Skin Sensitisation – Chemical Applicability Domain of the LLNA

Dave Roberts, Anne Marie Api, Terry Schultz

18th November 2015

Basic mechanism of contact allergy

Inflammation

Systemic recirculation of

sensitised T lymphocytes

The period of

time between

first contact and

development of

contact allergy

may be from

weeks to years

SKIN

LYMPH

NODE

1

2

3

Langerhans

cells migrate

to the local

lymph node 4

5

6

Clonal expansion

Apply test chemical to the

ears 1x/day for 3 days.

72 hr later, inject 3H-thymidine

via the tail vein.

Five hours later,

remove draining

auricular lymph

nodes.

Prepare cell

suspensions,

precipitate

with

trichloroacetic

acid and

incubate

overnight.Mix

precipitated

cells with

scintillation

cocktail.

Count on liquid

scintillation

counter to measure3H-TdR

incorporation in

disintegrations

per minute (DPM).

Figure 1: The local lymph node assay method

Epicutaneous treatment on

Wednesday, Thursday and

Friday

3HTdR on Monday morning

Remove lymph

nodes Monday

afternoon

Precipitate high

mol wt material

-scintillation

counting for

incorporated

3HTdR

LLNA protocol

The LLNA “EC3” value

0

2

4

6

0 2 4 6 8 10

Concentration (%)

Sti

mu

lati

on

in

de

x

a

b

c

d

EC3

EC3 is calculated via:

c+[(3-d)/(b-d)] x (a-c)

How good is the LLNA?

The only extensive source of potency data against which new non-animal methods can be tested

But how reliable is it overall?

What, if any, types of chemicals is it unreliable for?

Variability of the LLNA - Standard deviation for logEC3 from multiple testing

Data from Basketter, Gerberick and Kimber, 2007, Contact Dermatitis 57(2), 70-75.

Chemical

name

n EC3,%

ref [2]

Log-

average

mean EC3,%*

SD for

logEC3**

DNCB 13 0.05 0.04 0.17 (2.2)

K2CrO7 3 0.08 0.08 0.22 (2.8)

PPD 10 0.16 0.1 0.18 (2.3)

Hydroquinone 3 0.11 0.14 0.13 (1.8)

Methyldibromoglutaronitrile 3 0.9 1.3 0.15 (2.0)

Isoeugenol 31 1.2 1.4 0.15 (2.0)

Cinnamaldehyde 3 3.0 2.4 0.14 (1.9)

Hexylcinnamaldehyde 15 11 9.5 0.13 (1.8)

Eugenol 4 13 15.0 0.22 (2.8)

Abietic acid 3 15 10.9 0.12 (1.7)

Penicillin G 3 30 20.8 0.14 (1.9)

Hydroxycitronellal 3 33 27.5 0.08 (1.4)

• Log-average mean (also known as

geometric mean) = antilog[(SlogEC3)/n]

**In brackets, factor for 95% confidence limits

on EC3, based on 2 SDs for logEC3

Overall for 94 assays on 12 compounds:

SD = 0.147; factor of 2 for 95% confidence on EC3

How to predict sensitization potency

• Test it in the LLNA

• Test it in in vitro assay(s) simulating LLNA

• Find out about about its chemistry

How to predict sensitization potency

• Test it in the LLNA

• Reduce animal usage by:• Using rLLNA for potency (Roberts 2015)

• DST approach to identify chemicals that don’t need testing for low level use (Safford et al 2015; Roberts et al 2015)

How to predict sensitization potency

• Test it in the LLNA • No need to know any chemistry

• Test it in in vitro assay(s) simulating LLNA• Shouldn’t need to know any chemistry

• Find out about about its chemistry

How to predict sensitization potency

• Find out about about its chemistry:• How does it react (mechanistic domain)?• How reactive is it?

• Rate constant or surrogate• Bioavailability parameter (log P or none)?

• Modeling in cutaneo partition, not penetration

• Apply QMM or read-across to predict EC3• Already do-able for many chemicals

Importance of Chemical Domains

HUMAN POTENCY CLASSES

Human potency class vs logEC3

0

1

2

3

4

5

6

7

-2 -1 0 1 2 3

logEC3

Human potency class

0

1

2

3

4

5

6

7

-2 -1 0 1 2 3

logEC3

Human potency class

Full dataset After removal of outliers

What can we learn from the outliers we’ve removed?

Which are trying to tell us something about the applicability domain?

Which have trivial ( but not necessarily uninteresting) explanations?

What are the outliers saying?

4 casesHydroquinone, Anethole, Resorcinol, Tocopherol…

…indicated overprediction by LLNA for chemicals activated by abiotic oxidation, in agreement with findings for oleic acid and related compounds

1 caseMethyl methacrylate…

…volatility and high polymerisability under LLNA conditions

1 caseAnisyl alcohol…

…overprediction by LLNA for allylic/benzylic/styrylic alcohols?

9 remaining casesOne metal, outside domain, 8 have trivial explanations

Michael Acceptors

• No GP data set suitable for present purpose, but …

• Human NOEL data from Basketter et al 2014 with corresponding EC3 values for 9 compounds

• Log NOEL correlated with logEC3

• y = 1.7357x + 2.5993 , R² = 0.967

Log NOEL = 1.74 log EC3 + 2.60, R² = 0.967

1.5

2

2.5

3

3.5

4

4.5

-0.5 0 0.5 1 1.5

Ethyl acrylate

Carvone

Citral

Log EC3

Log NOEL

Outliers:Ethyl acrylate – polymerization and evaporation under LLNA conditionsCarvone and citral – low reactivity as MA, but pro-hapten alerts

Michael Acceptors. Log NOEL vs log EC3

The SNAr Reaction

X

Y1, Y2... Y1, Y2...

Nu

Y1, Y2...

Nu XProtein

ProteinNuProtein

+ X

Intermediate

Degree of reactivity depends on overall ability of X and Y

groups to stabilise the negative charge in the intermediate

Modelling SNAr Reactivity

Combination of s- values of Y’s and s* of X

Reactivity parameter, for QMM, RP = SYs- + 0.24s*X

(Roberts et al 2011, Chem. Res. Toxicol. 24, 1003−1011)

SNAr - GP Dataset (Landsteiner and Jacobs, 1936)

• 20 SNAr type compounds tested

• 10 sensitisers

• 10 non-sensitisers

• A discriminant function (DF) based on SYs- and s*X separates sensitisers from non-sensitisers (Roberts, 1995)

DF = SYs- + as*X (a in the range of 0.29 to 0.68)

• DF is very similar to RP for the LLNA QMM

RP = SYs- + 0.24s*X

• Use of DF with a =0.29 gives almost as good correlation as RP for LLNA data

LLNA pEC3 vs DF DF = SYs- + 0.29s*X (DF - Derived from 1936 GP Data)

0

1

2

3

4

5

6

2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4

pEC3 = 2.65DF - 5.36 R² = 0.973

pEC3

DF

Conclusion: LLNA and GP agree very well for the SNAr domain

Task 2. Parameter Ranges of the LLNA Dataset

*C16 alkene sultone has logP 5.99 and is positive in the LLNA but no EC3 available**TNSB has logP - 3.53 and fits the SNAr QMM, but not in the dataset

Mechanistic Domain logP Reactivity

MA - 0.21 to 5.00* kcys = 10-3.6 to 107 M-1s-1

HP-SN2 - 1.36 to 7.50

NP-SN2 2.75 to 9.90 Alkyl chloride to

benzylic bromide

SB - 4.26 to 4.65 Ss* 0.24 to 2.64

Acyl - 2.30 to 8.60

SNAr 0.90** to 5.10 kcys = 10-3 to 100.4 M-1s-1

Overall Findings

• The LLNA is highly consistent - biological variability within a factor of 2

• However, impurity issues and unreliable interpretation of dose-response data need to be considered in curation of new databases

• For most chemicals, LLNA correlates well with human potency

• Chemicals that are non-sensitizers but can be autoxidised to sensitizing reaction products are often overpredicted (false +)

Outliers removed

Going from left (low EC3, LLNA overpredicts potency) to right (high EC3, LLNA underpredicts potency)

HPC1, underpredicted

HPC2, underpredicted

HPC2, overpredicted

HPC3, overpredicted

Beryllium sulphate

Lyral

Glutaraldehyde

Hydroquinone

Metal allergens outside domain

More potent impurity in commercial material? Not a domain issue

Variable composition test/exposure material, not a domain issue

Abiotic oxidation to Benzoquinone – domain implications

Outliers removed

Going from left (low EC3, LLNA overpredicts potency) to right (high EC3, LLNA underpredicts potency

HPC3, overpredicted

HPC3, overpredicted

HPC4, overpredicted

HPC4, overpredicted

Chlopromazine

Benzoyl peroxide

Hexyl salicylate

Iodopropynyl butyl carbamate

Synthesis impurities? If so, not a domain issue

More potent impurity in commercial material? Not a domain issue

Anomalous high LLNA potency compared to other salicylates. Impurity? Not a domain issue

LLNA potency consistent with SAR, human classification may need re-examining

Outliers removed

Going from left (low EC3, LLNA overpredicts potency) to right (high EC3, LLNA underpredicts potency

HPC4, underpredicted

HPC4, underpredicted

HPC5, overpredicted

HPC5, overpredicted

Methyl methacrylate

Aniline

Anethole

Benzyl salicylate

Short-lived under LLNA conditions, and volatile. Out of domain based on phys-chemproperties

More potent impurities in commercial materials? Not a domain issue

Autoxidative activation? Domain implications

Similar to hexyl salicylate, not a domain issue

Outliers removed

Going from left (low EC3, LLNA overpredicts potency) to right (high EC3, LLNA underpredicts potency

HPC5, overpredicted

HPC5, overpredicted

HPC5, overpredicted

Anisyl alcohol

Resorcinol

Tocopherol

Not oxidation (anisaldehyde is NS)Activation by conjugation of benzylic/styrylic/allylic alcohols to give SN2 electrophiles may be a domain issue

Autoxidative activation? Domain implications

Likely to contain Tocotrienols, which can undergo autoxidativeactivation? Domain implications

SNAr Domain – Guinea Pig and LLNA Data for DNCB and Its Relations

O2N

NO2

NO2

F

NO2

NO2

Cl

NO2

NO2

Br

NO2

NO2

I

NO2

NO2

SCN

NO2

NO2

SO3

NO2

NO2

Cl

NO2

Cl

Cl

CN

Cl

CN

Cl

Cl

O2N

SO3

NO2

NO2

DNFB DNCB DNBB DNIB DNTB

DNBS DCNBTCPN TNCB TNBS

Cl

LLNA Potency vs RP. Thermodynamic Controlled Reaction for TNCB and TNBS

0

1

2

3

4

5

6

2 2.5 3 3.5 4

pEC3

RP

TNBS

TNCB (+2 others)

pEC3 = 2.81(±0.12)RP - 5 44(±0.36)

n = 10, R2 = 0.987, s = 0.13, F = 594

(Roberts et al. 2014, Chem. Res. Toxicol. 27, 240-246)