title: Integrating non-animal test information into an adaptive testing strategy - skin sensitization proof of concept case.
abstract: There is an urgent need to develop data integration and testing strategy frameworks allowing interpretation of results from animal alternative test batteries. To this end, we developed a Bayesian Network Integrated Testing Strategy (BN ITS) with the goal to estimate skin sensitization hazard as a test case of previously developed concepts (Jaworska et al., 2010). The BN ITS combines in silico, in chemico, and in vitro data related to skin penetration, peptide reactivity, and dendritic cell activation, and guides testing strategy by Value of Information (VoI). The approach offers novel insights into testing strategies: there is no one best testing strategy, but the optimal sequence of tests depends on information at hand, and is chemical-specific. Thus, a single generic set of tests as a replacement strategy is unlikely to be most effective. BN ITS offers the possibility of evaluating the impact of generating additional data on the target information uncertainty reduction before testing is commenced.
authors: Procter & Gamble Eurocor, Strombeek-Bever, Belgium. Jaworska.J@pg.com
authors: Joanna
authors: J
authors: Jaworska
authors: Artsiom
authors: A
authors: Harol
authors: Petra S
authors: PS
authors: Kern
authors: G Frank
authors: GF
authors: Gerberick
mesh_terms: D000826:Animal Testing Alternatives / Q000379:methods*; D000818:Animals; D001499:Bayes Theorem; D001682:Biological Availability; D003877:Dermatitis, Contact; D023441:Local Lymph Node Assay; D051379:Mice; D004364:Pharmaceutical Preparations; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018675:Toxicity Tests / Q000379:methods*
chemical_list: D004364:Pharmaceutical Preparations