Application of a Systems Biology Approach to Skin Allergy Risk Assessment

Abstract

We have developed an in silico model of the induction of skin sensitisation, in order to characterise and quantify the contribution of each pathway to the overall biological process. This analysis has been used to guide our research on skin sensitisation and in vitro test development programmes, and provides a theoretical rationale for the interpretation and integration of non-animal predictive data for risk assessment (RA) purposes. The in vivo mouse Local Lymph Node Assay (LLNA) is now in widespread use for the evaluation of skin sensitisation potential and potency. Recent changes in European Union (EU) legislation (i.e. the 7th Amendment to the EU Cosmetics Directive) have made the development of non-animal approaches to provide the data for skin sensitisation RA a key business need. Several in vitro predictive assays have already been developed for the prediction of skin sensitisation. However, these are based on the determination of a small number of pathways within the overall biological process, and our understanding of the relative contribution of these individual pathways to skin sensitisation induction is limited. To address this knowledge gap, a “systems biology” approach has been used to construct a computer-based mathematical model of the induction of skin sensitisation, in collaboration with Entelos, Inc. The biological mechanisms underlying the induction phase of skin sensitisation are represented by nonlinear ordinary differential equations and defined by using information from over 500 published papers. By using the model, we have identified knowledge gaps for future investigative research, and key factors that have a major influence on the induction of skin sensitisation (e.g. TNF-α production in the epidermis). The relative contribution of each of these key pathways has been assessed by determining their contributions to the overall process (e.g. sensitiser-specific T-cell proliferation in the draining lymph node). This information provides a biologically-relevant rationale for the interpretation and potential integration of diverse types of non-animal predictive data. Consequently, the Skin Sensitisation Physiolab® (SSP) platform represents one approach to integration that is likely to prove an invaluable tool for hazard evaluation in a new framework for consumer safety RA.

Animal models in translational medicine: Validation and prediction

“…involving human subjects) should be balanced with the often simplistic design of experimental clinical trials. A more recent approach is in silico modeling or also called quantitative systems pharmacology [38][39][40]. By modeling disease mechanisms, the efficacy of drugs addressing known or novel targets on clinical endpoints and biomarkers is predicted.…”

Emulsification and antioxidation of biosurfactant extracts from Chinese medicinal herbs fermentation in vitro

“…SPATs were performed using the method described in the literature to estimate the safety and sensitivity of skin moisturizers (24,25). Briefly, 30 volunteers participated in this investigation.…”

“…Human cells suffer oxidation damage caused by prolonged and constant exposure to free radicals and ROSs, such as NO (24). However, NO is an unstable free radical that immediately results in the production of NO 2 À when exposed to O 2 in the air.…”

The Challenges Involved in Modeling Toxicity Data In Silico: A Review

“…A substantial research program was initiated by Unilever, to critically evaluate the feasibility of a new conceptual approach for consumer safety risk assessment [351], including a computational model of skin sensitization using system biology [352]. Insights from these modelling exercises led to the focus of subsequent nonanimal test development upon the identified toxicity pathways, namely skin bioavailability [353], protein binding [343] , skin inflammation/Dendritic cell (DC) maturation and T cell proliferation.…”