Dendrimer-mediated permeation enhancement of chlorhexidine digluconate: Determination of in vitro skin permeability and visualisation of dermal distribution.

Chlorhexidine digluconate (CHG) is a cationic bisbiguanide used in the UK as the first-line skin antiseptic prior to surgery in the UK due to its favourable efficacy and safety profile, high affinity for skin binding and minimal reports of resistance. Despite this, bacteria remain within deeper skin layers, furrows and appendages that are considered inaccessible to CHG, due to its poor dermal penetration. In this study a third generation, polyamidoamine dendrimer (G3 PAMAM-NH2) was utilised to improve dermal penetration of CHG. A topical gel formulation was optimised to maximise CHG delivery (containing 0.5% gelling agent and 4% drug), followed by drug and dendrimer co-formulation into a commercially viable gel. The gel containing 4% CHG and 1 mM PAMAM dendrimer significantly increased the depth permeation of CHG compared to the commercial benchmark (Hibiscrub®, containing 4% w/v CHG) (p < 0.05). The optimised formulation was further characterised using Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS), which indicated that the depth of dermal penetration achieved was sufficient to reach the skin strata that typically harbours pathogenic bacteria, which is currently inaccessible by commercial CHG formulations. This study therefore indicates that a G3 PAMAM-NH2 dendrimer gel may be viable as a permeation enhancer of CHG, for improved skin antisepsis in those at risk of a skin or soft tissue infection as a result of surgical intervention.

Development of a Gaussian Process - feature selection model to characterise (poly)dimethylsiloxane (Silastic® ) membrane permeation.

OBJECTIVES: The current study aims to determine the effect of physicochemical descriptor selection on models of polydimethylsiloxane permeation. METHODS: A total of 2942 descriptors were calculated for a data set of 77 chemicals. Data were processed to remove redundancy, single values, imbalanced and highly correlated data, yielding 1363 relevant descriptors. For four independent test sets, feature selection methods were applied and modelled via a variety of Machine Learning methods. KEY FINDINGS: Two sets of molecular descriptors which can provide improved predictions, compared to existing models, have been identified. Best permeation predictions were found with Gaussian Process methods. The molecular descriptors describe lipophilicity, partial charge and hydrogen bonding as key determinants of PDMS permeation. CONCLUSIONS: This study highlights important considerations in the development of relevant models and in the construction and use of the data sets used in such studies, particularly that highly correlated descriptors should be removed from data sets. Predictive models are improved by the methodology adopted in this study, notably the systematic evaluation of descriptors, rather than simply using any and all available descriptors, often based empirically on in vitro experiments. Such findings also have clear relevance to a number of other fields.

The influence of diffusion cell type and experimental temperature on machine learning models of skin permeability.

OBJECTIVES: The aim of this study was to use Gaussian process regression (GPR) methods to quantify the effect of experimental temperature (Texp ) and choice of diffusion cell on model quality and performance. METHODS: Data were collated from the literature. Static and flow-through diffusion cell data were separated, and a series of GPR experiments was conducted. The effect of Texp was assessed by comparing a range of datasets where Texp either remained constant or was varied from 22 to 45 °C. KEY FINDINGS: Using data from flow-through diffusion cells results in poor model performance. Data from static diffusion cells resulted in significantly greater performance. Inclusion of data from flow-through cell experiments reduces overall model quality. Consideration of Texp improves model quality when the dataset used exhibits a wide range of experimental temperatures. CONCLUSIONS: This study highlights the problem of collating literature data into datasets from which models are constructed without consideration of the nature of those data. In order to optimise model quality data from only static, Franz-type, experiments should be used to construct the model and Texp should either be incorporated as a descriptor in the model if data are collated from a range of studies conducted at different temperatures.

Antimicrobial efficacy and mechanism of action of poly(amidoamine) (PAMAM) dendrimers against opportunistic pathogens.

The aim of this study was to investigate a range of poly(amidoamine) (PAMAM) dendrimer generations against Gram-positive and Gram-negative skin pathogens and to determine any differences in antimicrobial potency for different generations, characterising how differences in physicochemical properties influence antimicrobial efficacy. A range of tests were carried out, including viable count assays to determine half maximal inhibitory concentration (IC50) values for each dendrimer, membrane integrity studies and an inner membrane permeabilisation assay. This is supported by scanning electron microscopy imaging of the interactions observed between dendrimers and bacteria. The results of this study indicate that the antimicrobial efficacy of native PAMAM dendrimers is dependent on generation, concentration and terminal functionalities, for example, the concentration at 50% growth inhibition (MIC50) (µg/mL), against Staphylococcus aureus was between 26.77 for the G2-PAMAM-NH2 dendrimer and 2.881 for the G5-PAMAM-NH2 dendrimer. There was a strong correlation between membrane disruption and the determined biocidal activity, making it a key contributing mechanism of action. This study demonstrates that selection of the type of PAMAM dendrimer is important as their inherent antimicrobial efficacy varies according to their individual physicochemical properties. This understanding may pave the way for the development of enhanced dendrimer-based antimicrobial formulations and drug-delivery systems.

Dendrimer pre-treatment enhances the skin permeation of chlorhexidine digluconate: Characterisation by in vitro percutaneous absorption studies and Time-of-Flight Secondary Ion Mass Spectrometry.

Skin penetration and localisation of chlorhexidine digluconate (CHG) within the skin have been investigated in order to better understand and optimise the delivery using a nano polymeric delivery system of this topically-applied antimicrobial drug. Franz-type diffusion cell studies using in vitro porcine skin and tape stripping procedures were coupled with Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) to visualise the skin during various treatments with CHG and polyamidoamine dendrimers (PAMAM). Pre-treatment of the skin with PAMAM dendrimers significantly increased the amount and depth of permeation of CHG into the skin in vitro. The effect observed was not concentration dependant in the range 0.5-10mM PAMAM. This could be important in terms of the efficiency of treatment of bacterial infection in the skin. It appears that the mechanism of enhancement is due to the PAMAM dendrimer disrupting skin barrier lipid conformation or by occluding the skin surface. Franz-type diffusion cell experiments are complimented by the detailed visualisation offered by the semi-quantitative ToF-SIMS method which provides excellent benefits in terms of sensitivity and fragment ion specificity. This allows a more accurate depth profile of chlorhexidine permeation within the skin to be obtained and potentially affords the opportunity to map the co-localisation of permeants with skin structures, thus providing a greater ability to characterise skin absorption and to understand the mechanism of permeation, providing opportunities for new and more effective therapies.

Support vector regression to estimate the permeability enhancement of potential transdermal enhancers.

OBJECTIVES: Searching for chemicals that will safely enhance transdermal drug delivery is a significant challenge. This study applies support vector regression (SVR) for the first time to estimating the optimal formulation design of transdermal hydrocortisone formulations. METHODS: The aim of this study was to apply SVR methods with two different kernels in order to estimate the enhancement ratio of chemical enhancers of permeability. KEY FINDINGS: A statistically significant regression SVR model was developed. It was found that SVR with a nonlinear kernel provided the best estimate of the enhancement ratio for a chemical enhancer. CONCLUSIONS: Support vector regression is a viable method to develop predictive models of biological processes, demonstrating improvements over other methods. In addition, the results of this study suggest that a global approach to modelling a biological process may not necessarily be the best method and that a 'mixed-methods' approach may be best in optimising predictive models.

Simulated drug discovery process to conduct a synoptic assessment of pharmacy students.

OBJECTIVE. To implement and assess a task-based learning exercise that prompts pharmacy students to integrate their understanding of different disciplines. DESIGN. Master of pharmacy (MPharm degree) students were provided with simulated information from several preclinical science and from clinical trials and asked to synthesize this into a marketing authorization application for a new drug. Students made a link to pharmacy practice by creating an advice leaflet for pharmacists. ASSESSMENT. Students' ability to integrate information from different disciplines was evaluated by oral examination. In 2 successive academic years, 96% and 82% of students demonstrated an integrated understanding of their proposed new drug. Students indicated in a survey that their understanding of the links between different subjects improved. CONCLUSION. Simulated drug discovery provides a learning environment that emphasizes the connectivity of the preclinical sciences with each other and the practice of pharmacy.

Distribution and visualisation of chlorhexidine within the skin using ToF-SIMS: a potential platform for the design of more efficacious skin antiseptic formulations.

PURPOSE: In order to increase the efficacy of a topically applied antimicrobial compound the permeation profile, localisation and mechanism of action within the skin must first be investigated. METHODS: Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to visualise the distribution of a conventional antimicrobial compound, chlorhexidine digluconate, within porcine skin without the need for laborious preparation, radio-labels or fluorescent tags. RESULTS: High mass resolution and high spatial resolution mass spectra and chemical images were achieved when analysing chlorhexidine digluconate treated cryo-sectioned porcine skin sections by ToF-SIMS. The distribution of chlorhexidine digluconate was mapped throughout the skin sections and our studies indicate that the compound appears to be localised within the stratum corneum. In parallel, tape strips taken from chlorhexidine digluconate treated porcine skin were analysed by ToF-SIMS to support the distribution profile obtained from the skin sections. CONCLUSIONS: ToF-SIMS can act as a powerful complementary technique to map the distribution of topically applied compounds within the skin.

An evaluation of the potential of linear and nonlinear skin permeation models for the prediction of experimentally measured percutaneous drug absorption.

UNLABELLED: OBJECTIVES The developments in combinatorial chemistry have led to a rapid increase in drug design and discovery and, ultimately, the production of many potential molecules that require evaluation. Hence, there has been much interest in the use of mathematical models to predict dermal absorption. Therefore, the aim of this study was to test the performance of both linear and nonlinear models to predict the skin permeation of a series of 11 compounds. METHODS: The modelling in this study was carried out by the application of both quantitative structure permeability relationships and Gaussian process-based machine learning methods to predict the flux and permeability coefficient of the 11 compounds. The actual permeation of these compounds across human skin was measured using Franz cells and a standard protocol with high performance liquid chromatography analysis. Statistical comparison between the predicted and experimentally-derived values was performed using mean squared error and the Pearson sample correlation coefficient. KEY FINDINGS: The findings of this study would suggest that the models failed to accurately predict permeation and in some cases were not within two- or three-orders of magnitude of the experimentally-derived values. However, with this set of compounds the models were able to effectively rank the permeants. CONCLUSIONS: Although not suitable for accurately predicting permeation the models may be suitable for determining a rank order of permeation, which may help to select candidate molecules for in-vitro screening. However, it is important to note that such predictions need to take into account actual relative drug candidate potencies.

The application and limitations of mathematical modelling in the prediction of permeability across mammalian skin and polydimethylsiloxane membranes.

OBJECTIVES: Predicting the rate of percutaneous absorption of a drug is an important issue with the increasing use of the skin as a means of moderating and controlling drug delivery. One key feature of this problem domain is that human skin permeability (as K(p)) has been shown to be inherently non-linear when mathematically related to the physicochemical parameters of penetrants. As such, the aims of this study were to apply and evaluate Gaussian process (GP) regression methods to datasets for membranes other than human skin, and to explore how the nature of the dataset may influence its analysis. METHODS: Permeability data for absorption across rodent and pig skin, and artificial membranes (polydimethylsiloxane, PDMS, i.e. Silastic) membranes was collected from the literature. Two quantitative structure-permeability relationship (QSPR) models were used to compare with the GP models. Further performance metrics were computed in terms of all predictions, and a range of covariance functions were examined: the squared exponential (SE), neural network (NNone) and rational quadratic (QR) covariance functions, along with two simple cases of Matern covariance function (Matern3 and Matern5) where the polynomial order is set to 1 and 2, respectively. As measures of performance, the correlation coefficient (CORR), negative log estimated predictive density (NLL, or negative log loss) and mean squared error (MSE) were employed. KEY FINDINGS: The results demonstrated that GP models with different covariance functions outperform QSPR models for human, pig and rodent datasets. For the artificial membranes, GPs perform better in one instance, and give similar results in other experiments (where different covariance parameters produce similar results). In some cases, the GP predictions for some of the artificial membrane dataset are poorly correlated, suggesting that the physicochemical parameters employed in this study might not be appropriate for developing models that represent this membrane. CONCLUSIONS: While the results of this study indicate that permeation across rodent (mouse and rat) and pig skin is, in a statistical sense, similar, and that the artificial membranes are poor replacements of human or animal skin, the overriding issue raised in this study is the nature of the dataset and how it can influence the results, and subsequent interpretation, of any model produced for particular membranes. The size of the datasets, in both absolute and comparative senses, appears to influence model quality. Ideally, to generate viable cross-comparisons the datasets for different mammalian membranes should, wherever possible, exhibit as much commonality as possible.

The application of feature selection to the development of Gaussian process models for percutaneous absorption.

OBJECTIVES: The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical descriptors which exert the most significant influence on percutaneous absorption, and to compare such models with established existing models. METHODS: Gaussian processes, including automatic relevance detection (GPRARD) methods, were employed to develop models of percutaneous absorption that identified key physicochemical descriptors of percutaneous absorption. Using MatLab software, the statistical performance of these models was compared with single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs). Feature selection methods were used to examine in more detail the physicochemical parameters used in this study. A range of statistical measures to determine model quality were used. KEY FINDINGS: The inherently nonlinear nature of the skin data set was confirmed. The Gaussian process regression (GPR) methods yielded predictive models that offered statistically significant improvements over SLN and QSPR models with regard to predictivity (where the rank order was: GPR > SLN > QSPR). Feature selection analysis determined that the best GPR models were those that contained log P, melting point and the number of hydrogen bond donor groups as significant descriptors. Further statistical analysis also found that great synergy existed between certain parameters. It suggested that a number of the descriptors employed were effectively interchangeable, thus questioning the use of models where discrete variables are output, usually in the form of an equation. CONCLUSIONS: The use of a nonlinear GPR method produced models with significantly improved predictivity, compared with SLN or QSPR models. Feature selection methods were able to provide important mechanistic information. However, it was also shown that significant synergy existed between certain parameters, and as such it was possible to interchange certain descriptors (i.e. molecular weight and melting point) without incurring a loss of model quality. Such synergy suggested that a model constructed from discrete terms in an equation may not be the most appropriate way of representing mechanistic understandings of skin absorption.

Formulation and characterization of a captopril ethyl ester drug-in-adhesive-type patch for percutaneous absorption.

BACKGROUND: The ethyl ester of captopril has been shown to exhibit enhanced permeation across human skin compared to the parent drug. A drug-in-adhesive patch formulation of a captopril ethyl ester was therefore developed for optimum drug release. METHOD: A wide range of transdermal patches were prepared using two commercially available bioadhesive polymers. Investigational screening was conducted on the patches using microscopy, texture profile analysis, and infrared spectroscopy. Drug release profiles of suitable patches were obtained using both polydimethylsiloxane (Silastic) and porcine skin in vitro. RESULTS: Diffusion results across Silastic showed a gradual plateau in flux with increased drug loading that may be attributable to intramolecular interactions while flux across porcine skin was seen to increase with increasing patch thickness and attained a therapeutic level. CONCLUSIONS: This study demonstrated that adhesion and drug loading are significant factors in optimizing a topical patch formulation for the delivery of a captopril prodrug.

The application of Gaussian processes in the prediction of percutaneous absorption.

OBJECTIVES: The aim was to assess mathematically the nature of a skin permeability dataset and to determine the utility of Gaussian processes in developing a predictive model for skin permeability, comparing it with existing methods for deriving predictive models. METHODS: Principal component analysis was carried out in order to determine the nature of the dataset. MatLab software was used to assess the performance of Gaussian process, single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs) using a range of statistical measures. KEY FINDINGS: Principal component analysis showed that the dataset is inherently non-linear. The Gaussian process model yielded a predictive model that provides a significantly more accurate estimate of skin absorption than previous models, particularly QSPRs (which were consistently worse than Gaussian process or SLN models), and does so across a wider range of molecular properties. Gaussian process models appear particularly capable of providing excellent predictions where previous studies have shown QSPRs to fail, such as where penetrants have high log P and high molecular weight. CONCLUSIONS: A non-linear approach was more appropriate than QSPRs or SLNs for the analysis of the dataset employed herein, as the prediction and confidence values in the prediction given by the Gaussian process are better than with other methods examined. Gaussian process provides a novel way of analysing skin absorption data that is substantially more accurate, statistically robust and reflective of our empirical understanding of skin absorption than the QSPR methods so far applied to skin absorption.

Metabolism of captopril carboxyl ester derivatives for percutaneous absorption.

OBJECTIVES: To determine the metabolism of captopril n-carboxyl derivatives and how this may impact on their use as transdermal prodrugs. The pharmacological activity of the ester derivatives was also characterised in order to compare the angiotensin converting enzyme inhibitory potency of the derivatives compared with the parent drug, captopril. METHODS: The metabolism rates of the ester derivatives were determined in vitro (using porcine liver esterase and porcine ear skin) and in silico (using molecular modelling to investigate the potential to predict metabolism). KEY FINDINGS: Relatively slow pseudo first-order metabolism of the prodrugs was observed, with the ethyl ester displaying the highest rate of metabolism. A strong relationship was established between in-vitro methods, while in-silico methods support the use of in-vitro methods and highlight the potential of in-silico techniques to predict metabolism. All the prodrugs behaved as angiotensin converting enzyme inhibitors, with the methyl ester displaying optimum inhibition. CONCLUSIONS: In-vitro porcine liver esterase metabolism rates inform in-vitro skin rates well, and in-silico interaction energies relate well to both. Thus, in-silico methods may be developed that include interaction energies to predict metabolism rates.

An investigation into solvent-membrane interactions when assessing drug release from organic vehicles using regenerated cellulose membranes.

The influence of organic solvents on artificial membranes when assessing drug release from topical formulations is, generally, poorly characterised yet current guidelines require no characterisation of the membrane before, during or after an experiment. Therefore, the aim of this study was to determine the effect of solvent-membrane interactions when using in-vitro Franz cell methods for the assessment of corticosteroid release and to assess compliance or otherwise with Higuchi's equation. The rate of beclometasone dipropionate monohydrate (BDP) and betamethasone 17-valerate (BMV) release across a regenerated cellulose membrane (RCM), from both saturated solutions and commercial formulations, was determined. Increasing the ratio of organic solvent, compared with aqueous phase, in the donor fluid (DF) resulted in up to a 416-fold increase in steady-state flux. Further, alterations in the receiver fluid (RF) composition caused, in some cases, 337-fold increases in flux. Analysis indicated that the RCM remained chemically unchanged, that its pore size remained constant and that no drug partitioned into the membrane, regardless of the DF or RF employed. However, it was observed that the organic solvents had a thinning effect on the RCM, resulting in enhanced flux, which was potentially due to the variation in the diffusional path length. Such findings raise issues of the veracity of data produced from any membrane release study involving a comparison of formulations with differing solvent content.

Design, synthesis and characterization of captopril prodrugs for enhanced percutaneous absorption.

Most drugs are designed primarily for oral administration, but the activity and stability profiles desirable for this route often make them unsuitable for transdermal delivery. We were therefore interested in designing analogues of captopril, a model drug with poor percutaneous penetration, for which the sustained steady-state blood plasma level associated with transdermal delivery (and which is unattainable orally) would be particularly beneficial. Quantitative structure-permeability relationships (QSPRs) predicted that ester and thiol prodrug derivatives of captopril would have lower maximal transdermal flux (J(m)) than the parent drug, since the increases in permeability coefficient (k(p)) of prodrugs would be outweighed by the reductions in aqueous solubility. Therefore, the aim of this study was to synthesize a series of prodrugs of captopril and to determine if a QSPR model could be used to design therapeutically viable prodrugs. Molecules with the highest predicted k(p) values were synthesized and characterized, and J(m) measured in Franz diffusion cells from saturated aqueous donor across porcine skin (fresh and frozen). In-vitro metabolism was also measured. Captopril and the prodrugs crossed the skin relatively freely, with J(m) being highest for ethyl to butyl esters. Substantial first-order metabolism of the prodrugs was observed, suggesting that their enhanced percutaneous absorption was complemented by their metabolic performance. The results suggested that QSPR models provided excellent enhancements in drug delivery. This was not seen at higher lipophilicities, suggesting that issues of solubility need to be considered in conjunction with any such use of a QSPR model.

A potential anti-implantation and spermicidal strategy: putative derivatives of nonoxynol-9 and anti-inflammatory agents and their spermicidal activity.

OBJECTIVES: We report the synthesis of novel ester derivatives of nonoxynol-9, an approved spermicidal agent, using the non-steroidal inflammatory drugs (NSAIDs) ibuprofen and indomethacin. Indomethacin has previously been shown to inhibit the implantation of the fertilised ovum into the uterus wall of pregnant rats. It is proposed that nonoxynol-9, in combination with a non-selective NSAID may exhibit both anti-implantation and spermicidal properties. METHODS: Both novel derivatives and nonoxynol-9 were then tested on boar spermatozoa in order to establish if spermicidal activity was retained following the esterification. RESULTS: The results showed that both the ibuprofen and indomethacin derivatives enabled complete cell death of boar spermatozoa at a concentration of 100 microg ml(-1), which is comparable to nonoxynol-9 at the same concentration. CONCLUSIONS: These results indicate that NSAID derivatives of nonoxynol-9 retain the activity of the parent molecule and may have other advantages associated with the molecular incorporation of the NSAID moieties and their anti-implantation activity.

A Raman spectroscopic investigation of bioadhesive tetracaine local anaesthetic formulations.

Raman spectroscopy at 785 nm has been employed to characterise the properties of tetracaine in bioadhesive gel and patch formulations. In the first study, interactions between the drug and excipients in novel bioadhesive patch systems were characterised. It was determined that the drug did not interact with any of its formulation components, and that this was an important factor in its clinical performance, particularly the rapid onset of anaesthesia. Investigations of drug uptake in the stratum corneum from a gel formulation suggested that tetracaine rapidly undergoes a phase-change upon application to the skin. The intensity of the tetracaine Raman bands at approximately 1600 cm(-1) suggests that the local anaesthetic is rapidly absorbed into the skin. Decreases in Raman tetracaine band intensities, along with an absence in the concomitant alteration in the internal standard spectra, indicates an decrease in the tetracaine concentration present in the gel. Further, a baseline indicating complete tetracaine absorption appears to be reached after approximately 40 min of exposure. After this time little further absorption was observed, suggesting that the stratum corneum "reservoir" was saturated with tetracaine at this time. This is consistent with the optimum application time required for tetracaine gels to attain maximum clinical efficacy. This study has indicated the effectiveness of Raman spectroscopy in the analysis of gel-based pharmaceutical preparations, showing it to be a simple, rapid, virtually non-invasive technique for determination of tetracaine.

Effect of occlusion on the percutaneous penetration of linoleic acid and glycerol.

The effect of occlusion on the in vitro percutaneous absorption of linoleic acid was investigated. A greater skin concentration of linoleic acid from an ethanolic vehicle was observed in non-occluded experiments compared with occluded experiments (P<0.05). Such changes were not observed as consistently when ethanol was replaced with a less volatile organic solvent (cyclomethicone). These observations were attributed to the increase in the concentration gradient due to the unimpeded evaporation of volatile solvents, which provided a greater driving force and enhanced non-occluded delivery in these systems, compared with occluded systems. Conversely, the percutaneous absorption of a polar material (glycerol) from an aqueous solution did not yield any such differences. While more conclusive comparisons between volatile and non-volatile solvents and penetrants would be required to substantiate fully these comparisons, it is apparent that non-occlusion of volatile solvents may enhance percutaneous absorption. The physicochemical properties of the penetrant, for example its natural state at skin temperature (i.e. solid or liquid) may further determine the degree of enhanced percutaneous absorption compared with occluded environments.