Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul, Republic of Korea.
KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul, Republic of Korea.
Toxicol In Vitro. 2020 Oct;68:104955. doi: 10.1016/j.tiv.2020.104955. Epub 2020 Jul 31.
Current alternatives to animal testing methods for skin irritation evaluation such as reconstructed human epidermis models are not fully representing physiological response caused by skin irritants. Skin irritation is physiologically induced by the dilation and increased permeability of endothelial cells. Thus, our objectives were to mimic physiological skin irritation using a skin-on-a-chip model and compare predictive capacities with a reconstructed human epidermis model to evaluate its effectiveness. To achieve our goals, the skin-on-a-chip model, consisting of three layers representing the epidermal, dermal and endothelial components, was adapted. Cell viability was measured using the OECD TG 439 protocol for test substance evaluation. The tight junctions of endothelial cells were also observed and measured to assess physiological responses to test substances. These parameters were used to physiologically evaluate cell-to-cell interactions induced by test substances and quantify model accuracy, sensitivity, and specificity. Based on in vivo data, the classification accuracy of twenty test substances using a dual-parameter chip model was 80%, which is higher than other methods. Besides, the chip model was more suitable for simulating human skin irritation. Therefore, it is important to note that the dual-parameter chip model possesses an enhanced predictive capacity and could serve as an alternative to animal testing for skin irritation.
目前，用于皮肤刺激性评价的替代动物试验方法，如重建的人表皮模型，不能完全反映皮肤刺激性物质引起的生理反应。皮肤刺激性是由内皮细胞的扩张和通透性增加引起的生理反应。因此，我们的目标是使用皮肤芯片模型模拟生理皮肤刺激性，并将其预测能力与重建的人表皮模型进行比较，以评估其有效性。为了实现我们的目标，我们对包含表皮、真皮和内皮成分的三层皮肤芯片模型进行了适应性改造。采用 OECD TG 439 试验物质评价协议测量细胞活力。还观察和测量了内皮细胞的紧密连接，以评估对试验物质的生理反应。这些参数用于生理评估试验物质诱导的细胞间相互作用，并量化模型的准确性、灵敏度和特异性。基于体内数据，使用双参数芯片模型对 20 种试验物质的分类准确率为 80%，高于其他方法。此外，芯片模型更适合模拟人体皮肤刺激性。因此，需要注意的是，双参数芯片模型具有增强的预测能力，可以作为动物试验替代方法用于皮肤刺激性评价。
