Quantitative structure-permeability relationships (QSPRs) for percutaneous absorption

Methods for the characterisation of dermal uptake: Progress and perspectives for organophosphate esters

Organophosphate esters (OPEs) are a group of pollutants that are widely detected in the environment at high concentrations. They can adversely affect human health through multiple routes of exposure, including dermal uptake. Although attention has been paid to achieving an accurate and complete quantification of the dermal uptake of OPEs, existing evaluation methods and parameters have obvious weaknesses. This study reviewed two main categories of methodologies, namely the relative absorption (RA) model and the permeability coefficient (PC) model, which are widely used to assess the dermal uptake of OPEs. Although the PC model is more accurate and is increasingly used, the most important parameter in this model, the permeability coefficient (Kp), has been poorly characterised for OPEs, resulting in considerable errors in the estimation of the dermal uptake of OPEs. Thus, the detailed in vitro methods for the determination of Kp are summarised and sorted. Furthermore, the commonly used skin membranes are identified and the factors affecting Kp and corresponding mechanisms are discussed. In addition, the experimental conditions, conclusions, and available data on Kp values of the OPEs are thoroughly summarised. Finally, the corresponding knowledge gaps are proposed, and a more accurate and sophisticated experimental system and unknown Kp values for OPEs are suggested.

Comparison of supercritical fluid chromatographic methods to predict the skin permeability of pharmaceutical and cosmetic compounds

Supercritical fluid chromatography (SFC) was explored as an alternative for liquid chromatography to predict the skin permeability of pharmaceutical and cosmetic compounds. Nine dissimilar stationary phases were applied to screen a test set of 58 compounds. The experimental retention factors (log k), in addition to two sets of theoretical molecular descriptors, were applied to model the skin permeability coefficient. Different modelling approaches, i.e. multiple linear regression (MLR) and partial least squares (PLS) regression, were used. In general, the MLR models performed better than the PLS models for a given descriptor set. The results obtained on a cyanopropyl (CN) column provided the best correlation with the skin permeability data. The retention factors obtained on this column were included in a simple MLR model, together with the octanol-water partition coefficient and the number of atoms (r² = 0.81, RMSEC = 0.537 or 20.5% and RMSECV = 0.580 or 22.1%). The overall best MLR model included the chromatographic descriptor from a phenyl column and 18 descriptors (r² = 0.98, RMSEC = 0.167 or 6.2% and RMSECV = 0.238 or 8.9%). This model showed a good fit, on top of very good predictive features. However, stepwise MLR models with a reduced complexity could also be determined, with the best performance parameters obtained with the CN-column based retention and eight descriptors (r² = 0.95, RMSEC = 0.282 or 10.7% and RMSECV = 0.353 or 13.4%). SFC thus provides a suitable alternative to the liquid chromatographic techniques previously applied to model the skin permeability.

Parabens Permeation through Biological Membranes: A Comparative Study Using Franz Cell Diffusion System and Biomimetic Liquid Chromatography

Parabens (PBs) are used as preservatives to extend the shelf life of various foodstuffs, and pharmaceutical and cosmetic preparations. In this work, the membrane barrier passage potential of a subset of seven parabens, i.e., methyl-, ethyl-, propyl- isopropyl, butyl, isobutyl, and benzyl paraben, along with their parent compound, p-hydroxy benzoic acid, were studied. Thus, the Franz cell diffusion (FDC) method, biomimetic liquid chromatography (BLC), and in silico prediction were performed to evaluate the soundness of both describing their permeation through the skin. While BLC allowed the achievement of a full scale of affinity for membrane phospholipids of the PBs under research, the permeation of parabens through Franz diffusion cells having a carbon chain > ethyl could not be measured in a fully aqueous medium, i.e., permeation enhancer-free conditions. Our results support that BLC and in silico prediction alone can occasionally be misleading in the permeability potential assessment of these preservatives, emphasizing the need for a multi-technique and integrated experimental approach.

Mechanistic Insights into Passive Membrane Permeability of Drug-like Molecules from a Weighted Ensemble of Trajectories

Passive permeability of a drug-like molecule is a critical property assayed early in a drug discovery campaign that informs a medicinal chemist how well a compound can traverse biological membranes, such as gastrointestinal epithelial or restrictive organ barriers, so it can perform a specific therapeutic function. However, the challenge that remains is the development of a method, experimental or computational, which can both determine the permeation rate and provide mechanistic insights into the transport process to help with the rational design of any given molecule. Typically, one of the following three methods are used to measure the membrane permeability: (1) experimental permeation assays acting on either artificial or natural membranes; (2) quantitative structure–permeability relationship models that rely on experimental values of permeability or related pharmacokinetic properties of a range of molecules to infer those for new molecules; and (3) estimation of permeability from the Smoluchowski equation, where free energy and diffusion profiles along the membrane normal are taken as input from large-scale molecular dynamics simulations. While all these methods provide estimates of permeation coefficients, they provide very little information for guiding rational drug design. In this study, we employ a highly parallelizable weighted ensemble (WE) path sampling strategy, empowered by cloud computing techniques, to generate unbiased permeation pathways and permeability coefficients for a set of drug-like molecules across a neat 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine membrane bilayer. Our WE method predicts permeability coefficients that compare well to experimental values from an MDCK-LE cell line and PAMPA assays for a set of drug-like amines of varying size, shape, and flexibility. Our method also yields a series of continuous permeation pathways weighted and ranked by their associated probabilities. Taken together, the ensemble of reactive permeation pathways, along with the estimate of the permeability coefficient, provides a clearer picture of the microscopic underpinnings of small-molecule membrane permeation.

Physicochemical and biopharmaceutical aspects influencing skin permeation and role of SLN and NLC for skin drug delivery

The skin is a complex and multifunctional organ, in which the static versus dynamic balance is responsible for its constant adaptation to variations in the external environment that is continuously exposed. One of the most important functions of the skin is its ability to act as a protective barrier, against the entry of foreign substances and against the excessive loss of endogenous material. Human skin imposes physical, chemical and biological limitations on all types of permeating agents that can cross the epithelial barrier. For a molecule to be passively permeated through the skin, it must have properties, such as dimensions, molecular weight, pKa and hydrophilic-lipophilic gradient, appropriate to the anatomy and physiology of the skin. These requirements have limited the number of commercially available products for dermal and transdermal administration of drugs. To understand the mechanisms involved in the drug permeation process through the skin, the approach should be multidisciplinary in order to overcome biological and pharmacotechnical barriers. The study of the mechanisms involved in the permeation process, and the ways to control it, can make this route of drug administration cease to be a constant promise and become a reality. In this work, we address the physicochemical and biopharmaceutical aspects encountered in the pathway of drugs through the skin, and the potential added value of using solid lipid nanoparticles (SLN) and nanostructured lipid vectors (NLC) to drug permeation/penetration through this route. The technology and architecture for obtaining lipid nanoparticles are described in detail, namely the composition, production methods and the ability to release pharmacologically active substances, as well as the application of these systems in the vectorization of various pharmacologically active substances for dermal and transdermal applications. The characteristics of these systems in terms of dermal application are addressed, such as biocompatibility, occlusion, hydration, emollience and the penetration of pharmacologically active substances. The advantages of using these systems over conventional formulations are described and explored from a pharmaceutical point of view.

Predicting the Membrane Permeability of Fentanyl and Its Analogues by Molecular Dynamics Simulations

The lipid membrane is considered a crucial component of opioid general anesthesia. The main drug used for the induction and maintenance of opioid anesthesia is fentanyl and its various analogues. However, these drugs have different clinical effects, and detailed atomic-level insight into the drug–membrane interactions could lead to a better understanding how these drugs exert their anesthetic properties. In this study, we have used extensive umbrella sampling molecular dynamics simulations to study the permeation process of fentanyl and three of its analogues into a variety of simple phospholipid membrane models. Our simulations show that we can accurately predict the permeability coefficients of these drug molecules, which is an important process in understanding how pharmaceuticals reach their molecular targets. We were also able to show that one phospholipid provides more accurate predictions than other lipids commonly used in these types of permeation studies, which will aid future studies of these types of processes.

Physiologically-Based Pharmacokinetic Modeling to Support Determination of Bioequivalence for Dermatological Drug Products: Scientific and Regulatory Considerations

Physiologically-based pharmacokinetic (PBPK) modeling and simulation provides mechanism-based predictions of the pharmacokinetics of an active ingredient following its administration in humans. Dermal PBPK models describe the skin permeation and disposition of the active ingredient following the application of a dermatological product on the skin of virtual healthy and diseased human subjects. These models take into account information on product quality attributes, physicochemical properties of the active ingredient and skin (patho)physiology, and their interplay with each other. Regulatory and product development decision makers can leverage these quantitative tools to identify factors impacting local and systemic exposure. In the realm of generic drug products, the number of US Food and Drug Administratioin (FDA) interactions that use dermal PBPK modeling to support alternative bioequivalence (BE) approaches is increasing. In this report, we share scientific considerations on the development, verification and validation (V&V), and application of PBPK models within the context of a virtual BE assessment for dermatological drug products. We discuss the challenges associated with model V&V for these drug products stemming from the fact that target-site active ingredient concentrations are typically not measurable. Additionally, there are no established relationships between local and systemic PK profiles, when the latter are quantifiable. To that end, we detail a multilevel model V&V approach involving validation for the model of the drug product of interest coupled with the overall assessment of the modeling platform in use while leveraging in vitro and in vivo data related to local and systemic bioavailability.

RP-18 TLC Chromatographic and Computational Study of Skin Permeability of Steroids

The skin permeability of steroids, as investigated in this study, is important because some of these compounds are, or could, be used in preparations applied topically. Several models of skin permeability, involving thin layer chromatographic and calculated descriptors, were generated and validated using K_p reference values obtained in silico and then tested on a group of solutes whose experimental K_p values could be found (log K_p^exp). The study established that the most applicable log K_p model is based on RP-18 thin layer chromatographic data (R_M) and the calculated descriptors V_M (molar volume) and PSA (polar surface area). Two less efficient, yet simple, equations based on PSA or V_M combined with HD (H-donor count) can be used with caution for rapid, rough estimations of compounds’ skin permeability prior to their chemical synthesis.

Lanolin-Based Synthetic Membranes for Transdermal Permeation and Penetration Drug Delivery Assays

Due to the high similarity in composition and structure between lanolin and human SC lipids, we will work with two models from wool wax. Two types of lanolin were evaluated: one extracted with water and surfactants (WEL) and the other extracted with organic solvents (SEL). Skin permeation and skin penetration studies were performed with two active compounds to study the feasibility of the use of lanolin-based synthetic membranes as models of mammalian skin. Diclofenac sodium and lidocaine were selected as the active compounds considering that they have different chemical natures and different lipophilicities. In the permeation assay with SEL, a better correlation was obtained with the less permeable compound diclofenac sodium. This assay suggests the feasibility of using artificial membranes with SEL as a model for percutaneous absorption studies, even though the lipophilic barrier should be improved. Penetration profiles of the APIs through the SEL and WEL membranes indicated that the two membranes diminish penetration and can be considered good membrane surrogates for skin permeability studies. However, the WEL membranes, with a pH value similar to that of the skin surface, promoted a higher degree of diminution of the permeability of the two drugs, similar to those found for the skin.

Comparison of in-silico modelling and reversed-phase liquid chromatographic retention on an octadecyl silica column to predict skin permeability of pharmaceutical and cosmetic compounds

This study focuses on the in-silico modelling of the skin permeability using a test set of pharmaceutical and cosmetic compounds. Two sets of theoretical molecular descriptors, obtained from the E-Dragon and Vega ZZ software programs, were used in the models. Different linear regression methods, i.e. Multiple Linear Regression (MLR) and Partial Least Squares (PLS) regression, were applied for modelling and estimating the skin permeability. The best model was obtained using a stepwise MLR approach on the E-Dragon descriptor set. In a second step, the retention of the test set compounds was measured on a C18 column at two pH levels: pH 5.5 and pH 7. Different organic-modifier fractions were applied in the mobile phase to be able to extrapolate the retention factors to a log k_w value, with k_w the estimated retention factor in an aqueous mobile phase without organic modifier. Thereafter it was examined whether combining this chromatographic descriptor with the theoretical descriptors could improve the modelling of the skin permeability. The chromatographic descriptor often did not show an added value compared to the models containing only theoretical descriptors. Therefore, the in-silico models were preferred, and these models could be useful to predict the skin permeability of pharmaceutical and cosmetic compounds.

Skin penetration/permeation success determinants of nanocarriers: Pursuit of a perfect formulation

The advent of nanocarriers in the field of pharmaceutical drug delivery, while exhibiting considerable advantages, has created challenges for researchers. Among the applications of nanocarriers, drug delivery to the skin has attracted increasing attention in recent decades due to its advantages over oral and parenteral administration. Accordingly, this work attempts to discuss the major obstacles surrounding topically applied formulations and different nanocarriers' potential to overcome these barriers to investigate whether their passive penetration through the skin is likely. Therefore, skin anatomical views and transcutaneous pathways are briefly reviewed. Factors commonly thought to influence skin penetration are discussed from the perspective of particularly penetrating nanocarriers. The formulation of these nanocarriers is outlined, and promising constituents are highlighted to help investigators optimize nanocarrier formulations.

Assessment of Finite and Infinite Dose In Vitro Experiments in Transdermal Drug Delivery

Penetration, usually with finite dosing, provides data about the total active amount in the skin and permeation, being the most used methodology, usually with infinite dosing, leads to data about pharmacokinetic parameters. The main objective of this work is to assess if results from permeation, most of them at finite dose, may be equivalent to those from penetration usually at infinite dose. The transdermal behavior of four drugs with different physicochemical properties (diclofenac sodium, ibuprofen, lidocaine, and caffeine) was studied using penetration/finite and kinetic permeation/infinite dose systems using vertical Franz diffusion cells to determine the relationships between permeation and penetration profiles. Good correlation of these two in vitro assays is difficult to find; the influence of their dosage and the proportion of different ionized/unionized compounds due to the pH of the skin layers was demonstrated. Finite and infinite dose regimens have different applications in transdermal delivery. Each approach presents its own advantages and challenges. Pharmaceutical industries are not always clear about the method and the dose to use to determine transdermal drug delivery. Being aware that this study presents results for four actives with different physicochemical properties, it can be concluded that the permeation/infinite results could not be always extrapolated to those of penetration/finite. Differences in hydrophilicity and ionization of drugs can significantly influence the lack of equivalence between the two methodologies. Further investigations in this field are still needed to study the correlation of the two methodologies and the main properties of the drugs that should be taken into account.

Application of RP-18 TLC Retention Data to the Prediction of the Transdermal Absorption of Drugs

Several chromatographic parameters (R_M⁰ and S obtained from RP-18 TLC with methanol—pH 7.4 phosphate buffer mobile phases by extrapolation to zero concentration of methanol; R_f and R_M obtained from RP-18 TLC with acetonitrile—pH 7.4 phosphate buffer 70:30 v/v as a mobile phase) and calculated molecular descriptors (molecular weight—M_W; molar volume—V_M; polar surface area—PSA; total count of nitrogen and oxygen atoms—(N+O); H-bond donor count—HD; H-bond acceptor count—HA; distribution coefficient—log D; total energy—E_T; binding energy—E_b; hydration energy—E_h; energy of the highest occupied molecular orbital—E_HOMO; energy of the lowest unoccupied orbital—E_LUMO; electronic energy—E_e; surface area—S_a; octanol-water partition coefficient—log P; dipole moment—DM; refractivity—R, polarizability—α) and their combinations (R_f/PSA, R_M/M_W, R_M/V_M) were tested in order to generate useful models of solutes’ skin permeability coefficient log K_p. It was established that neither R_M⁰ nor S obtained in the conditions used in this study is a good predictor of the skin permeability coefficient. The chromatographic parameters R_f and R_f/PSA were also unsuitable for this purpose. A simple and potentially useful, purely computational model based on (N+O), log D and HD as independent variables and accounting for ca. 83% of total variability was obtained. The evaluation of parameters derived from R_M (R_M, R_M/M_W, R_M/V_M) as independent variables in log K_p models proved that R_M/V_M is the most suitable descriptor belonging to this group. In a search for a reliable log K_p model based on this descriptor two possibilities were considered: a relatively simple model based on 5 independent variables: (N+O), log D, R_M/V_M, E_T and E_h and a more complex one, involving also E_b, M_W and PSA.

Preparation and Evaluation of Cubic Nanoparticles for Improved Transdermal Delivery of Propranolol Hydrochloride

Transdermal drug delivery of propranolol hydrochloride (PRH) is promising for the treatment of infantile hemangioma (IH). Clinically used PRH hydrogel fails to reach the deep IH for complete recovery. In this study, the PRH-loaded cubic nanoparticles (CNPs) were prepared to promote the transdermal effect of PRH. A remote drug loading method was developed to prepare the PRH-CNPs. For the traditional passive drug loading method, the largest encapsulation efficiency (EE%) was around 50%. The remote drug loading was performed by increasing the pH of the mixture of blank CNPs and PRH solution. The optimal PRH-CNPs showed an EE% of 90.15 ± 2.44% at pH 8.5. The permeation of the PRH solution was poor while the PRH-CNPs showed greatly enhanced skin permeation. It was found that smaller-sized PRH-CNPs contributed to increased skin permeation and retention. In addition, the PRH-CNPs had higher cytotoxicity towards the EOMA cells when compared with the PRH solution. During storage for 1 month, the PRH-CNPs kept stable size distribution, pH, and EE%. In conclusion, results of this study suggested that the PRH-CNPs could be a potential candidate for the treatment of the IH by transdermal delivery.

Topical agents: a thoughtful choice for multimodal analgesia

For over a thousand years, various substances have been applied to the skin to treat pain. Some of these substances have active ingredients that we still use today. However, some have been discontinued due to their harmful effect, while others have been long forgotten. Recent concerns regarding the cardiovascular and renal risk from nonsteroidal anti-inflammatory drugs, and issues with opioids, have resulted in increasing demand and attention to non-systemic topical alternatives. There is increasing evidence of the efficacy and safety of topical agents in pain control. Topical analgesics are great alternatives for pain management and are an essential part of multimodal analgesia. This review aims to describe essential aspects of topical drugs that physicians should consider in their practice as part of multimodal analgesia. This review describes the mechanism of popular topical analgesics and also introduces the most recently released and experimental topical medications.

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.

Correlations Between Skin Barrier Integrity and Delivery of Hydrophilic Molecules in the Presence of Penetration Enhancers

PURPOSE

We investigated the potential correlations between skin barrier integrity and hydrophilic drugs distribution in skin in the presence of different types of penetration enhancers (PEs) and their combinations.

METHODS

We measured skin conductivity to evaluate skin barrier integrity before and after the topical application of different chemical PEs, physical PE, peptide PE and their combinations in vitro. We also investigated their effect on the skin distribution profiles of two hydrophilic model drugs, Fluorescein sodium (376 Da) and Fluorescein isothiocyanate-dextrans 10 (10 KDa).

RESULTS

The physical PE significantly increased the skin conductivity compared to all other PEs, while the peptide PE had no effect on it. The drug deposition in different skin layers was not only dependent on PE applied but also its own molecular weight. We further found two excellent correlations: one (R² = 0.9388) between skin barrier integrity and total skin absorption of FNa and another one(R² = 0.9212) between skin barrier integrity and the deposition of FNa in dermis and receptor in presence of chemical or physical PEs and their combinations.

CONCLUSIONS

The total skin absorption or the deposition in dermis and receptor of small hydrophilic drug in the presence of chemical and physical PEs and their combinations show a good correlation with skin barrier integrity. However, such correlations hold true neither for large hydrophilic drug nor for peptide PE. All good relationships found in this work will allow screening suitable PEs or combinations by measuring the skin conductivity induced by corresponding PEs. Graphical Abstract The total skin absorption of small hydrophilic drug shows a good correlation with skin barrier integrity in the presence of chemical and physical penetration enhancers and their combinations. However, such a correlation hold true neither for large hydrophilic drug nor for peptide penetration enhancer.

Mineral oil in food, cosmetic products, and in products regulated by other legislations

For a few years, mineral oils and their potential adverse health effects have been a constant issue of concern in many regulatory areas such as food, cosmetics, other consumer products, and industrial chemicals. Analytically, two fractions can be distinguished: mineral oil saturated hydrocarbons (MOSH) and mineral oil aromatic hydrocarbons (MOAH). This paper aims at assessing the bioaccumulative potential and associated histopathological effects of MOSH as well as the carcinogenic potential of MOAH for consumer-relevant mineral oils. It also covers the absorption, distribution, metabolism, and excretion of MOSH and MOAH upon oral and dermal exposures. The use and occurrence of consumer-relevant, highly refined mineral oils in food, cosmetics and medicinal products are summarized, and estimates for the exposure of consumers are provided. Also addressed are the challenges in characterizing the substance identity of mineral oil products under REACH. Evidence from more recent autopsy and biopsy studies, along with information on decreasing food contamination levels, indicates a low risk for adverse hepatic lesions that may arise from the retention of MOSH in the liver. With respect to MOAH, at present there is no indication of any carcinogenic effects in animals dermally or orally exposed to highly refined mineral oils and waxes. Such products are used not only in cosmetics but also in medicinal products and as additives in food contact materials. The safety of these mineral oil-containing products is thus indirectly documented by their prevalent and long-term use, with a simultaneous lack of clinical and epidemiological evidence for adverse health effects.

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 (T_exp ) 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 T_exp was assessed by comparing a range of datasets where T_exp 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 T_exp 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 T_exp should either be incorporated as a descriptor in the model if data are collated from a range of studies conducted at different temperatures.

Airborne Particulate Matter: Human Exposure and Health Effects

OBJECTIVE

Exposure to airborne particulate matter (PM) is estimated to cause millions of premature deaths annually. This work conveys known routes of exposure to PM and resultant health effects.

METHODS

A review of available literature.

RESULTS

Estimates for daily PM exposure are provided. Known mechanisms by which insoluble particles are transported and removed from the body are discussed. Biological effects of PM, including immune response, cytotoxicity, and mutagenicity, are reported. Epidemiological studies that outline the systemic health effects of PM are presented.

CONCLUSION

While the integrated, per capita, exposure of PM for a large fraction of the first-world may be less than 1 mg per day, links between several syndromes, including attention deficit hyperactivity disorder (ADHD), autism, loss of cognitive function, anxiety, asthma, chronic obstructive pulmonary disease (COPD), hypertension, stroke, and PM exposure have been suggested. This article reviews and summarizes such links reported in the literature.

In silico prediction of dermal absorption of pesticides - an evaluation of selected models against results from in vitro testing

Current guidance for the estimation of dermal absorption (DA) of pesticides recommends the use of default values, read-across of information between formulations and in vitro testing. While QSARs exist to estimate percutaneous absorption, their use is currently not encouraged. Therefore, the potential of publicly available models for DA estimation was investigated based on data from 564 human in vitro DA experiments on pesticides. The classic Potts Guy model, the correction of Cleek Bunge for highly lipophilic chemicals, the mechanistic model of Mitragotri, and the COSMOS model were used to estimate the permeability coefficient k_p. Different approaches were explored to calculate the percentage of external dose absorbed. IH SkinPerm was examined as stand-alone model. The models generally failed to accurately predict experimental values. For 30-40% of the predictions, there was overestimation by one order of magnitude. Three models underpredicted >10% of the cases, the remaining models <5%. DA of hydrophilic substances was typically underpredicted. Overprediction was more prominent for solid preparations and suspensions. The molecular weight, irritation potential and skin thickness did not correlate with the models' predictivity. Of the models investigated, IH SkinPerm performed best with 38% of the predictions within one order of magnitude and 2% underpredicted cases.

Development of a nano-QSPR model to predict band gaps of spherical metal oxide nanoparticles

Antibacterial activities and cytotoxicity of metal oxide nanoparticles are determined by their special band structures, which also influence their potential ecological risks. Traditional experimental determination of the band gap is time-consuming, while the accuracy of theoretical computation depends on the selected algorithm, for which higher precision algorithms, being more expensive, can give a more accurate band gap. Therefore, in this study, a quantitative structure–property relationship (QSPR) model, highlighting the influence of crystalline type and material size, was developed to predict the band gap of metal oxide nanoparticles rapidly and accurately. The structural descriptors for metal oxide nanoparticles were generated via quantum chemistry computations, among which heat of formation and beta angle of the unit cell were the most important parameters influencing band gaps. The developed model shows great robustness and predictive ability (R² = 0.848, RMSE = 0.378 eV, RMSE_CV = 0.478 eV, Q_EXT² = 0.814, RMSE_P = 0.408 eV). The current study can assist in screening the ecological risks of existing metal oxide nanoparticles and may act as a reference for newly designed materials.

Antibacterial activities and cytotoxicity of metal oxide nanoparticles are determined by their special band structures, which also influence their potential ecological risks.

Model fitting for small skin permeability data sets: hyperparameter optimisation in Gaussian Process Regression

OBJECTIVES

The aim of this study was to investigate how to improve predictions from Gaussian Process models by optimising the model hyperparameters.

METHODS

Optimisation methods, including Grid Search, Conjugate Gradient, Random Search, Evolutionary Algorithm and Hyper-prior, were evaluated and applied to previously published data. Data sets were also altered in a structured manner to reduce their size, which retained the range, or 'chemical space' of the key descriptors to assess the effect of the data range on model quality.

KEY FINDINGS

The Hyper-prior Smoothbox kernel results in the best models for the majority of data sets, and they exhibited significantly better performance than benchmark quantitative structure-permeability relationship (QSPR) models. When the data sets were systematically reduced in size, the different optimisation methods generally retained their statistical quality, whereas benchmark QSPR models performed poorly.

CONCLUSIONS

The design of the data set, and possibly also the approach to validation of the model, is critical in the development of improved models. The size of the data set, if carefully controlled, was not generally a significant factor for these models and that models of excellent statistical quality could be produced from substantially smaller data sets.

Management of chronic neuropathic pain with single and compounded topical analgesics

The goal of our review was to emphasize important aspects that physicians should take into consideration when prescribing topical analgesics as part of chronic neuropathic pain treatment. We discuss the dermatopharmacokinetics and microstructural components of the skin, differences between topical and transdermal drug delivery, and topical medication effects on peripheral neuropathy and central sensitization. Even though the US FDA approved topical analgesics are 8%-capsaicin and 5%-lidocaine patches for treating postherpetic neuralgia, there are many other studies conducted on the efficacy of topical ketamine cream, clonidine gel, topical gabapentin, topical baclofen and topical phenytoin for peripheral neuropathic pain, either alone or in combination with other formulations. Furthermore, we discuss new compounded topical analgesics that are becoming more popular and that are showing promising results in the management of chronic peripheral neuropathies. However, more studies are needed for elucidation of the role of topical analgesics and their effects, especially when combined with other treatments.

Plasticity of skin water permeability and skin thickness in the amphibious mangrove rivulus Kryptolebias marmoratus

The skin of amphibious fishes is a multipurpose organ, important for gas and ion exchange and nitrogen excretion when fish are out of water (emersed). We tested the hypothesis that skin permeability is altered to maintain water balance through changes in water permeability and skin thickness during salinity acclimation and/or when fish emerse, using the euryhaline, amphibious fish Kryptolebias marmoratus as a model. We first recorded the behaviour of fish out of water to determine which part of the cutaneous surface was in contact with the substrate. Fish spent about 70% of their time on their ventral surface when out of water. Osmotic permeability of the skin was assessed in fish acclimated to 0.3 or 45‰ using ³H₂O fluxes in an in vitro micro-Ussing chamber setup. In freshwater-acclimated fish, ³H₂O influx across the skin was significantly higher compared to hypersaline-acclimated fish, with no significant changes in efflux. Prolonged emersion (7 days) resulted in an increase in skin ³H₂O influx, but not efflux in fish acclimated to a moist 45‰ substrate. In a separate experiment, dorsal epidermal skin thickness increased while the ventral dermis thickness decreased in fish emersed for over a week. However, there was no link between regional skin thickness and water flux in our experiments. Taken together, these findings suggest that K. marmoratus alter skin permeability to maximize water uptake while emersed in hypersaline conditions, adjustments that probably help them survive months of emersion during the dry season when drinking to replace water loss is not possible.

Benzalkonium Chloride: An Irritant and Sensitizer

BACKGROUND

Benzalkonium chloride (BAK) is a known irritant, and potentially cross-reacting quaternary ammonium compounds are commonly used as preservatives in personal care products.

OBJECTIVE

The aim of the study was to review positive reactions to BAK in 615 patients patch tested for suspected allergic contact dermatitis.

METHODS

A retrospective chart review was performed in 615 patients patch tested from June 2015 to October 2016. All patients were tested to a Modified American Contact Dermatitis Society core series of 70 allergens including BAK (0.1% aqueous). Initial readings were performed at 48 hours with final readings performed between 72 and 168 hours. Results were graded as + (weak: papules and erythema), ++ (strong: papules and edema or vesicles), or +++ (extreme: coalescing vesicles, spreading or bullous reactions).

RESULTS

A total of 141 men (23%) and 475 women (77%) were tested (mean age, 49 years). Four hundred thirty-two (70%) were atopic. Of 615 patients, 198 (32%) tested positive to BAK, and 64 (10%) had ++ or +++ reactions at their final reading. On average, BAK-positive patients were using at least 1 product containing BAK or possible cross-reactors.

CONCLUSIONS

Widespread exposure to irritants in dermatitis patients can predispose to sensitization. Products containing BAK or potential cross-reactors should be used carefully in patients with compromised skin barriers.

Impact of Chemical Structure on Conjunctival Drug Permeability: Adopting Porcine Conjunctiva and Cassette Dosing for Construction of In Silico Model

Conjunctiva occupies most of the ocular surface area, and conjunctival permeability affects ocular and systemic drug absorption of topical ocular medications. Therefore, the aim of this study was to obtain a computational in silico model for structure-based prediction of conjunctival drug permeability. This was done by employing cassette dosing and quantitative structure-property relationship (QSPR) approach. Permeability studies were performed ex vivo across fresh porcine conjunctiva and simultaneous dosing of a cassette mixture composed of 32 clinically relevant drug molecules with wide chemical space. The apparent permeability values were obtained using drug concentrations that were quantified with liquid chromatography tandem-mass spectrometry. The experimental data were utilized for building a QSPR model for conjunctival permeability predictions. The conjunctival permeability values presented a 17-fold range (0.63-10.74 × 10^-6 cm/s). The final QSPR had a Q² value of 0.62 and predicted the external test set with a mean fold error of 1.34. The polar surface area, hydrogen bond donor, and halogen ratio were the most relevant descriptors for defining conjunctival permeability. This work presents for the first time a predictive QSPR model of conjunctival drug permeability and a comprehensive description on conjunctival isolation from the porcine eye. The model can be used for developing new ocular drugs.

Biological and environmental surface interactions of nanomaterials: characterization, modeling, and prediction

The understanding of nano-bio interactions is deemed essential in the design, application, and safe handling of nanomaterials. Proper characterization of the intrinsic physicochemical properties, including their size, surface charge, shape, and functionalization, is needed to consider the fate or impact of nanomaterials in biological and environmental systems. The characterizations of their interactions with surrounding chemical species are often hindered by the complexity of biological or environmental systems, and the drastically different surface physicochemical properties among a large population of nanomaterials. The complexity of these interactions is also due to the diverse ligands of different chemical properties present in most biomacromolecules, and multiple conformations they can assume at different conditions to minimize their conformational free energy. Often these interactions are collectively determined by multiple physical or chemical forces, including electrostatic forces, hydrogen bonding, and hydrophobic forces, and calls for multidimensional characterization strategies, both experimentally and computationally. Through these characterizations, the understanding of the roles surface physicochemical properties of nanomaterials and their surface interactions with biomacromolecules can play in their applications in biomedical and environmental fields can be obtained. To quantitatively decipher these physicochemical surface interactions, computational methods, including physical, statistical, and pharmacokinetic models, can be used for either analyses of large amounts of experimental characterization data, or theoretical prediction of the interactions, and consequent biological behavior in the body after administration. These computational methods include molecular dynamics simulation, structure-activity relationship models such as biological surface adsorption index, and physiologically-based pharmacokinetic models. WIREs Nanomed Nanobiotechnol 2017, 9:e1440. doi: 10.1002/wnan.1440 For further resources related to this article, please visit the WIREs website.

Development of a novel in silico model of zeta potential for metal oxide nanoparticles: a nano-QSPR approach

Once released into the aquatic environment, nanoparticles (NPs) are expected to interact (e.g. dissolve, agglomerate/aggregate, settle), with important consequences for NP fate and toxicity. A clear understanding of how internal and environmental factors influence the NP toxicity and fate in the environment is still in its infancy. In this study, a quantitative structure-property relationship (QSPR) approach was employed to systematically explore factors that affect surface charge (zeta potential) under environmentally realistic conditions. The nano-QSPR model developed with multiple linear regression (MLR) was characterized by high robustness [Formula: see text] and external predictivity [Formula: see text] The results clearly showed that zeta potential values varied markedly as functions of the ionic radius of the metal atom in the metal oxides, confirming that agglomeration and the extent of release of free MexOy largely depend on their intrinsic properties. A developed nano-QSPR model was successfully applied to predict zeta potential in an ionized solution of NPs for which experimentally determined values of response have been unavailable. Hence, the application of our model is possible when the values of zeta potential in the ionized solution for metal oxide nanoparticles are undetermined, without the necessity of performing more time consuming and expensive experiments. We believe that our studies will be helpful in predicting the conditions under which MexOy is likely to become problematic for the environment and human health.

Estimating Maximal In Vitro Skin Permeation Flux from Studies Using Non-sink Receptor Phase Conditions

PURPOSE

This study explored the impact of non-sink receptor conditions on the in vitro skin permeation test (IVPT) and sought to estimate equivalent sink condition IVPT data.

METHODS

Simulated diffusion model and experimental IVPT data were generated for ethyl salicylate across human epidermal membranes in Franz diffusion cells using six different receptor phases, with a 10 fold variation in ethyl salicylate solubility.

RESULTS

Both simulated and experimental IVPT - time profiles were markedly affected by receptor phase solubility and receptor sampling rates. Similar sink condition equivalent estimated maximum fluxes were obtained by nonlinear regression and adjustment of linear regression estimates of steady state flux for relative saturation of the receptor phase over time for the four receptor phases in which the ethyl salicylate was relatively soluble. The markedly lower steady - state fluxes found for the other two phases in which ethyl salicylate was less soluble was attributed to an aqueous solution boundary layer effect.

CONCLUSIONS

Non-sink receptor phase IVPT data can be used to derive equivalent sink receptor phase IVPT data provided the receptor phase solubility and hydrodynamics are sufficient to minimise the impact of aqueous diffusion layers on IVPT data.

Adaption of a dermal in vitro method to investigate the uptake of chemicals across amphibian skin

BACKGROUND

Literature data indicate that terrestrial life stages of amphibians may be more sensitive to xenobiotics than birds or mammals. It is hypothesized that dermal exposure could potentially be a significant route of exposure for amphibians, as there is evidence that their skin is more permeable than the skin of other vertebrate species. Thus, higher amounts of xenobiotics might enter systemic circulation by dermal uptake resulting in adverse effects. Heretofore, no guidelines exist to investigate dermal toxicity of chemicals to amphibians. In order to minimize vertebrate testing, this work was targeted to develop an in vitro test system as a possible model to assess the dermal uptake of chemicals across amphibian skin.

RESULTS

The dermal absorption in vitro method (OECD guideline 428), an established toxicological (mammal) test procedure, was adapted to amphibian skin, in a first approach using the laboratory model organism Xenopus laevis and reference compounds (caffeine and testosterone). Skin permeability to both reference substances was significantly higher compared to published mammalian data. Caffeine permeated faster across the skin than testosterone, with ventral skin tending to be more permeable than dorsal skin. As usage of frozen mammalian skin is accepted, frozen skin of X. laevis was tested in parallel. To the freshly excised skin, however, freezing led to increased skin permeability, in particular to caffeine, indicating a loss of skin integrity due to freezing (without additional preservation measures).

CONCLUSIONS

This work has demonstrated that the chosen method can be applied successfully to amphibian skin, providing the basis for further investigations. In future, well-established in vitro test systems and a broad dataset for many chemicals may help assess potential amphibian risk from xenobiotics without the need for extensive vertebrate testing.

A review of the current state of the art of physiologically-based tests for measuring human dermal in vitro bioavailability of polycyclic aromatic hydrocarbons (PAH) in soil

Polycyclic Aromatic Hydrocarbons are classed as Persistent Organic Pollutants, a large group of compounds that share similar characteristics. They are lipophilic, resistant to degradation in the environment and harmful to human and environmental health. Soil has been identified as the primary reservoir for Polycyclic Aromatic Hydrocarbons in the United Kingdom. This study reviews the literature associated with, or is relevant to, the measurement and modelling of dermal absorption of Polycyclic Aromatic Hydrocarbons from soils. The literature illustrates the use of in vivo, in vitro and in silico methods from a wide variety of scientific disciplines including occupational and environmental exposure, medical, pharmaceutical and cosmetic research and associated mathematical modelling. The review identifies a number of practical shortcomings which must be addressed if dermal bioavailability tests are to be applied to laboratory analysis of contaminated soils for human health risk assessment.

Supporting read-across using biological data

Read-across, i.e. filling toxicological data gaps by relating to similar chemicals, for which test data are available, is usually done based on chemical similarity. Besides structure and physico-chemical properties, however, biological similarity based on biological data adds extra strength to this process. In the context of developing Good Read-Across Practice guidance, a number of case studies were evaluated to demonstrate the use of biological data to enrich read-across. In the simplest case, chemically similar substances also show similar test results in relevant in vitro assays. This is a well-established method for the read-across of e.g. genotoxicity assays. Larger datasets of biological and toxicological properties of hundreds and thousands of substances become increasingly available enabling big data approaches in read-across studies. Several case studies using various big data sources are described in this paper. An example is given for the US EPA's ToxCast dataset allowing read-across for high quality uterotrophic assays for estrogenic endocrine disruption. Similarly, an example for REACH registration data enhancing read-across for acute toxicity studies is given. A different approach is taken using omics data to establish biological similarity: Examples are given for stem cell models in vitro and short-term repeated dose studies in rats in vivo to support read-across and category formation. These preliminary biological data-driven read-across studies highlight the road to the new generation of read-across approaches that can be applied in chemical safety assessment.

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.

Assessment of Lemon Balm (Melissa officinalis L.) Hydrogels: Quality and Bioactivity in Skin Cells

The aim of the study was to design gels with lemon balm extract, assess their quality, and investigate the effect of rosmarinic acid on skin cells in normal conditions and under oxidative stress. Methods. The quantities of rosmarinic acid (RA) released from gels were evaluated by applying the HPLC technique. HaCaT cell viability was assessed by using the MTT method. ROS generation was measured using DCFH-DA dye. The results showed that the gelling material affected the release of RA content from gels. Lower and slower RA content release was determined in carbomer-based gels. After 6 hours of biopharmaceutical research in vitro, at least 4% of RA was released from the gel. The results of the biological studies on HaCaT cells demonstrated that, in the oxidative stress conditions, RA reduced intracellular ROS amounts to 28%; 0.25–0.5 mg/mL of RA increased cell viability by 10–24% and protected cells from the damage caused by H₂O₂. Conclusions. According to research results, it is appropriate to use a carbomer as the main gelling material, and its concentration should not exceed 1.0%. RA, depending on the concentration, reduces the amount of intracellular ROS and enhances cell viability in human keratinocytes in oxidative stress conditions.

Using water-solvent systems to estimate in vivo blood-tissue partition coefficients

BACKGROUND

Blood-tissue partition coefficients indicate how a chemical will distribute throughout the body and are an important part of any pharmacokinetic study. They can be used to assess potential toxicological effects from exposure to chemicals and the efficacy of potential novel drugs designed to target certain organs or the central nervous system. In vivo measurement of blood-tissue partition coefficients is often complicated, time-consuming, and relatively expensive, so developing in vitro systems that approximate in vivo ones is desirable. We have determined such systems for tissues such as brain, muscle, liver, lung, kidney, heart, skin, and fat.

RESULTS

Several good (p < 0.05) blood-tissue partition coefficient models were developed using a single water-solvent system. These include blood-brain, blood-lung, blood-heart, blood-fat, blood-skin, water-skin, and skin permeation. Many of these partition coefficients have multiple water-solvent systems that can be used as models. Several solvents-methylcyclohexane, 1,9-decadiene, and 2,2,2-trifluoroethanol-were common to multiple models and thus a single measurement can be used to estimate multiple blood-tissue partition coefficients. A few blood-tissue systems require a combination of two water-solvent partition coefficient measurements to model well (p < 0.01), namely: blood-muscle: chloroform and dibutyl ether, blood-liver: N-methyl-2-piperidone and ethanol/water (60:40) volume, and blood-kidney: DMSO and ethanol/water (20:80) volume.

CONCLUSION

In vivo blood-tissue partition coefficients can be easily estimated through water-solvent partition coefficient measurements.Graphical abstract:Predicted blood-brain barrier partition coefficients coloured by measured log BB value.

Progressive development in experimental models of transungual drug delivery of anti-fungal agents

Pre-clinical development comprises of different procedures that relate drug discovery in the laboratory for commencement of human clinical trials. Pre-clinical studies can be designed to recognize a lead candidate from a list to develop the procedure for scale-up, to choose the unsurpassed formulation, to determine the frequency, and duration of exposure; and eventually make the foundation of the anticipated clinical trial design. The foremost aim in the pharmaceutical research and industry is the claim of drug product quality throughout a drug's life cycle. The particulars of the pre-clinical development process for different candidates may vary; however, all have some common features. Typically in vitro, in vivo or ex vivo studies are elements of pre-clinical studies. Human pharmacokinetic in vivo studies are often supposed to serve as the 'gold standard' to assess product performance. On the other hand, when this general assumption is revisited, it appears that in vitro studies are occasionally better than in vivo studies in assessing dosage forms. The present review is compendious of different such models or approaches that can be used for designing and evaluation of formulations for nail delivery with special reference to anti-fungal agents.

The application of machine learning to the modelling of percutaneous absorption: an overview and guide

Machine learning (ML) methods have been applied to the analysis of a range of biological systems. This paper reviews the application of these methods to the problem domain of skin permeability and addresses critically some of the key issues. Specifically, ML methods offer great potential in both predictive ability and their ability to provide mechanistic insight to, in this case, the phenomena of skin permeation. However, they are beset by perceptions of a lack of transparency and, often, once a ML or related method has been published there is little impetus from other researchers to adopt such methods. This is usually due to the lack of transparency in some methods and the lack of availability of specific coding for running advanced ML methods. This paper reviews critically the application of ML methods to percutaneous absorption and addresses the key issue of transparency by describing in detail - and providing the detailed coding for - the process of running a ML method (in this case, a Gaussian process regression method). Although this method is applied here to the field of percutaneous absorption, it may be applied more broadly to any biological system.

A survey of manufacturing and handling practices for monoclonal antibodies by pharmacy, nursing and medical personnel

INTRODUCTION

There is a paucity of data available to assess the occupational health and safety risk associated with exposure to monoclonal antibodies. Industry standards and published guidelines are conflicting or outdated. Guidelines offer contrary recommendations based on an array of methodological approaches. This survey aimed to describe current practices, beliefs and attitudes relating to the handling of monoclonal antibodies by Australian medical, nursing and pharmacy clinicians.

METHODS

An electronic survey was distributed between June and September 2013. Respondents were surveyed on three focus areas: institutional guideline availability and content, current practices and attitudes. Demographic data relating to respondent and primary place of practice were also collected.

RESULTS

A total of 222 clinicians completed the survey, with representation from all targeted professional groups and from a variety of geographic locations. 92% of respondents reported that their institution prepared or administered monoclonal antibodies, with 87% specifically handling anti-cancer monoclonal antibodies. Monoclonal antibodies were mostly prepared onsite (84-90%) and mostly within pharmacy clean-rooms (75%) and using cytotoxic cabinets (61%). 43% of respondents reported access to institutional monoclonal antibody handling guidelines with risk reduction strategies including training and education (71%), spill and waste management (71%), procedures for transportation (57%) and restricted handling (50%). Nurses had a stronger preference towards pharmacy manufacturing than both doctors and pharmacists for a range of clinical scenarios. 95% of all respondents identified that professional or regulatory body guidelines are an important resource when considering handling practices.

CONCLUSION

Monoclonal antibodies are most commonly handled according to cytotoxic drug standards and often in the absence of formal guidelines.