Skin Permeability Coefficient Research Articles

Percutaneous absorption of two bisphenol a analogues, BPAF and TGSA: Novel In vitro data from human skin

Bisphenol AF (BPAF) and TGSA are analogues of Bisphenol A (BPA). BPAF is used in polymer synthesis, while TGSA is applied in thermal papers. The EU classifies BPAF as toxic to reproduction and TGSA as a skin sensitizer. However, TGSA's other health effects remain unclear. BPAF contamination has been noted among electronic waste workers, and TGSA exposure is documented in various professions. Despite the significance of skin contact, data on skin permeation rates for BPAF and TGSA are limited. This study aimed to generate percutaneous absorption data for BPAF and TGSA following OECD guidelines.[14C]-labeled BPAF or TGSA was applied to human skin samples in vitro using Franz diffusion cells for 20 and 40 h, respectively. Key parameters such as steady-state flux, lag time, and skin permeability coefficient (Kp) were calculated. Furthermore, the distribution of the dose across different compartments, particularly within the skin, was evaluated at the conclusion of the experiment. Sequential strippings and epidermis-dermis separation were conducted for BPAF to predict the potential absorption of the remaining dose present within the skin.The permeability coefficients for BPAF and TGSA were found to be 1.9 E−03 and 1.6 E−03 cm/h, with 22% and 23% of the applied doses absorbed, respectively. Both chemicals are classified as "fast" penetrants based on their Kp values. These findings suggest that BPAF and TGSA are absorbed through the skin, highlighting potential occupational risks through dermal exposure. The new percutaneous absorption data will enhance the assessment of the occupational risks.

Artificial intelligence for skin permeability prediction: deep learning

Background and objective Researchers have put in significant laboratory time and effort in measuring the permeability coefficient (Kp) of xenobiotics. To develop alternative approaches to this labour-intensive procedure, predictive models have been employed by scientists to describe the transport of xenobiotics across the skin. Most quantitative structure-permeability relationship (QSPR) models are derived statistically from experimental data. Recently, artificial intelligence-based computational drug delivery has attracted tremendous interest. Deep learning is an umbrella term for machine-learning algorithms consisting of deep neural networks (DNNs). Distinct network architectures, like convolutional neural networks (CNNs), feedforward neural networks (FNNs), and recurrent neural networks (RNNs), can be employed for prediction. Methods In this project, we used a convolutional neural network, feedforward neural network, and recurrent neural network to predict skin permeability coefficients from a publicly available database reported by Cheruvu et al. The dataset contains 476 records of 145 chemicals, xenobiotics, and pharmaceuticals, administered on the human epidermis in vitro from aqueous solutions of constant concentration either saturated in infinite dose quantities or diluted. All the computations were conducted with Python under Anaconda and Jupyterlab environment after importing the required Python, Keras, and Tensorflow modules. Results We used a convolutional neural network, feedforward neural network, and recurrent neural network to predict log kp. Conclusion This research work shows that deep learning networks can be successfully used to digitally screen and predict the skin permeability of xenobiotics.

Mitragyna speciosa ethanolic extract: Extraction, anti-inflammatory, cytotoxicity, and transdermal delivery assessments

This study aimed to investigate the efficiency of extraction procedures for Mitragyna speciosa Korth (M. speciosa) as well as the anti-inflammatory, cytotoxicity, and transdermal delivery potential of M. speciosa ethanolic extract. Extraction of M. speciosa leaves was conducted using three different methods: maceration, ultrasonic-assisted extraction (UAE), and UAE with maceration. The extraction yields obtained were 9.3–23.1% with a mitragynine content of 7.9–10.2%. Mitragynine remaining of M. speciosa extracts was greater than 97% after 30-d storage at various conditions. Cytotoxicity study towards various skin cells reveals that cell growth half inhibitory concentrations (IC50) of M. speciosa extract ranged from 1.4 ± 0.0 to 2.5 ± 0.2 mg/mL. M. speciosa extract exhibited dose-dependent inhibitory effects on nitric oxide production (IC50 = 147.8 ± 9.0 µg/mL) and suppressed pro-inflammatory cytokine expression levels. Ex vivo assessment using porcine ear skin reveals that skin permeation of mitragynine from M. speciosa extract was restricted with permeation flux ranging from 0.4 ± 0.1 to 11.6 ± 1.1 µg·cm−2·h−1 and skin deposition at 24 h ranged from 8.7 ± 2.6 to 60.5 ± 16.2 µg·cm−2. Vehicle composition and lipophilicity were found to be determinants of mitragynine permeation. The mixture of hydrophilic chemical enhancers—propylene glycol and diethylene glycol monoethyl ether—as M. speciosa extract vehicle yielded the highest skin permeability coefficient of mitragynine. These findings offer valuable information that can be utilized for the transdermal and/or topical product development of mitragynine and M. speciosa extract.

Effect of Receptor Solution in Studies of In Vitro Permeation Test (IVPT)

In Vitro Permeation Test (IVPT) is commonly used to evaluate skin penetration of chemicals and performance of dermatological products. For a permeant with low aqueous solubility, an additive that is expected not to alter the skin barrier can be used in the receptor solution to improve permeant solubility. The objective of this study was to (a) evaluate the effects of these additives in IVPT receptor solution on skin permeability of model permeants and skin electrical resistance and (b) determine the solubility of the permeants in these receptor solutions. Bovine serum albumin (BSA), 2-hydroxypropyl-beta-cyclodextrin (HPCD), ethanol, nonionic surfactant Brij-98, and propylene glycol were the additives, and phosphate buffered saline (PBS) was the control. Steady-state skin permeability coefficients and resistances were determined. The receptor solutions examined in this study did not cause a significant increase in skin permeability or decrease in resistance (less than 40 % changes) except 25 % ethanol. The receptor solution containing 25 % ethanol induced an approximately twofold average increase in skin permeability and reduced skin electrical resistance by approximately threefold. The receptor solution of 2.5 % HPCD provided the highest levels of solubility for the model lipophilic permeants, while 0.2 % Brij-98 and 5 % ethanol showed the lowest solubility enhancement from those in PBS.

Evaluation of selected quantitative structure permeability relationship (QSPR) based mathematical models for the prediction of skin permeability of Camellia sinensis (tea) compounds

Background: Skin permeability coefficient (logKp) is a major determinant for topical drugs. In vitro and ex vivo determination of logKp is expensive, time and labour intensive, and difficult to apply to large databases. QSPR models derived from statistical correlation between descriptors of the compounds with the in vitro or ex vivo permeation data, are therefore used extensively. Vast number of QSPR equations makes the selection of a particular equation to screen a database, difficult choice. Objective: This study has evaluated common descriptor based equations for selection of the best suitable equation for screening phytochemical library of Camellia sinensis. Methods: Seven QSPR based models were used to estimate and compare the logKp of tea compounds. The best method was selected with respect to the gold standard logKp. Result: The model of Potts and Guy showed close proximation with the gold standard logKp and had highest association along with least RMSE value and least deviation. According to this method, approximately, 37.38%, 35.35% and 27.27% of the tea compounds were found to have high, good and poor logKp respectively. Conclusion: Potts and Guy equation can be effectively used to screen the phytochemical library of Camellia sinensis. This study has potential application in the field of topical medicine and cosmetics.

An examination of published datasets of skin permeability and partition coefficients

Permeability and partition coefficients of the skin barrier are important for assessing dermal absorption, bioavailability, and safety of cosmetics and medicine. We use the Potts and Guy equation to analyse the dependence of skin permeability on the hydrophobicity of permeants and highlight the significant differences in published datasets. Correlations of solute partition to skin are examined to understand the likely causes of the differences in the skin permeability datasets. Recently published permeability datasets show weak correlation and low dependence on hydrophobicity. As expected, early datasets show good correlation with hydrophobicity due to the related derivation. The weaker correlation of later datasets cannot be explained by the partition to skin lipids. All the datasets of solute partition to skin lipid showed a similar correlation to hydrophobicity where the log-linear correlation coefficient of partition is almost the same of the log-linear coefficient of Potts and Guy equation. Weak correlation and dependence of the late permeability datasets with SC lipid/water partition and that they are significantly under predicted by the Potts and Guy equation suggests either additional non-lipid pathway at play or a weaker skin barrier property.

Immobilized Keratin HPLC Stationary Phase-A Forgotten Model of Transdermal Absorption: To What Molecular and Biological Properties Is It Relevant?

Chromatographic retention data collected on immobilized keratin (KER) or immobilized artificial membrane (IAM) stationary phases were used to predict skin permeability coefficient (log Kp) and bioconcentration factor (log BCF) of structurally unrelated compounds. Models of both properties contained, apart from chromatographic descriptors, calculated physico-chemical parameters. The log Kp model, containing keratin-based retention factor, has slightly better statistical parameters and is in a better agreement with experimental log Kp data than the model derived from IAM chromatography; both models are applicable primarily to non-ionized compounds.Based on the multiple linear regression (MLR) analyses conducted in this study, it was concluded that immobilized keratin chromatographic support is a moderately useful tool for skin permeability assessment.However, chromatography on immobilized keratin may also be of use for a different purpose-in studies of compounds' bioconcentration in aquatic organisms.

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.

Pharmacokinetic and toxicological in silco profiling of pluchine from the medicinal plant – Pluchea lanceolata

Background: Pluchea lanceolata belongs to the genus Pluchea (family: Asteraceae). The medicinal herb has been used for various ailments to prevent joint swelling in arthritic disorders, rheumatism, and other neurological-inflammatory disorders. Pluchine, which in our review was found to be a compound from P. Lanceolata, is explored for possible pharmacokinetic and toxicological properties by in silico computational predictive tools. Aims and Objectives: The aim of the study is to profile the pharmacokinetic, toxicological, and drug likeness scores of pluchine’s active principle using computational analysis and prediction tools. Materials and Methods: The authenticated and validated chemical structure of pluchine with its chemical formula will be extracted from standard web-based tools PubChem and ChemSpider. The two-dimensional to three-dimensional (3D) structure conversion will be processed with ChemSketchonline software; the 3D structure output will be processed further to be screened for molecular and pharmacokinetic properties for absorption, distribution, metabolism, and elimination, followed by toxicity profiling through AdmetSAR software. Results: Pluchine active principle from P. lanceolata had a predictive pharmacokinetic profile of human intestinal absorption of <30%, Human skin permeability coefficients (log k p) of pluchine were −6.75 cm/s, and the blood–brain barrier were predicted to be positive with a probability score of 0.65. Drug likeness lipinskiscore is positive with -0- violations. Acute oral toxicity testing for pluchine predicts it to be placed in category III with LD50 values >500 mg/kg but <5000 mg/kg. Conclusion: The pluchineactive principle from P. lanceolata is predicted to have a favorable pharmacokinetic and drug-like property profile for lead compound development.

Predicting skin permeability of pharmaceutical and cosmetic compounds using retention on octadecyl, cholesterol-bonded and immobilized artificial membrane columns

In this study, the retention on three types of columns, an immobilized artificial membrane (IAM), a cholesterol-bonded and an octadecyl (C18) column, was applied for the prediction of skin permeability. The first two columns are biomimicking ones, which have certain components of the skin bound to the stationary phase, and were applied in HPLC, while the sub-2 µm C18 column was studied in UHPLC because of its fast features. Fifty-eight compounds were analyzed applying different mobile-phase compositions, with varying percentages of organic modifier on every column, to extrapolate the retention factor to a theoretically purely aqueous mobile phase (log kw). The retention factors, along with two sets of theoretical molecular descriptors, were used to model the skin permeability coefficient (log Kp) using multiple linear regression (MLR) and partial least squares (PLS) regression modelling. Although the retention factors (log k) on the IAM column showed a better correlation with the skin permeability, the overall best model was obtained by applying a stepwise MLR approach on the UHPLC parameters combined with some theoretical descriptors. This model showed a good fit, and on top has potential to accurately predict skin permeability values. Furthermore, the UHPLC method has the advantage of being fast and can thus be classified as a high-throughput approach.

In Silico Prediction of Skin Permeability Using a Two-QSAR Approach.

Topical and transdermal drug delivery is an effective, safe, and preferred route of drug administration. As such, skin permeability is one of the critical parameters that should be taken into consideration in the process of drug discovery and development. The ex vivo human skin model is considered as the best surrogate to evaluate in vivo skin permeability. This investigation adopted a novel two-QSAR scheme by collectively incorporating machine learning-based hierarchical support vector regression (HSVR) and classical partial least square (PLS) to predict the skin permeability coefficient and to uncover the intrinsic permeation mechanism, respectively, based on ex vivo excised human skin permeability data compiled from the literature. The derived HSVR model functioned better than PLS as represented by the predictive performance in the training set, test set, and outlier set in addition to various statistical estimations. HSVR also delivered consistent performance upon the application of a mock test, which purposely mimicked the real challenges. PLS, contrarily, uncovered the interpretable relevance between selected descriptors and skin permeability. Thus, the synergy between interpretable PLS and predictive HSVR models can be of great use for facilitating drug discovery and development by predicting skin permeability.

IAM Chromatographic Models of Skin Permeation.

Chromatographic retention factor log kIAM obtained from IAM HPLC chromatography with buffered aqueous mobile phases and calculated molecular descriptors (surface area—Sa; molar volume—VM; polar surface area—PSA; count of freely rotable bonds—FRB; H-bond acceptor count—HA; energy of the highest occupied molecular orbital—EHOMO; energy of the lowest unoccupied orbital—ELUMO; and polarizability—α) obtained for a group of 160 structurally unrelated compounds were tested in order to generate useful models of solutes’ skin permeability coefficient log Kp. It was established that log kIAM obtained in the conditions described in this study is not sufficient as a sole predictor of the skin permeability coefficient. Simple put, potentially useful models based on log kIAM and readily available calculated descriptors, accounting for 85 to 91% of the total variability, were generated using Multiple Linear Regression (MLR).The models proposed in the study were tested on a group of 20 compounds with known experimental log Kp values.

RP-18 TLC and Computational Descriptors of Skin Permeability of Sunscreens

The relationships between the reversed-phase thin layer chromatographic retention parameters obtained on octadecyl-modified silica (RP-18) sorbent for mobile phases containing water and one of six water-miscible organic modifiers (acetone, methanol, acetonitrile, tetrahydrofurane, N,N-dimethylformamide, 1,4-dioxane) and skin permeability coefficients were studied for a group of 21 cosmetic raw materials, mainly organic sunscreens and preservatives. The correlations between the skin permeability coefficients log K_d calculated in silico using EpiSuite software and the RP-18 thin layer chromatographic retention parameters are mostly linear, especially for compounds of lower-to-medium lipophilicity. It was established that skin permeability coefficient models based on retention parameters collected for mobile phases containing acetone or dioxane (75% v/v), proposed for structurally unrelated cosmetic raw materials are also applicable to other actives, as shown using a test set of compounds whose in vivo log K_d data are available. Skin permeability models developed in this study have the benefit of being based on easily obtained, chromatographic descriptors and their applicability extends beyond cosmetic chemistry.

Evaluating micellar liquid chromatographic methods on octadecyl particle-based and monolithic columns to predict the skin permeation of drug and cosmetic molecules

A micellar liquid chromatographic method was developed to assist in the modeling of the skin permeability of pharmaceutical and cosmetic compounds. The composition of the mobile phase was determined by means of a two-factor central composite design, after which it was tested on both a particle-based and monolithic column. The latter provided the opportunity to increase the flow rate from 1 to 8 mL/min without reaching too high backpressures. The micellar conditions allowed analyzing a large test set of compounds with diverse characteristics with just one mobile-phase composition. The obtained experimental chromatographic descriptors besides two sets of theoretical molecular descriptors were used to model the skin permeability coefficient log Kp, applying multiple linear regression and partial least squares regression approaches. The micellar method on the monolithic column provided useful models with similar or even slightly better performance parameters than the method on the particle-based column. Furthermore, a much faster analysis can be achieved when applying a flow rate of 8 mL/min, making the micellar monolithic method ideal to estimate skin permeability.

Permeation, stability and acute dermal irritation of miroestrol and deoxymiroestrol from Pueraria candollei var. mirifica crude extract loaded transdermal gels

In this study, permeation behaviors and chemical stability of miroestrol and deoxymiroestrol from Pueraria candollei var. mirifica (PM), Thai traditional medicine, crude extract containing transdermal gels were firstly evaluated. Three different PM extract containing gels were formulated, including hydroalcoholic and microemulsion gels using carbomer, and silicone gel using silicone elastomer. In vitro permeation through porcine ear skin demonstrated that the flux and 24 h cumulative permeation of miroestrol and deoxymiroestrol were in the order of hydroalcoholic > silicone > microemulsion gels. Hydroalcoholic gel provided the highest partition coefficient from gel onto skin, and thus the skin permeability coefficient. After 24 h permeation, no miroestrol and deoxymiroestrol remained deposited in the skin. Accelerated study using heating-cooling revealed insignificant difference between the remaining percentages of miroestrol and deoxymiroestrol in aqueous and non-aqueous based gels. Long-term stability study showed that miroestrol contents remained constant for 90 d and 30 d under 5 ± 3 °C and 30 ± 2 °C, 75 ± 5%RH, respectively; whereas the percentage of deoxymiroestrol decreased significantly after 30 d storage, irrespective of storage conditions. Acute dermal irritation test on New Zealand White rabbits showed that PM hydroalcoholic gels were non-irritant, with no signs of erythema or oedema.

Enhanced permeability and photoprotective potential of optimized p-coumaric acid-phospholipid complex loaded gel against UVA mediated oxidative stress.

Photo-oxidative skin damage is mainly caused by the UV-A radiation of the sun. Synthetic sunscreens used to counter this acts mostly on the superficial skin layer and possess serious side effects. P-coumaric acid (PCA) is a UV-A protective plant phenolic having quick diffusion and distribution in superficial skin layers limiting its application as herbal sunscreen. The present study was designed to formulate an optimized phospholipid complex of PCA (PCAPC) through response surface methodology to enhance its skin permeation to deeper skin layers providing protection against photo-oxidative stress. PCAPC was characterized by FT-IR, DTA, PXRD, TEM, zeta potential etc. PCAPC was then incorporated into a gel formulation (PCAPC-GE) to facilitate its transdermal delivery. Physicochemical properties of the gel were assessed by pH, homogeneity, rheology, spreadability etc. In-vitro SPF and UVA-PF of the gel was evaluated and compared with conventional gel (PCA-GE). Ex-vivo skin permeation flux, permeability coefficient, skin deposition and dermatokinetic analysis were carried out to measure the rate and level of skin permeation. This was accompanied by in-vivo evaluation of PCAPC-GE and PCA-GE in the experimental rat model by measuring the various oxidative stress markers such as superoxide dismutase, catalase etc. PCAPC-GE provided high SPF and UVA-PF value compared to PCA-GE. The physicochemical parameters were suitable for transdermal application. PCAPC-GE enhanced the permeation rate of PCA by almost 6 fold compared to PCA-GE. Besides, a significant reduction of UV-A induced oxidative stress biomarkers were observed for PCAPC-GE. Thus, the PCAPC-GE may be an effective alternative of synthetic sunscreens due to its enhanced permeation and protection against UVA-induced oxidative stress.

Reassessment of the experimental skin permeability coefficients of polycyclic aromatic hydrocarbons and organophosphorus pesticides

Human exposure to polycyclic aromatic hydrocarbons (PAHs) and organophosphorus pesticides (OPPs) by dermal route is a continuing concern in environmental and occupational toxicology. Diverse authors have measured in vitro the absorption flux and permeability coefficient (kP) of those compounds delivered on skin surface using volatile solvents. However, there isn’t a harmonized method to obtain kP when the test substance is deposited on the skin as a solid. Consequently, varied experimental kPs have been reported for PAHs and OPPs, most in clear disagreement with the values predicted by well-established mathematical models. In this work, we collected the permeation fluxes reported for these toxicants through human skin and calculated the (aqueous) kPs using a method based on the maximum flux and water solubility. The reanalyzed fluxes and recalculated kPs show improved consistency between the different experimental works and mathematical models. Notably, the recalculated kP of benzo[a]pyrene, among others, was approximately 100 times higher than it had been previously considered. Suggestions are given to generalize the method in studies with other solvent-deposited toxicants and drugs.

Development and evaluation of two-parameter linear free energy models for the prediction of human skin permeability coefficient of neutral organic chemicals

The experimental values of skin permeability coefficients, required for dermal exposure assessment, are not readily available for many chemicals. The existing estimation approaches are either less accurate or require many parameters that are not readily available. Furthermore, current estimation methods are not easy to apply to complex environmental mixtures. We present two models to estimate the skin permeability coefficients of neutral organic chemicals. The first model, referred to here as the 2-parameter partitioning model (PPM), exploits a linear free energy relationship (LFER) of skin permeability coefficient with a linear combination of partition coefficients for octanol–water and air–water systems. The second model is based on the retention time information of nonpolar analytes on comprehensive two-dimensional gas chromatography (GC × GC). The PPM successfully explained variability in the skin permeability data (n = 175) with R2 = 0.82 and root mean square error (RMSE) = 0.47 log unit. In comparison, the US-EPA’s model DERMWIN™ exhibited an RMSE of 0.78 log unit. The Zhang model—a 5-parameter LFER equation based on experimental Abraham solute descriptors (ASDs)—performed slightly better with an RMSE value of 0.44 log unit. However, the Zhang model is limited by the scarcity of experimental ASDs. The GC × GC model successfully explained the variance in skin permeability data of nonpolar chemicals (n = 79) with R2 = 0.90 and RMSE = 0.23 log unit. The PPM can easily be implemented in US-EPA’s Estimation Program Interface Suite (EPI Suite™). The GC × GC model can be applied to the complex mixtures of nonpolar chemicals.

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

Several chromatographic parameters (RM0 and S obtained from RP-18 TLC with methanol—pH 7.4 phosphate buffer mobile phases by extrapolation to zero concentration of methanol; Rf and RM 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—MW; molar volume—VM; 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—ET; binding energy—Eb; hydration energy—Eh; energy of the highest occupied molecular orbital—EHOMO; energy of the lowest unoccupied orbital—ELUMO; electronic energy—Ee; surface area—Sa; octanol-water partition coefficient—log P; dipole moment—DM; refractivity—R, polarizability—α) and their combinations (Rf/PSA, RM/MW, RM/VM) were tested in order to generate useful models of solutes’ skin permeability coefficient log Kp. It was established that neither RM0 nor S obtained in the conditions used in this study is a good predictor of the skin permeability coefficient. The chromatographic parameters Rf and Rf/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 RM (RM, RM/MW, RM/VM) as independent variables in log Kp models proved that RM/VM is the most suitable descriptor belonging to this group. In a search for a reliable log Kp model based on this descriptor two possibilities were considered: a relatively simple model based on 5 independent variables: (N+O), log D, RM/VM, ET and Eh and a more complex one, involving also Eb, MW and PSA.

Curcumin-Loaded Self-Microemulsifying Gel for Enhancing Wound Closure

Introduction: Wound healing is a process in which damaged cutaneous tissues are repaired and is a dynamic physiological interaction involving several types of cells, tissues, and proteins. Compared with typical treatments, specifically in terms of multifunctional properties, bioactive drug-loaded wound dressing in a controlled and sustained delivery system is an advanced tool that significantly improves wound healing. Curcumin substantially enhances wound healing and prevents oxidative damage. However, the effects of this compound on improving wound healing are limited by its aqueous solubility, poor tissue absorption, and rapid metabolism. Hence, the current study aimed to investigate the therapeutic effect of curcumin-loaded self-microemulsifying gel on wound healing. Methods: Ex vivo permeation studies of the skin of BALB/c mice were performed using a diffusion cell sampling system. The in vivo therapeutic effect was investigated with a full-thickness wound model. Two 6-mm full-thickness circular wounds were created on the back of the mice via punch biopsy. Then, they received different topical gels for 12 days to enhance wound closure. Results: The curcumin-loaded self-microemulsifying gel had higher skin flux, cumulative amount, and permeability coefficient than the commercial gels. In addition, it enhanced wound healing. Conclusions: This is the first study that utilized self-microemulsifying gel loaded with curcumin as a delivery system for wound healing. However, the effect of this delivery system on wound healing or skin disease treatment should be further investigated.