TABLE 2.
In silico QSAR and in vitro models for prediction of sensitization capacity of chemicals.
| Assay | Significant features | Number of compounds | % Prediction of sensitizer | % Prediction of non-sensitizer | Model system | References |
|---|---|---|---|---|---|---|
| In silico | ||||||
| LDA QSAR | 14 parameter model; HOMO-LUMO energy gap; Shannon index; discriminant analysis | 259 | 76.5 | 87.9 | GPMT | [33,35] |
| Neural network QSAR | 14 parameter model; HOMO-LUMO energy gap; Shannon index | 259 | 83.2 | 94.3 | GPMT | [35] |
| SAR | Skin metabolism; electrophilic interactions; molecular structure and reactivity; steric effects | 106 | Qualitative | Qualitative | LLNA | [7] |
| QSAR | 2D or 3D molecular r structure descriptors; topological indices; autocorrelation functions; logical regression | 54 | 72 | 93 | LLNA | [49] |
| DEREK, TOPKAT and linear regression | TOPKAT is GPMT based; DEREK and LR model is based on LLNA and GPMT | 178 | 82.9, 73.3, 87.6 | 82.9, 73.3, 87.6 | GPMT | [48] |
| DEREK and linear regression | DEREK and LR model is based on LLNA and GPMT | 178 | 73, 83.2 | 73, 83.2 | LLNA | [48] |
| TIMES-SS | Skin metabolism model; COREPA 3D-QSAR | 634 | 65 | 72 | LLNA, GPMT, BgVV | [37] |
| 4D-QSAR | Two-2-state (sensitizer, non-sensitizer) categorical model; 3D structure of molecules | 196 | 91.5 | 93.9 | LLNA | [91] |
| QSPR | Literature and structural descriptors | 358, 307, 251 | 90, 95, 90 | ND | LLNA, GPMT, BgVV | [59] |
| TOPSMODE-QSAR | Tonnage amount, cluster analysis; prediction of hair dye substances; only 10% of chemicals were pre-tested using LLNA and/or human tests | 229 | Qualitative | Qualitative | LLNA and human tests | [146] |
| Physiolab | Epidermal inflammation; LC maturation markers; Ag specific T cell proliferation | 8 | 100 | 0 | Entelos | |
| DEREK/METEOR | Expert system/metabolic fate predictor | Not disclosed | Not disclosed | Not disclosed | Not disclosed | LHASA limited |
| TOXHUNTER | Genomic, proteomic and metabolomic compound signatures | Not disclosed | Not disclosed | Not disclosed | Not disclosed | Genego |
| BioEpisteme | 2D or 3D molecular descriptors | Not disclosed | Not disclosed | Not disclosed | Not disclosed | Prous Institute |
| In chemico | ||||||
| GSH/Cys/Lys PRA | Six models; different ratios of GSH, Cys, or Lys to chemicals; recursive partitioning model based tree classification to compare LLNA EC3 | 82 | 89 | 89 | LLNA | [58] |
| DPRA | Different ratios of GSH, Cys, or Lys to chemicals; GSH (1:100), Lys (1:50), Cys (1:10), His(1:50) | 38 | 66, 67, 84, 36 | 66, 67, 84, 36 | LLNA | [57] |
| DPRA | Horseradish peroxidase and hydrogen peroxide assay; highly sensitive HPLC tandem mass spectrometry | 32 | 100 | Not Determined | LLNA | [56] |
| Cell based | ||||||
| h-CLAT | 3 rounds of trial for inter-laboratory [5 labs] consistency testing; CD54 and CD86 expression of THP-1 sensitized cells | 27 | 84 | 84 | LLNA | [135] |
| h-CLAT | CD54 and CD86 expression of THP-1 sensitized cells | 100 | 85 | 85 | LLNA | [8] |
| MUSST | CD86 expression of U-937 sensitized cells | 99 | 85 | Not determined | Human data | [1] |
| Keratinosens | Trial for inter-laboratory [5 labs] consistency testing; ARE expression of HaCat sensitized cells | 28 | 91 | 91 | LLNA | [5] |
| ARE luciferase assay | ARE gene expression in AREc32 cells; seeded in 96-well plates at a density of 50,000 cells | 102 | 83 | 83 | LLNA | [108] |
| Integrated testing strategy | ||||||
| Peptide/ARE/TIMES-SS | ARE expression of HaCat sensitized cells, TIMES-SS and peptide reactivity; data integration from multiple systems using regression analysis | 116 | 87.9 | 87.9 | LLNA | [109] |