Abstract
Mapping the uptake of topical drugs and quantifying dermal pharmacokinetics (PK) presents numerous challenges. Though high resolution and high precision methods such as mass spectrometry offer the means to quantify drug concentration in tissue, these tools are complex and often expensive, limiting their use in routine experiments. For the many topical drugs that are naturally fluorescent, tracking fluorescence emission can be a means to gather critical PK parameters. However, skin autofluorescence can often overwhelm drug fluorescence signatures. Here we demonstrate the combination of standard epi-fluorescence imaging with deep learning for the visualization and quantification of fluorescent drugs in human skin. By training a U-Net convolutional neural network on a dataset of annotated images, drug uptake from both high "infinite" dose and daily clinical dose regimens can be measured and quantified. This approach has the potential to simplify routine topical product development in the laboratory.
Highlights
The development of topically applied drug products presents numerous challenges, which include the identification of an optimal active pharmaceutical ingredient (API), the formulation of the API for delivery through the skin barrier, assessment of the percutaneous pharmacokinetics (PK) of the API, its engagement with the target, and assessment of the skin’s pharmacodynamic response [1]
This study explored the use of simple epi-fluorescence microscopy combined with machine learning methods for the visualization and quantification of drug uptake within skin
Epi fluorescence microscopy combined with deep learning was able to successfully recognize and quantify the uptake of two different drugs within biopsied skin samples
Summary
The development of topically applied drug products presents numerous challenges, which include the identification of an optimal active pharmaceutical ingredient (API), the formulation of the API for delivery through the skin barrier, assessment of the percutaneous pharmacokinetics (PK) of the API, its engagement with the target, and assessment of the skin’s pharmacodynamic response [1]. Mass spectrometry imaging (MSI) tools such as Matrix Assisted Laser Desorption Ionization (MALDI), Secondary Ion Mass Spectrometry (SIMS) and Desorption Electrospray Ionization (DESI) offer the ability to quantify drug uptake within biopsy tissue slices at close to cellular resolution [6]. These methods, can be rather costly, making them prohibitive for widespread use and restrictive to larger pharmaceutical ventures. Autoradiography, in particular Microautoradiography (MARG), offers the ability to examine cellular and even subcellular drug uptake, but the use of radiolabels largely restricts the use of this method to preclinical studies [7,8]
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