Computational modeling of the skin barrier

Fabrication of Chemofluidic Integrated Circuits by Multi-Material Printing

Photolithographic patterning of components and integrated circuits based on active polymers for microfluidics is challenging and not always efficient on a laboratory scale using the traditional mask-based fabrication procedures. Here, we present an alternative manufacturing process based on multi-material 3D printing that can be used to print various active polymers in microfluidic structures that act as microvalves on large-area substrates efficiently in terms of processing time and consumption of active materials with a single machine. Based on the examples of two chemofluidic valve types, hydrogel-based closing valves and PEG-based opening valves, the respective printing procedures, essential influencing variables and special features are discussed, and the components are characterized with regard to their properties and tolerances. The functionality of the concept is demonstrated by a specific chemofluidic chip which automates an analysis procedure typical of clinical chemistry and laboratory medicine. Multi-material 3D printing allows active-material devices to be produced on chip substrates with tolerances comparable to photolithography but is faster and very flexible for small quantities of up to about 50 chips.

A Predictive Self-Organizing Multicellular Computational Model of Infant Skin Permeability to Topically Applied Substances

Computational models of skin permeability are typically based on assumptions of fixed geometry and homogeneity of the whole epidermis or of epidermal strata and are often limited to adult skin. Infant skin differs quantitatively from that of the adult in its structure and its functional properties, including its barrier function to permeation. To address this problem, we developed a self-organizing multicellular epidermis model of barrier formation with realistic cell morphology. By modulating the parameters relating to cell turnover reflecting those in adult or infant epidermis, we were able to generate accordingly two distinct models. Emerging properties of these models reflect the corresponding experimentally measured values of epidermal and stratum corneum thickness. Diffusion of an externally applied substance (e.g., caffeine) was simulated by a molecular exchange between the model agents, defined by the individual cells and their surrounding extracellular space. By adjusting the surface concentration and the intercellular exchange rate, the model can recapitulate experimental permeability data after topical exposure. By applying these parameters to an infant model, we were able to predict the caffeine concentration profile in infant skin, closely matching experimental results. This work paves the way for a better understanding of skin physiology and function during the first years of life.

How Sensitive Are Transdermal Transport Predictions by Microscopic Stratum Corneum Models to Geometric and Transport Parameter Input?

While predictive models of transdermal transport have the potential to reduce human and animal testing, microscopic stratum corneum (SC) model output is highly dependent on idealized SC geometry, transport pathway (transcellular vs. intercellular), and penetrant transport parameters (e.g., compound diffusivity in lipids). Most microscopic models are limited to a simple rectangular brick-and-mortar SC geometry and do not account for variability across delivery sites, hydration levels, and populations. In addition, these models rely on transport parameters obtained from pure theory, parameter fitting to match in vivo experiments, and time-intensive diffusion experiments for each compound. In this work, we develop a microscopic finite element model that allows us to probe model sensitivity to variations in geometry, transport pathway, and hydration level. Given the dearth of experimentally-validated transport data and the wide range in theoretically-predicted transport parameters, we examine the model's response to a variety of transport parameters reported in the literature. Results show that model predictions are strongly dependent on all aforementioned variations, resulting in order-of-magnitude differences in lag times and permeabilities for distinct structure, hydration, and parameter combinations. This work demonstrates that universally predictive models cannot fully succeed without employing experimentally verified transport parameters and individualized SC structures.

Detailed modeling of skin penetration--an overview

In recent years, the combination of computational modeling and experiments has become a useful tool that is proving increasingly powerful for explaining biological complexity. As computational power is increasing, scientists are able to explore ever more complex models in finer detail and to explain very complex real world data. This work provides an overview of one-, two- and three-dimensional diffusion models for penetration into mammalian skin. Besides diffusive transport this includes also binding of substances to skin proteins and metabolism. These models are based on partial differential equations that describe the spatial evolution of the transport process through the biological barrier skin. Furthermore, the work focuses on analytical and numerical techniques for this type of equations such as discretization schemes or homogenization (upscaling) techniques. Finally, the work compares different geometry models with respect to the permeability.