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Evaluation of Suitable Models for Assessing Skin Metabolism

The skin is often overlooked as a metabolically active organ. Development of therapeutic compounds for topical application can be challenging because absorption rates may be unpredictable and metabolic activity can have unforeseen effects. The presence of metabolising enzymes in the skin is relatively low, especially when compared to the liver, but dermal tissue does express a variety of both phase I (monoxygenases, dehydrogenases, reductases) and phase II enzymes (glutathione, N-acetyl and UDP-glucuronosyl transferases).

Oxidative reactions of drugs or other chemicals play a key role in skin sensitisation, so any compound being developed for dermal application should at least be screened for first-pass metabolism in the skin. The primary issue that arises, however, is the cost of using freshly excised human skin or 3D models. As with hepatic metabolism, skin S9 presents a low cost in vitro alternative to evaluating metabolic activity that provides insight specific to topical applications. The human keratinocyte cell line, HaCaT, also demonstrates metabolic activity, and may be a useful model for studying skin metabolism.

In research presented by Cyprotex at the 2016 Great Lakes Drug Metabolism and Disposition Group, three different models (liver S9, skin S9 and HaCaT cells) were compared for their metabolising capability. Within the study, 10 different substrates were assessed alongside a panel of skin sensitisers known to require metabolic activation. Structural elucidation of any potential metabolites was performed using a Water Xevo G2-S Qtof UPLC-MS/MS platform.

To summarise the results from the study:

  • In general, liver S9 was the most metabolically competent system compared with the skin S9 and HaCaT cells. However, it was interesting to note that HaCaT cells tended to demonstrate greater metabolic capacity over skin S9.
  • Within the skin based models (skin S9 and HaCaT cells), the most sensitive way of analysis was by structural elucidation rather than parent compound disappearance due to the low levels of metabolites formed.
  • For certain compounds, the models tended to show differences in specific metabolic pathways. For example, a reductive metabolite of testosterone was formed in HaCaT cells which was not observed in liver S9, suggesting reductases in skin may play an important detoxification role. Furthermore, aldehyde oxidation was greater in skin S9 than HaCaT cells.
  • Overall, although enzymatic activity appeared limited in skin S9 and HaCaT cells (certainly in comparison with liver S9), these in vitro systems are potentially more relevant models of the metabolic pathways within the skin and may be valuable in the detection of skin sensitisers where metabolic activation is an important mechanism in the initiation of sensitisation.

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