Session 2: Modelling Skin Sensitisation

Quantitative Modelling of the AOP for Skin Sensitisation
Dr Cameron MacKay: Quantitative Modelling of the AOP for Skin Sensitisation

Dr Cameron MacKay


Safety & Environmental Assurance Centre (SEAC) Colworth, Unilever


MacKay C., Cubberley R., Dhadra S., Gellatly N., Pendlington R., Pickles J., Reynolds J., Stark R., and Maxwell G.


Friedmann, P. S., Moss, C., Shuster, S., and Simpson,
J. M. (1983) Quantitative relationships between sensitizing dose of DNCB and reactivity in normal subjects. Clin. Exp. Immunol. 53, 709.



Recently proposed approaches for human health and ecotoxicological risk assessment of chemicals, such as Toxicity Testing in the 21st Century and adverse outcome pathways (AOPs), put strong emphasis on having a deeper understanding of the mechanism of action. Our aim is to directly apply our mechanistic understanding of the skin sensitisation response in assessing the likelihood of sensitisation occurring in humans following a defined chemical exposure (dose per unit area of skin exposed). Central to our approach is mathematical modelling of the underlying biology and evaluation of model output against available clinical data on sensitisation.

We present our current mathematical model of the skin sensitisation response. The model outputs naïve CD8+ T cell activation as a surrogate measure for sensitisation induction in humans. Ordinary differential equations are used to model key events of the AOP: skin penetration (chemical diffusion and partitioning), haptenation of protein nucleophiles and antigen processing and presentation by skin dendritic cells.

Biological parameters are taken from immunological literature with human data used where possible. Chemical-specific parameters are derived from bespoke in vitro experiments and from sensitiser-specific literature. The model has been used to simulate a study (published previously by Friedmann et al. 1983) in which 132 healthy volunteers were exposed to one of five doses of the contact allergen 2,4-dinitrochlorobenzene. 

The results from model simulations and the conclusions reached by Friedmann and co-workers are compared. The implications of the analysis are discussed in the context of defining an appropriate model output representative of sensitisation risk and our ongoing research into sensitiser induced T cell proliferation.