Transdermal Drug Delivery: Determining Permeation Parameters Using Tape Stripping and Numerical Modeling.

The function of transdermal drug delivery (TDD) systems is complex due to the multiple layers necessary for controlling the rate of drug release and the interaction with the patient's skin. In this work, we study a particular aspect of a TDD system, that is, the parameters that describe the drug permeation through the skin layers. Studies of the diffusion of two compounds were carried out and supported by tape stripping and numerical modeling. The experimental studies are carried out for porcine skin in a Franz diffusion cell and tape stripping is used to quantify the concentration of drug in the stratum corneum. A multi-layered numerical model, based on Fickian diffusion, is used to determine the unknown parameters that define the skin's permeability, such as the partition between layers and the mass transfer coefficients due to the surface barrier. A significant correlation was found between the numerical modeling and experimental results, indicating that the partition and mass transfer effects at the interlayer boundary are accurately represented in the numerical model. We find that numerical modeling is essential to fully describe the diffusion characteristics.

Multi-region finite element modelling of drug release from hydrogel based ophthalmic lenses.

Understanding the way in which drug is released from drug carrying hydrogel based ophthalmic lenses aids in the development of efficient ophthalmic drug delivery. Various solute-polymer interactions affect solute diffusion within hydrogels as well as hydrogel-bulk partitioning. Additionally, surface modifications or coatings may add to resistance of mass transfer across the hydrogel interface. It is necessary to consider both interfacial resistances as well as the appropriate driving force when characterizing interface flux. Such a driving force is induced by a difference in concentration which deviates from equilibrium conditions. We present a Galerkin finite element approach for solute transport in hydrogels which accounts for diffusion within the gel, storage effects due to polymer-solute interaction, as well as partitioning and mass transfer resistance effects at the interface. The approach is formulated using a rotational symmetric model to account for realistic geometry. We show that although the resulting global system is not symmetric in the case of partitioning, it is similar to a symmetric negative semidefinite system. Thus, it has non-positive real eigenvalues and is coercive, ensuring the validity of the finite element formulation as well as the numerical stability of the implicit backward Euler time integration method employed. Two models demonstrating this approach are presented and verified with release experimental data. The first is the release of moxifloxacin from intraocular lenses (IOLs) plasma grafted with different polyacrylates. The second accounts for both loading as well as the release of diclofenac from disc shaped IOL material loaded for varied time periods and temperature.

A numerical framework for drug transport in a multi-layer system with discontinuous interlayer condition.

Discontinuous boundary conditions arise naturally when describing various physical phenomena and numerically modelling such conditions can prove difficult. In the field of pharmaceutical sciences, two such cases are the partitioning of a compound between different materials and a flux rate membrane controlling mass transfer between materials which both result in a discontinuous jump in concentration across adjacent materials. In this study, we introduce a general one-dimensional finite element drug delivery framework, which along with diffusion, reversible binding and dissolution within material layers, incorporates the partitioning and mass transfer conditions between layers of material. We apply the framework to construct models of experiments, which along with experimental data, allow us to infer pharmacokinetic properties of potential material for drug delivery. Understanding such material properties is the key to optimising the therepeutic effect of a targeted drug delivery system.

Simulation of Lake Victoria Circulation Patterns Using the Regional Ocean Modeling System (ROMS).

Lake Victoria provides important ecosystem services including transport, water for domestic and industrial uses and fisheries to about 33 million inhabitants in three East African countries. The lake plays an important role in modulating regional climate. Its thermodynamics and hydrodynamics are also influenced by prevailing climatic and weather conditions on diel, seasonal and annual scales. However, information on water temperature and circulation in the lake is limited in space and time. We use a Regional Oceanographic Model System (ROMS) to simulate these processes from 1st January 2000 to 31st December 2014. The model is based on real bathymetry, river runoff and atmospheric forcing data using the bulk flux algorithm. Simulations show that the water column exhibits annual cycles of thermo-stratification (September-May) and mixing (June-August). Surface water currents take different patterns ranging from a lake-wide northward flow to gyres that vary in size and number. An under flow exists that leads to the formation of upwelling and downwelling regions. Current velocities are highest at the center of the lake and on the western inshore waters indicating enhanced water circulation in those areas. However, there is little exchange of water between the major gulfs (especially Nyanza) and the open lake, a factor that could be responsible for the different water quality reported in those regions. Findings of the present study enhance understanding of the physical processes (temperature and currents) that have an effect on diel, seasonal, and annual variations in stratification, vertical mixing, inshore-offshore exchanges and fluxes of nutrients that ultimately influence the biotic distribution and trophic structure. For instance information on areas/timing of upwelling and vertical mixing obtained from this study will help predict locations/seasons of high primary production and ultimately fisheries productivity in Lake Victoria.

Numerical modelling of transdermal delivery from matrix systems: parametric study and experimental validation with silicone matrices.

A model is presented for transdermal drug delivery from single-layered silicone matrix systems. The work is based on our previous results that, in particular, extend the well-known Higuchi model. Recently, we have introduced a numerical transient model describing matrix systems where the drug dissolution can be non-instantaneous. Furthermore, our model can describe complex interactions within a multi-layered matrix and the matrix to skin boundary. The power of the modelling approach presented here is further illustrated by allowing the possibility of a donor solution. The model is validated by a comparison with experimental data, as well as validating the parameter values against each other, using various configurations with donor solution, silicone matrix and skin. Our results show that the model is a good approximation to real multi-layered delivery systems. The model offers the ability of comparing drug release for ibuprofen and diclofenac, which cannot be analysed by the Higuchi model because the dissolution in the latter case turns out to be limited. The experiments and numerical model outlined in this study could also be adjusted to more general formulations, which enhances the utility of the numerical model as a design tool for the development of drug-loaded matrices for trans-membrane and transdermal delivery.

Numerical modelling and experimental investigation of drug release from layered silicone matrix systems.

Medical devices and polymeric matrix systems that release drugs or other bioactive compounds are of interest for a variety of applications. The release of the drug can be dependent on a number of factors such as the solubility, diffusivity, dissolution rate and distribution of the solid drug in the matrix. Achieving the goal of an optimal release profile can be challenging when relying solely on traditional experimental work. Accurate modelling complementing experimentation is therefore desirable. Numerical modelling is increasingly becoming an integral part of research and development due to the significant advances in computer simulation technology. This work focuses on numerical modelling and investigation of multi-layered silicone matrix systems. A numerical model that can be used to model multi-layered systems was constructed and validated by comparison with experimental data. The model could account for the limited dissolution rate and effect of the drug distribution on the release profiles. Parametric study showed how different factors affect the characteristics of drug release. Multi-layered medical silicone matrices were prepared in special moulds, where the quantity of drug in each layer could be varied, and release was investigated with Franz-diffusion cell setup. Data for long-term release was fitted to the model and the full depletion of the system predicted. The numerical model constructed for this study, whose input parameters are the diffusion, effective dissolution rate and dimensional solubility coefficients, does not require any type of steady-state approximation. These results indicate that numerical model can be used as a design tool for development of controlled release systems such as drug-loaded medical devices.

Test-retest reliability and feature selection in physiological time series classification.

Feature test-retest reliability is proposed as a useful criterion for the selection/exclusion of features in time series classification tasks. Three sets of physiological time series are examined, EEG and ECG recordings together with measurements of neck movement. Comparisons of reliability estimates from test-retest studies with measures of feature importance from classification tasks suggest that low reliability can be used to exclude irrelevant features prior to classifier training. By removing features with low reliability an unnecessary degradation of the classifier accuracy may be avoided.

A dynamic energy budget (DEB) model for the energy usage and reproduction of the Icelandic capelin (Mallotus villosus).

We apply a dynamic energy budget (DEB) model to the Icelandic capelin (Mallotus villosus) and introduce a new state variable to capture the roe production of individual fish. Species-specific coefficients are found for the capelin such as the shape coefficient and the Arrhenius temperature. We show how to link the DEB model to measurable quantities such as weight, length, fat, and roe content. We use data on measured 3-year old female capelin from 1999 to 2000 season from the Marine Research Institute of Iceland (MRI) and Matis, an Icelandic Food and Biotech R&D. We then find plausible parameter values for the DEB model by fitting the output of the model to these data. We obtain good fits between theory and observations, and the DEB model successfully reproduces weight, length, fat percentage and roe percentage of capelin. We discuss the effect of maturity on the spawning route of capelin, and describe how we intend to incorporate these results with an interacting particle model for the spawning migration of capelin.

Reliability of quantitative EEG features.

OBJECTIVE: To investigate the reliability of several well-known quantitative EEG (qEEG) features in the elderly in the resting, eyes closed condition and study the effects of epoch length and channel derivations on reliability. METHODS: Fifteen healthy adults, over 50 years of age, underwent 10 EEG recordings over a 2-month period. Various qEEG features derived from power spectral, coherence, entropy and complexity analysis of the EEG were computed. Reliability was quantified using an intraclass correlation coefficient. RESULTS: The highest reliability was obtained with the average montage, reliability increased with epoch length up to 40s, longer epochs gave only marginal improvement. The reliability of the qEEG features was highest for power spectral parameters, followed by regularity measures based on entropy and complexity, coherence being least reliable. CONCLUSIONS: Montage and epoch length had considerable effects on reliability. Several apparently unrelated regularity measures had similar stability. Reliability of coherence measures was strongly dependent on channel location and frequency bands. SIGNIFICANCE: The reliability of regularity measures has until now received limited attention. Low reliability of coherence measures in general may limit their usefulness in the clinical setting.

Dynamics of group formation in collective motion of organisms.

A mathematical description of the collective motion of organisms using a density-velocity model is presented. This model consists of a system of nonlinear parabolic equations, a forced Burgers equation for velocity and a diffusion-convection equation for density. The motion is mainly due to forces resulting from the differences between local density levels and a prescribed density level. The existence of a global attractor for a 1D density-velocity model is proved by asymptotic analysis to demonstrate different patterns in the attractors for density. The theoretical results are supplemented with numerical results. These patterns correspond to movements of collective organized groups of organisms such as fish schools and bird flocks.