Table 1.
OECD Case Study Title (Submitter) |
Purpose | Data Inputs | Reference | Quantitative Evaluation? |
---|---|---|---|---|
An AOP-based ‘2 out of 3’ Integrated Testing Strategy Approach to Skin Hazard Identification (BASF) | Hazard ID | DPRA, hCLAT, KeratinoSens™, U-SENS™ |
Urbisch et al., 2015 | Yes |
Sequential Testing Strategy (STS) for Hazard Identification of Skin Sensitisers (RIVM) | Hazard ID | DPRA, hCLAT, KeratinoSens™, HaCaT gene signature, MultiCASE, CAESAR, DEREK, OECD QSAR toolbox | van der Veen et al., 2014 | No |
A Non-testing Pipeline Approach for Skin Sensitisation (DuPont/G. Patlewicz) | Hazard ID | Existing data, protein binding profile, physicochemical properties, TIMES-SS, expert judgment | Patlewicz et al., 2014 | No |
Stacking Meta-model for Skin Sensitisation Hazard Identification (L’Oréal) | Hazard ID | DPRA, KeratinoSens™, U-SENS™, TIMES-SS, ToxTree, volatility, pH | Del Bufalo et al., in press | No |
Integrated Decision Strategy for Skin Sensitisation Hazard (ICCVAM) | Hazard ID | DPRA, hCLAT, KeratinoSens™, OECD QSAR Toolbox, physicochemical properties | Strickland et al., 2016 | Yes |
Consensus of Classification Trees for Skin Sensitisation Hazard Prediction (EC- JRC) | Hazard ID | TIMES-SS, DRAGON descriptors | Asturiol et al., 2016 | No |
Sensitizer Potency Prediction Based on Key Event 1 + 2: Combination of Kinetic Peptide Reactivity Data and KeratinoSens® Data (Givaudan) | Potency (continuous) | Cor1C420 (kinetic peptide reactivity), KeratinoSens™, TIMES-SS | Natsch et al., 2015 | No |
The Artificial Neural Network Model for Predicting LLNA EC3 (Shiseido) | Potency class/EC3 | DPRA, hCLAT, ARE (or KeratinoSens™) | Hirota et al., 2015 | Yes |
Bayesian Network DIP (BN-ITS-3) for Hazard and Potency Identification of Skin Sensitizers (P&G) | Potency class | DPRA, hCLAT, KeratinoSens™, TIMES-SS, bioavailability (solubility at pH7, log D at pH7, plasma protein binding, fraction ionized) | Jaworska et al., 2015 | Yes |
Sequential Testing Strategy (STS) for Sensitising Potency Classification Based on in Chemico and In Vitro Data (Kao) | Potency class | DPRA, hCLAT | Takenouchi et al., 2015 | Yes |
ITS for Sensitising Potency Classification Based on In Silico, In Chemico, and In Vitro Data (Kao) | Potency class | DPRA, hCLAT, DEREK | Takenouchi et al., 2015 | Yes |
Data Interpretation Procedure for Skin Allergy Risk Assessment (SARA) (Unilever) | Sensitization probability | Bioavailability, skin protein kinetics, ordinary differential equation model | MacKay et al., 2013 | No |