Quantitative Expression and Inter-Individual Variability of Skin Proteins Involved in Drug and Excipient Metabolism and Transporters Using Targeted and Label Free LC MS/MS Proteomics

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Project summary There are only few genetic alternatives for complex drug products such as the dermal formulations. This is because establishing bioequivalence (BE) for dermatological drug products by conducting comparative clinical endpoint studies can be costly and the studies may not be sufficiently sensitive to detect certain formulation differences (Tsakalozou et al 2021). Establishing in silico models such as physiologically-based pharmacokinetic (PBPK) might help with creation of alternative BE path without heavy reliance on large human clinical studies. However, robustness of such PBPK models and their advantages for answering the regulatory questions relay of sufficiency of system (non-drug-related) information supplied to them. The interaction of drug and formulation ingredients with the constituents of the skin (such as enzymes and proteins) determines the fate of the drug and exertion of its therapeutic effects. These might be highly non-linear and they may vary depending on the condition of the skin (health/disease) as well as location in the body and the attributes of the population (age, ethnicity etc). In this project, the principal enzymes and transporters of the human skin, which are relevant to both active moiety of dermal products as well as the ingredients in the formulation, will be quantified using variety of high resolution tandem mass spectrometry based proteomics measurements. This will be achieved by a collaboration between academia, industry and the FDA and will address the ongoing interest in providing robust in silico models for transdermal drug delivery systems. These data are necessary for populating physiologically based pharmacokinetic (PBPK) models of drug metabolism and disposition (including but not limited to those housed by the Simcyp Simulator) of human skin. The aim is to achieve very broad coverage of relevant proteins and, to this end, a global proteomic approach will be adopted. Proteomic studies are labour intensive and the current published data on skin is limited to few samples. We increase this to over 100 and attempt to stratify based on various attributes. In particular we will address potential ethnic differences focussing initially on Caucasian population and African-Caribbean individuals. All data will be used to populate the Simcyp MechaDema PBPK model in first instance to create an immediate path for practical use by pharmaceutical scientists however the data will remain open for all modellers engaged with PBPK.