Robertson, Cameron (2019) The scope and limitations of novel NMR techniques to characterise and quantify biologically active compounds in the 'Stratum corneum'. (PhD thesis), Kingston University, .
Abstract
The accurate determination of biologically active compounds in the skin is of considerable importance when evaluating the penetration of skin health products through different layers of the skin. This thesisreportsonthecharacterisation andquantitation ofbiologically active compoundsinsimple model mixtures and complex mixtures which mimic that of a typical skin product, through the use of qNMR, pure shift NMR and DOSY techniques complemented by semi-automated software packages. Characterisation and quantitation conditions were acquired over several heterogeneous samples allowingfor analysisofhowdynamicrangeand complexity of different sample mixtures affect the Limits of Detection (LOD) and Limits of Quantitation (LOQ) of biologically active compounds. NMR is of particular value inthis task, as it is non-destructive, uses a primary ratio method for quantification, and tolerates a wide variety of hydrophilic and hydrophobic components within a given matrix. In this investigation we have attained a trueness level <10%, repeatability values of <1% and brought the limit of quantitation down to 100nM ( ̃limit of baseline range of several key biomarkers in the skin per litre seen in vivo), while commenting on the limitations observed, such as peakoverlap and sensitivity limits. Pure shift optimised sequences allow ustoreducepeakoverlapping, allowing further characterisation of individual compounds and the separation of complex mixtures using NMR. These validated methodologies are then all brought together to develop a new methodology for ex-vivo analysis of skin layers. This analysis allowed for characterisation and quantitation of natural moisturising factors (NMF), biomarkers of hydration and skin health alongside construction of permeation profiles for common topical components in different formulations. Data analysis demonstrates resultscorroboratewithresults seen in previous validated methodologies which havemore complex and time-consumingpreparation and data processingthan the proof of concept study presented here.
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