Delivery of drug formulations through the subcutaneous route is a widely used modality for the treatment of several diseases, such as diabetes and autoimmune conditions. Subcutaneous injections are typically used to inject low-viscosity drugs in small doses. However, for new biologics, there is a need to deliver drugs of higher viscosity in large volumes. The response of subcutaneous tissue to such high-volume doses and higher viscosity injections is not well understood. Animal models have several drawbacks such as relevance to humans, lack of predictive power beyond the immediate population studied, cost, and ethical considerations. Therefore, a computational framework that can predict the tissue response to subcutaneous injections would be a valuable tool in the development of new devices. To model subcutaneous drug delivery, one needs to consider: a) the deformation and damage mechanics of skin layers due to needle penetration and b) the coupled fluid flow and deformation of the hypodermis tissue due to drug delivery The deformation of the skin is described by the anisotropic, hyper-elastic, and viscoelastic constitutive laws. The damage mechanics is modelled using appropriate damage criteria and damage evolution laws in the modelling framework. The deformation of the subcutaneous space due to fluid flow is described by the poro-hyperelastic theory. The objective of this review is to provide a comprehensive overview of the methodologies used to model each of the above-mentioned aspects of subcutaneous drug delivery. We also present an overview of the experimental techniques used to obtain various model parameters.
<p>The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic which not only created a situation of dealing with public health emergency but also triggered the financial crisis of international concern. The current situation demands rapid, convenient and reliable diagnosis of the disease to downregulate its spread. Primary method of diagnosis presently being used, such as nucleic acid testing (RT-PCR), CT scans etc. involve time-consuming advanced machinery for imaging/ RNA replication and highly skilled technicians which could be only done in a laboratory set-up. A rapid, simple yet selective naked eye detection methodology that does not require any advanced instrumental techniques is highly desirable. </p> <p>In this study, we report computational results which could form the basis of a simple and rapid strategy for the detection of SARS-Cov-2 using peptide (screened from angiotensin-converting enzyme 2 (ACE2) receptor of host cell) functionalized gold nanoparticles (GNPs). This is based on the preferential binding of viral spike (S) protein to ACE2 receptor situated on the surface of the host cell membrane by which the virus gains access to the host cell. The interaction of peptide coated GNPs with spike protein has been investigated using coarse grained molecular dynamic simulations. The potential of mean force calculation of spike protein confirmed strong binding between peptide and receptor binding domain (RBD) of spike protein. The results presented here demonstrate the potential of this peptide coated GNPs-based system in the development of convenient sensors for the clinical diagnosis. </p>
Accurate in-silico models of human skin are required to obtain the uptake/release of molecules across the skin layers to supplement the in-vivo/in-vitro experiments for faster development/testing of cosmetics and drugs. We aim to develop an in-silico skin permeation model by extending the multiscale modeling framework developed earlier for skin’s top layer to deeper layer and compared the outcomes with in-vitro experimental permeation data of 43 cosmetic-relevant molecules across human skin. In this study, we have extended a multiscale modeling framework, with realistic heterogeneous stratum corneum (SC) comprising of network of permeable lipids and corneocytes, followed by homogeneous viable epidermis and dermis. The diffusion coefficients of molecules in lipid layer were determined using molecular dynamics simulations, whereas the diffusion coefficients in other layers and all the partition coefficients were calculated from correlations reported in literature. These parameters were then used in the macroscopic models to predict the release profiles of drugs through the deeper skin layers. The obtained release profiles were in good agreement with available experimental data for most of the molecules. The reported model could provide insight into cosmetics/drugs skin permeation and act as a time-saving and efficient guiding tool for performing targeted experiments
The human skin provides a physiochemical and biological protective barrier to the body due to the unique structure of its outermost layer the stratum corneum. This layer consists of corneocytes and a multi-lamellar lipid matrix forming a composite, which mainly determines the barrier function of the stratum corneum. A substantiated understanding of this barrier is necessary, as controlled breaching or modulation of the same is also essential for many topical drug delivery and personal care applications. In this study, we have discussed the state-of-the-art of neutron diffraction techniques (using specifically deuterated lipids) for stratum corneum lipid analysis and combined it with the information obtained from molecular dynamics simulations, to understand the structure and barrier function of the stratum corneum. As an example, the effect of ceramide concentration on a lipid lamella system consisting of CER[NP]/CER[AP]/Cholesterol/free fatty acid is studied. This study demonstrates the usefulness of the combined approach of neutron diffraction and molecular dynamics simulation for effective analysis of the skin lipid systems. The optimization of force fields by comparison with experimental data is furthermore an important step in the direction of providing a predictive quality.
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