Physiologically based modelling of dermal absorption and kinetics of consumer-relevant chemicals: A case study with exposure to bisphenol A from thermal paper.

Bisphenol A (BPA) is one of the best studied industrial chemicals in terms of exposure, toxicity, and toxicokinetics. This renders it an ideal candidate to exploit the recent advancements in physiologically based pharmacokinetic (PBPK) modelling to support risk assessment of BPA specifically, and of other consumer-relevant hazardous chemicals in general. Using the exposure from thermal paper as a case scenario, this study employed the multi-phase multi-layer mechanistic dermal absorption (MPML MechDermA) model available in the Simcyp® Simulator to simulate the dermal toxicokinetics of BPA at local and systemic levels. Sensitivity analysis helped to identify physicochemical and physiological factors influencing the systemic exposure to BPA. The iterative modelling process was as follows: (i) development of compound files for BPA and its conjugates, (ii) setting-up of a PBPK model for intravenous administration, (iii) extension for oral administration, and (iv) extension for exposure via skin (i.e., hand) contact. A toxicokinetic study involving hand contact to BPA-containing paper was used for model refinement. Cumulative urinary excretion of total BPA had to be employed for dose reconstruction. PBPK model performance was verified using the observed serum BPA concentrations. The predicted distribution across the skin compartments revealed a depot of BPA in the stratum corneum (SC). These findings shed light on the role of the SC to act as temporary reservoir for lipophilic chemicals prior to systemic absorption, which inter alia is relevant for the interpretation of human biomonitoring data and for establishing the relationship between external and internal measures of exposure.

Artificial Intelligence That Predicts Sensitizing Potential of Cosmetic Ingredients with Accuracy Comparable to Animal and In Vitro Tests-How Does the Infotechnomics Compare to Other "Omics" in the Cosmetics Safety Assessment?

The aim of the current study was to develop an in silico model to predict the sensitizing potential of cosmetic ingredients based on their physicochemical characteristics and to compare the predictions with historical animal data and results from "omics"-based in vitro studies. An in silico model was developed with the use of WEKA machine learning software fed with physicochemical and structural descriptors of haptens and trained with data from published epidemiological studies compiled into estimated odds ratio (eOR) and estimated attributable risk (eAR) indices. The outcome classification was compared to the results of animal studies and in vitro tests. Of all the models tested, the best results were obtained for the Naive Bayes classifier trained with 24 physicochemical descriptors and eAR, which yielded an accuracy of 86%, sensitivity of 80%, and specificity of 90%. This model was subsequently used to predict the sensitizing potential of 15 emerging and less-studied haptens, of which 7 were classified as sensitizers: cyclamen aldehyde, N,N-dimethylacrylamide, dimethylthiocarbamyl benzothiazole sulphide, geraniol hydroperoxide, isobornyl acrylate, neral, and prenyl caffeate. The best-performing model (NaiveBayes eAR, 24 parameters), along with an alternative model based on eOR (Random Comittee eOR, 17 parameters), are available for further tests by interested readers. In conclusion, the proposed infotechnomics approach allows for a prediction of the sensitizing potential of cosmetic ingredients (and possibly also other haptens) with accuracy comparable to historical animal tests and in vitro tests used nowadays. In silico models consume little resources, are free of ethical concerns, and can provide results for multiple chemicals almost instantly; therefore, the proposed approach seems useful in the safety assessment of cosmetics.

Utilization of mechanistic modelling and simulation to analyse fenspiride proarrhythmic potency - Role of physiological and other non-drug related parameters.

WHAT IS KNOWN AND OBJECTIVE: Fenspiride, a drug that had been used for decades for the treatment of respiratory diseases, was recently withdrawn from the market due to the potential risk of QT prolongation and proarrhythmia. This is the first such withdrawal for many years and hence poses a question whether such risk could have been predicted and to what degree non-drug-specific parameters play a role in the reported QT prolongation and cases of TdP. The study aim was to test various 'what-if' scenarios to assess the influence of age, gender, heart rate, and plasma potassium concentration on QT interval prolongation due to various doses of fenspiride with the use of mechanistic mathematical modelling. METHODS: Concentration-time profiles were simulated with the use of a PBPK model developed based on published physico-chemical data, data from in vitro ADME experiments, and in vivo PK study results. Pharmacodynamic effect, that is, drug-triggered pseudoECG signal modification was simulated using a biophysically detailed model of human cardiac myocytes. Analysis of the qNet metric was also performed to classify proarrhythmic risk related to fenspiride. RESULTS: In the simulation study, arrhythmia was not observed even in the 'what-if' scenarios with extreme exposure, age, heart rate, and plasma potassium concentration. The qNet metric value positioned fenspiride in the intermediate risk class. WHAT IS NEW AND CONCLUSION: It can be hypothesized that the clinically observed arrhythmia cases were not directly caused by fenspiride alone but a combination of multiple factors, including comedications.

How circadian variability of the heart rate and plasma electrolytes concentration influence the cardiac electrophysiology - model-based case study.

The circadian rhythm of cardiac electrophysiology is dependent on many physiological and biochemical factors. Provided, that models describing the circadian patterns of cardiac activity and/or electrophysiology which have been verified to the acceptable level, modeling and simulation can give answers to many of heart chronotherapy questions. The aim of the study was to assess the performance of the circadian models implemented in Cardiac Safety Simulator v 2.2 (Certara, Sheffield, UK) (CSS), as well as investigate the influence ofcircadian rhythms on the simulation results in terms of cardiac safety. The simulations which were run in CSS accounted for inter-individual and intra-individual variability. Firstly, the diurnal variations in QT interval length in a healthy population were simulated accounting for heart rate (HR) circadian changes alone, or with concomitant diurnal variations of plasma ion concentrations. Next, tolterodine was chosen as an exemplary drug for PKPD modelling exercise to assess the role of circadian rhythmicity in the prediction of drug effects on QT interval. The results of the simulations were in line with clinical observations, what can serve as a verification of the circadian models implemented in CSS. Moreover, the results have suggested that the circadian variability of the electrolytes balance is the main factor influencing QT circadian pattern. The fluctuation of ion concentration increases the intra-subject variability of predicted drug-triggered QT corrected for HR (QTc) prolongation effect and, in case of modest drug effect on QTc interval length, allows to capture this effect.

Magnetic Core-Shell Molecularly Imprinted Nano-Conjugates for Extraction of Antazoline and Hydroxyantazoline from Human Plasma-Material Characterization, Theoretical Analysis and Pharmacokinetics.

The aim of this study was to develop magnetic molecularly imprinted nano-conjugate sorbent for effective dispersive solid phase extraction of antazoline (ANT) and its metabolite, hydroxyantazoline (ANT-OH) in analytical method employing liquid chromatography coupled with mass spectrometry method. The core-shell material was characterized in terms of adsorption properties, morphology and structure. The heterogeneous population of adsorption sites towards ANT-OH was characterized by two Kd and two Bmax values: Kd (1) = 0.319 µg L-1 and Bmax (1) = 0.240 µg g-1, and Kd (2) = 34.6 µg L-1 and Bmax (2) = 5.82 µg g-1. The elemental composition of magnetic sorbent was as follows: 17.55, 37.33, 9.14, 34.94 wt% for Si, C, Fe and O, respectively. The extraction protocol was optimized, and the obtained results were explained using theoretical analysis. Finally, the analytical method was validated prior to application to pharmacokinetic study in which the ANT was administrated intravenously to three healthy volunteers. The results prove that the novel sorbent could be useful in extraction of ANT and ANT-OH from human plasma and that the analytical strategy could be a versatile tool to explain a potential and pharmacological activity of ANT and ANT-OH.

Characterization of In Vitro and In Vivo Metabolism of Antazoline Using Liquid Chromatography-Tandem Mass Spectrometry.

Antazoline (ANT) was recently shown to be an effective and safe antiarrhythmic drug in the termination of atrial fibrillation. However, the drug is still not listed in clinical guidelines. No data on ANT metabolism in humans is available. We used liquid chromatography coupled with tandem mass spectrometry to identify and characterize metabolites of ANT. We analyzed plasma of volunteers following a single intravenous administration of 100 mg of ANT mesylate and in in vitro cultures of human hepatocytes. We revealed that ANT was transformed into at least 15 metabolites and we investigated the role of cytochrome P450 isoforms. CYP2D6 was the main one involved in the fast metabolism of ANT. The biotransformation of ANT by CYP2C19 was much slower. The main Phase I metabolite was M1 formed by the removal of phenyl and metabolite M2 with hydroxyl in the para position of phenyl. Glucuronidation was the leading Phase II metabolism. Further study on pharmacokinetics of the metabolites would allow us to better understand the activity profile of ANT and to predict its potential clinical applications. Ultimately, further investigation of the activity profile of the new hydroxylated M2 metabolite of ANT might result in an active substance with a different pharmacological profile than the parent molecule, and potentially a new drug candidate.

Drug interaction at hERG channel: In vitro assessment of the electrophysiological consequences of drug combinations and comparison against theoretical models.

Drugs carry a proarrhythmic risk, which gets even greater when they are used in combination. In vitro assessment of the proarrhythmic potential of drugs is limited to one compound and thus neglects the potential of drug-drug interactions, including those involving active metabolites. Here we present the results of an in vitro study of potential drug-drug interactions at the level of the hERG channel for the combination of up to three compounds: loratadine, desloratadine and ketoconazole. Experiments were performed at room temperature on an automated patch-clamp device CytoPatch 2, with the use of heterogeneously, stably transfected HEK cells. Single drugs, pairs and triplets were used. The results provided as the inhibition of the IKr current for pairs were compared against the calculated theoretical interaction. Models applied to calculate the combined effect of inhibitory actions of simultaneously given drugs include: (1) simple additive model with a maximal inhibition limit of 1 (all channels blocked in 100%); (2) Bliss independence; and (3) Loewe additivity. The observed IC50 values for loratadine, desloratadine and ketoconazole were 5.15, 1.95 and 0.74 µm respectively. For the combination of drugs tested in pairs, the effect was concentration dependent. In lower concentrations, the synergistic effect was observed, while for the highest tested concentrations it was subadditive. To triple the effect, it was subadditive regardless of concentrations. The square root of sum of squares of differences between the observed and predicted total inhibition was calculated to assess the theoretical interaction models. For most of the drugs, the allotopic model offered the best fit.

Drug-physiology interaction and its influence on the QT prolongation-mechanistic modeling study.

The current study is an example of drug-disease interaction modeling where a drug induces a condition which can affect the pharmacodynamics of other concomitantly taken drugs. The electrophysiological effects of hypokaliemia and heart rate changes induced by the antiasthmatic drugs were simulated with the use of the cardiac safety simulator. Biophysically detailed model of the human cardiac physiology-ten Tusscher ventricular cardiomyocyte cell model-was employed to generate pseudo-ECG signals and QTc intervals for 44 patients from four clinical studies. Simulated and observed mean QTc values with standard deviation (SD) for each reported study point were compared and differences were analyzed with Student's t test (α = 0.05). The simulated results reflected the QTc interval changes measured in patients, as well as their clinically observed interindividual variability. The QTc interval changes were highly correlated with the change in plasma potassium both in clinical studies and in the simulations (Pearson's correlation coefficient > 0.55). The results suggest that the modeling and simulation approach could provide valuable quantitative insight into the cardiological effect of the potassium and heart rate changes caused by electrophysiologically inactive, non-cardiological drugs. This allows to simulate and predict the joint effect of several risk factors for QT prolongation, e.g., drug-dependent QT prolongation due to the ion channels inhibition and the current patient physiological conditions.

Enhanced QSAR models for drug-triggered inhibition of the main cardiac ion currents.

The currently changing cardiac safety testing paradigm suggests, among other things, a shift towards using in silico models of cellular electrophysiology and assessment of a concomitant block of multiple ion channels. In this study, a set of four enhanced QSAR models have been developed: for the rapid delayed rectifying potassium current (IKr), slow delayed rectifying potassium current (IKs), peak sodium current (INa) and late calcium current (ICaL), predicting ion currents changes for the specific in vitro experiment from the 2D structure of the compounds. The models are a combination of both in vitro study parameters and physico-chemical descriptors, which is a novel approach in drug-ion channels interactions modeling. Their predictive power assessed in the enhanced, more demanding than standard procedure, 10-fold cross validation was reasonably high. Rough comparison with published pure in silico hERG interaction models shows that the quality of the model predictions does not differ from other models available in the public domain, however, it takes its advantage in accounting for inter-experimental settings variability. Developed models are implemented in the Cardiac Safety Simulator, a commercially available platform enabling the in vitro-in vivo extrapolation of the drugs proarrhythmic effect and ECG simulation. A more comprehensive assessment of the effects of the compounds on ion channels allows for making more informed decisions regarding the risk - and thus avoidance - of exclusion of potentially safe and effective drugs.

How in vitro influences in silico utilized for the prediction of in vivo - pilot study of the drug-induced pro-arrhythmic potency prediction.

The current drug cardiac safety risk assessment paradigm is about to be changed. The discussed modifications cover clinical as well as pre-clinical sides. As for the latter, the pre-clinical assessment, it is planned to be based on the analysis of the drug-triggered multiple ion currents inhibition. Considering the variability in the in vitro patch clamp studies results, it would be of benefit to assess how these apparatus- and protocol-dependent differences influence the risk prediction and, eventually, the decision making. Four compounds, namely dextromethorphan, ketoconazole, terfenadine, and quinidine were screened for hERG inhibition with an automated patch clamp apparatus (CytoPatch(TM)2). The results were then compared against the literature published data, and after being complemented with information about other current inhibitions and effective therapeutic plasma concentration, utilized for the in silico based safety assessment. Two endpoints were used: (1) the concentration dependent potential to induce early afterdepolarizations in the simulated action potential and (2) the arrhythmia-like disruption in the simulated pseudo-ECG signals. Data analysis results prove that IC50 values, describing the inhibition potential, significantly differ among studies, and the choice of input data can greatly influence the in silico based safety assessment and thus the decision making process.

Computer-based prediction of the drug proarrhythmic effect: problems, issues, known and suspected challenges.

It is likely that computer modelling and simulations will become an element of comprehensive cardiac safety testing. Their role would be primarily the integration and the interpretation of previously gathered data. There are still unanswered questions and issues which we list and describe below. They include sources of data used for the development of the models as well as data utilized as input information, which can come from the in vitro studies and the quantitative structure-activity relationship models. The pharmacokinetics of the drugs in question play a crucial role as their active concentration should be considered, yet the question remains where is the right place to assess it. The pharmacodynamic angle includes complications coming from multiple drugs (i.e. active metabolites) acting in parallel as well as the type of interaction with (potentially) multiple affected channels. Once established, the model and the methodology of its use should be further validated, optimistically against individual data reported at the clinical level as the physiological, anatomical, and genetic parameters play a crucial role in the drug-triggered arrhythmia induction. All the abovementioned issues should be at least considered and-hopefully-resolved, to properly utilize the mathematical models for a cardiac safety assessment.

Can 3D Printed Tablets Be Bioequivalent and How to Test It: A PBPK Model Based Virtual Bioequivalence Study for Ropinirole Modified Release Tablets.

As the field of personalized dosing develops, the pharmaceutical manufacturing industry needs to offer flexibility in terms of tailoring the drug release and strength to the individual patient's needs. One of the promising tools which have such capacity is 3D printing technology. However, manufacturing small batches of drugs for each patient might lead to huge test burden, including the need to conduct bioequivalence trials of formulations to support the change of equipment or strength. In this paper we demonstrate how to use 3D printing in conjunction with virtual bioequivalence trials based on physiologically based pharmacokinetic (PBPK) modeling. For this purpose, we developed 3D printed ropinirole formulations and tested their bioequivalence with the reference product Polpix. The Simcyp simulator and previously developed ropinirole PBPK model were used for the clinical trial simulations. The Weibull-fitted dissolution profiles of test and reference formulations were used as inputs for the model. The virtual bioequivalence trials were run using parallel design. The study power of 80% was reached using 125 individuals. The study demonstrated how to use PBPK modeling in conjunction with 3D printing to test the virtual bioequivalence of newly developed formulations. This virtual experiment demonstrated the bioequivalence of one of the newly developed formulations with a reference product available on a market.

Slow delayed rectifying potassium current (IKs ) - analysis of the in vitro inhibition data and predictive model development.

The excitable cell membranes contain ion channels that allow the ions passage through the specific pores via a passive process. Assessment of the inhibition of the IKr (hERG) current is considered to be the main target during the drug development process, although there are other ionic currents for which drug-triggered modification can either potentiate or mask hERG channel blockade. Information describing the results of in vitro studies investigating the chemical-IKs current interactions has been developed in the current study. Based on the publicly available data sources, 145 records were collected. The final list of publications consists of 64 positions and refers to 106 different molecules connected with IKs current inhibition, with at least one IC50 value measured. Ultimately, 98 of the IC50 values expressed as absolute values were gathered. For 36 records the IC50 was expressed as a relative value. For the 11 remaining records, the inhibition was not clearly expressed. Based on the collected data the predictive models for the IC50 estimation were developed with the use of various algorithms. The extended Quantitative Structure-Activity Relationships (QSAR) methodology was applied and the in vitro research settings were included as independent variables, apart from the physico-chemical descriptors calculated with the use of the Marvin Calculator Plugins. The root mean squared error and normalized root mean squared error values for the best model (an expert system based on two independent artificial neural networks) were 0.86 and 14.04%, respectively. The model was further built into the ToxComp system, the ToxIVIVE tool specialized for cardiotoxicity assessment of drugs.

3D printing combined with biopredictive dissolution and PBPK/PD modeling optimization and personalization of pharmacotherapy: Are we there yet?

Precision medicine requires selecting the appropriate dosage regimen for a patient using the right drug, at the right time. Model-Informed Precision Dosing (MIPD) is a concept suggesting utilization of model-based prediction methods for optimizing the treatment benefit-harm balance, based on individual characteristics of the patient, disease, treatment method, and other factors. Here, we discuss a theoretical workflow comprising several elements, beginning from the physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models, through 3D printed tablets with the model proposed dose, information range and flow, and the patient themselves. We also describe each of these elements, and the connection between them, highlighting challenges and potential obstacles.

Data on ADME parameters of bisphenol A and its metabolites for use in physiologically based pharmacokinetic modelling.

The paper presents the collection of physicochemical parameters of bisphenol A (BPA) and its sulfate (BPAS) and glucuronide (BPAG) conjugates, accompanied by data characterizing their absorption, distribution, metabolism and excretion (ADME) behavior following oral administration of BPA. The data were collected from open literature sources and publicly available databases. Additionally, data calculated by using the MarvinSketch 18.30.0 software or predicted by relevant QSAR models built in Simcyp® Simulator were also used. All data were analysed and are fit for purpose if necessary to ensure a reliable prediction of pharmacokinetics of BPA and its conjugates. The data selection process and reasoning for fitting is provided to allow critical assessment and to ensure data transparency. Finally, the sensitivity analysis was performed to assess the influence of the selected parameters on the PBPK model predictions.

BDTcomparator: a program for comparing binary classifiers.

SUMMARY: The BDTcomparator facilitates the selection of the best performing binary classification model or binary diagnostic procedure from the many possible alternatives by comparing their predictions with a known output, measured with the use of a system recognized as the gold standard. The program calculates the estimates of accuracy, sensitivity, specificity, predictive values and diagnostic likelihood ratios along with appropriate confidence intervals. Furthermore, all pairwise comparisons with respect to the above-mentioned measures are calculated. The formatted results can be exported to a text-file. AVAILABILITY AND IMPLEMENTATION: BDTcomparator is distributed under the GNU GPLv3 license and is freely available for download from http://www.tox-portal.net. We provide programs for both Linux and Windows operating systems. The source code of the program is provided in our companion website http://code.google.com/p/bdtcomparator/. CONTACT: kamil.fijorek@uek.krakow.pl SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Predictive model for L-type channel inhibition: multichannel block in QT prolongation risk assessment.

Evaluation of the proarrhythmic potential of an investigated compound is now an integral element of the safety profile required for the approval of new drugs. The human ether-à-go-go-related gene (hERG) channel blocking potency is regarded as a surrogate marker of the proarrhythmic risk at the early stages of the research and development process. However, there is no straight correlation between QT prolongation and TdP occurrence probability, and hERG inhibition potential can be an inadequate predictor of QT prolongation. The L-type calcium channel plays a pivotal role in cardiomyocytes' physiology. Thus the main aim of this study was to develop a predictive model for drug-triggered CaL channel inhibition and also the assessment of drug-multichannel interaction effects on the heart rate-corrected QT interval. The data set, consisting of 123 records describing in vitro experimental settings, measured IC50 values and calculated physico-chemical properties for 72 various chemicals, was collected. The models were tested in a modified 10-fold cross-validation procedure. The generalization ability of the best model was as follows: root mean squared error (RMSE) = 1.10, normalized root mean squared error (NRMSE) = 16.09%. Out of the 10 most important variables, 5 described conditions of the in vitro experiments thus their description and experiment's conditions standardization might be the key to the models better performance. The simulations performed with the ToxComp system showed that the hERG block alone causes concentration-dependent QT prolongation, whereas when multichannel block is regarded, the effect could be reversed. For that reason, the multichannel interaction of tested compounds should be taken into consideration, in order to make the proarrhythmic risk assessment more reliable.

Virtual population generator for human cardiomyocytes parameters: in silico drug cardiotoxicity assessment.

BACKGROUND: The anatomical and histological parameters of the human ventricle depend on many factors including age and sex. Myocyte volume and electric capacitance are significant physiological parameters of left ventricle cardiomyocyte mathematical models. They allow the assessment of inter-individual variability during in vitro-in vivo extrapolation of the drug cardiotoxic effect. OBJECTIVE: The current research was carried out to analyze the relationship between age, human left ventricle cardiomyocyte volume, and electric capacitance in a healthy population. METHODS: In order to collect data describing cardiomyocyte volume and membrane area, literature searches were performed. It was assumed that the cardiomyocyte volume (VOL) and area (AREA) distribution have non-negative support and are skewed to the right. A log-linear model with constant variance was used. A simulation study was run to assess the influence of physiological parameters on action potential duration. RESULTS: The coefficient of determination for the proposed model R(2) = 0.95, that is, 95% of the variability observed in log cardiomyocyte volume can be explained by the estimated regression equation. To allow simple calculation and model performance validation, a simple Excel file was developed (Supplementary material). CONCLUSIONS: To the best of our knowledge, there is no other model available, combining age, cardiomyocyte volume, and area. The main limitations of the proposed models result from the assumptions made at the data analysis stage. The limited amount of information available in the literature and the lack of differentiation between sexes results in one common equation. The developed model is a part of the computational system for drug cardiotoxicity assessment.

Open-access database of literature derived drug-related Torsade de Pointes cases.

Since an introduction of an ICH guidance in 2005, no new drugs were withdrawn from the market because of the causation of Torsade de Pointes (TdP). However, the risk of TdP is still a concern for marketed drugs. TdP is a type of polymorphic ventricular tachycardia which may lead to sudden cardiac death. QT/QTc interval prolongation is considered a sensitive, but not specific biomarker. To improve the effectiveness of studies' workflow related to TdP risk prediction we created an extensive, structured, open-access database of drug-related TdP cases. PubMed, Google Scholar bibliographic databases, and the Internet, via the Google search engine, were searched to identify eligible reports. A total of 424 papers with a description of 634 case reports and observational studies were included. Each paper was manually examined and listed with up to 53 variables related to patient/population characteristics, general health parameters, used drugs, laboratory measurements, ECG results, clinical management, and its outcomes, as well as suspected drug's properties and its FDA adverse reaction reports. The presented database may be considered as an extension of the recently developed and published database of drug cardiac safety-related information, part of the tox-portal project providing resources for cardiac toxicity assessment.

An open-access data set of pig skin anatomy and physiology for modelling purposes.

The use of animal as opposed to human skin for in vitro permeation testing (IVPT) is an alternative, which can reduce logistical and economic issues. However, this surrogate also has ethical considerations and may not provide an accurate estimation of dermal absorption in humans due to physiological differences. The current project aimed to provide a detailed repository for the anatomical and physiological parameters of porcine skin, with the aim of parametrizing the Multi-phase Multi-layer Mechanistic Dermal Absorption (MPML MechDermA) Model in the Simcyp Simulator. The MPML MechDermA Model is a physiologically based pharmacokinetic (PBPK) model that accounts for the physiology and geometry of skin in a mechanistic mathematical modelling framework. The database provided herein contains information on 14 parameters related to porcine skin anatomy and physiology, namely, skin surface pH, number of stratum corneum (SC) layers, SC thickness, corneocyte thickness, corneocyte dimensions (length and width), volume fraction of water in corneocyte (where SC is divided into four parts with different water contents), intercellular lipid thickness, viable epidermis thickness, dermis thickness, hair follicle and hair shaft diameter, hair follicle depth and hair follicle density. The collected parameters can be used to parameterize PBPK models, which could be further utilized to bridge the gap between animal and human studies with interspecies extrapolation or to predict dermatokinetic properties typically assessed in IVPT experiments. Database URL: https://data.mendeley.com/datasets/mwz9xv4cpd/1.