1,3-dione

326-06-7 non cosmetic Schiff base formation


155 alpha-iso-Methylionone 127-51-5 Fragrances Michael Acceptor / SN2

na 21.8 Weak Cat. 1B 7 DMSO POSITIVE 22 36 -

72



Ingredient class


Human potency

cat.b


U-SENSf

EC3 (%)

Potency cat.d

CLP cat.

Data sourcee


CV70 (µg/mL)

156 Cyclamen aldehyde 103-95-7 Fragrances Schiff base formation


157 Undecylenic acid 112-38-9 Preservatives No binding na 25 Weak Cat. 1B 10 DMSO POSITIVE 18 75 -

158 R(+)-Limonene 5989-27-5 Fragrances No binding na 69 Weak Cat. 1B 6 RPMI POSITIVE 30 >200 -

159 Tartaric acid 87-69-4 Actives No binding na NC NS no cat. 15 RPMI NEGATIVE >200 >200 -

160 Chlorobenzene 108-90-7 non cosmetic No binding na NC NS no cat. 6 DMSO NEGATIVE >200 >200 -

161 Sulfanilic acid 121-57-3 non cosmetic No binding na NC NS no cat. 6 RPMI NEGATIVE >200 >200 -

162 4-Hydroxybenzoic acid 99-96-7 Preservatives No binding na NC NS no cat. 6 DMSO NEGATIVE >200 >200 -

163 Saccharin 81-07-2 non cosmetic Acyl Transfer agent na NC NS no cat. 6 RPMI NEGATIVE >200 >200 -

164 1-Bromobutane 109-65-9 non cosmetic SN2 na NC NS no cat. 6 DMSO NEGATIVE >200 >200 -

165 6-Methyl coumarin 92-48-8 Fragrances Michael Acceptor na NC NS no cat. 6 DMSO POSITIVE 94 187 D

166 Ethyl benzoylacetate 94-02-0 Fragrances No binding na NC NS no cat. 6 DMSO NEGATIVE >200 >200 -

167 Vinylidene dichloride 75-35-4 non cosmetic Michael Acceptor na NC NS no cat. 6 DMSO NEGATIVE >200 >200 -

168 Benzoic acid 65-85-0 Preservatives No binding na NC NS no cat. 9 RPMI NEGATIVE >200 >200 -

169 Ethyl vanillin 121-32-4 Fragrances Schiff base formation

na NC NS no cat. 6 DMSO POSITIVE 66 66 D

170 Sulfanilamide 63-74-1 non cosmetic No binding na NC NS no cat. 6 RPMI NEGATIVE >200 >200 -

171 Kanamycin (sulfate) 25389-94-0 non cosmetic No binding na NC NS no cat. 6 RPMI NEGATIVE >200 >200 -

172 Streptomycin sulfate 3810-74-0 non cosmetic Schiff base formation

na NC NS no cat. 6 RPMI NEGATIVE >200 >200 -

173 Citric acid 77-92-9 Preservatives No binding na NC NS no cat. 10 RPMI NEGATIVE >200 >200 -

174 Polyethylene glycol 25322-68-3 Others No binding na NC NS no cat. 10 RPMI POSITIVE 73 >200 D

175 Benzyl alcohol 100-51-6 Preservatives No binding na NC NS no cat. 9 DMSO POSITIVE 176 >200 D

73


a SN2: substitution nucleophilic bi-molecular; SNAr: nucleophilic aromatic substitution (Patlewicz et al., 2008) b Human Skin Sensitizing Potency category (Basketter et al., 2014) ; na: not available c LLNA (TG429 and EU test method B.42 (OECD, 2010a; UN 2011)) ; na: not available d LLNA potency category based on the EC3 value as proposed by Kimber et al. (2003). e Data sources : 1: Arts et al. (2008); 2: Basketter et al. (2003); 3: Basketter et al. (2014); 4: Dearman et al. (1999); 5: Estrada et al. (2003); 6: Gerberick et al.

(2005); 7: Kern et al. (2010); 8: Kimber et al. (1995); 9: Natsch et al. (2009); 10: proprietary data; 11: Ryan et al. (2002); 12: Warbrick et al. (1999); 13:

Roberts et al. (2011); 14: Natsch et al. (2013); 15. ICCVAM, 2008; 16: SCCP/0983/06 opinion on COLIPA N° A50; ; 17: REACh

(http://apps.echa.europa.eu/registered/data/dossiers/DISS-9eb16d5d-b83e-2831-e044-00144f67d031/AGGR-a4e0d928-aa10-4059-83b9-

b93764122017_DISS-9eb16d5d-b83e-2831-e044-00144f67d031.html#AGGR-a4e0d928-aa10-4059-83b9-b93764122017). f Human versus LLNA and/or U-SENS™ S/NS classifications: : concordant hazard classifications between human, LLNA and U-SENS™; L: discordant hazard

classifications between LLNA and human; M: discordant hazard classifications between U-SENS™ and human; -: concordant hazard classifications between

LLNA and U-SENS™ without any human data available; D: discordant hazard classifications between LLNA and U-SENS™ without any human data available.

74