Figure 2 - uploaded by Gerhard J Nohynek
Content may be subject to copyright.
The distribution of molecular weight for 340 compounds. The molecular weights span a wide range of 18 to 765.
Source publication
The objective of this study was to construct and validate a quantitative structure-activity relationship model for skin absorption. Such models are valuable tools for screening and prioritization in safety and efficacy evaluation, and risk assessment of drugs and chemicals. A database of 340 chemicals with percutaneous absorption was assembled. Two...
Context in source publication
Citations
... The relationship between descriptors and skin permeability has been extensively studied in previous research [28,29]. In our investigation, we identified four descriptors, namely XLogP, number of hydrogen bond doners (nHBDon), number of hydrogen bond acceptors (nHBAcc), and topological polar surface area (TopoPSA), which exhibited a strong correlation with LogK p . ...
... XLogP is a calculation method for LogP and represents a measure of molecular hydrophobicity [30]. LogP has been widely recognized for its significant association with skin permeability [29]. This observation is consistent with the understanding that hydrophobic molecules have an increased ability to traverse the hydrophobic barrier of the skin. ...
The transdermal route of drug administration has gained popularity for its convenience and bypassing the first-pass metabolism. Accurate skin permeability prediction is crucial for successful transdermal drug delivery (TDD). In this study, we address this critical need to enhance TDD. A dataset comprising 441 records for 140 molecules with diverse LogKp values was characterized. The descriptor calculation yielded 145 relevant descriptors. Machine learning models, including MLR, RF, XGBoost, CatBoost, LGBM, and ANN, were employed for regression analysis. Notably, LGBM, XGBoost, and gradient boosting models outperformed others, demonstrating superior predictive accuracy. Key descriptors influencing skin permeability, such as hydrophobicity, hydrogen bond donors, hydrogen bond acceptors, and topological polar surface area, were identified and visualized. Cluster analysis applied to the FDA-approved drug dataset (2326 compounds) revealed four distinct clusters with significant differences in molecular characteristics. Predicted LogKp values for these clusters offered insights into the permeability variations among FDA-approved drugs. Furthermore, an investigation into skin permeability patterns across 83 classes of FDA-approved drugs based on the ATC code showcased significant differences, providing valuable information for drug development strategies. The study underscores the importance of accurate skin permeability prediction for TDD, emphasizing the superior performance of nonlinear machine learning models. The identified key descriptors and clusters contribute to a nuanced understanding of permeability characteristics among FDA-approved drugs. These findings offer actionable insights for drug design, formulation, and prioritization of molecules with optimum properties, potentially reducing reliance on costly experimental testing. Future research directions include offering promising applications in pharmaceutical research and formulation within the burgeoning field of computer-aided drug design.
... The strategies employed in QSPR are quite novel, and QSPR may become a new and better tool to solve the problem. Such approaches include chemical structure-based approaches, for example, fragment descriptor and neural network-based modeling approaches using large databases of theoretical molecular descriptors [123][124][125], ensemble modeling using nearest neighbor theories [126], topostructural, topochemical, shape and/or quantum mechanical indices [127] and Gaussian process models [128]. Such approaches, though novel, have yet to find significant, "real-world" application. ...
In vivo skin permeation studies are considered gold standard but are difficult to perform and evaluate due to ethical issues and complexity of process involved. In recent past, a useful tool has been developed by combining the computational modeling and experimental data for expounding biological complexity. Modeling of percutaneous permeation studies provides an ethical and viable alternative to laboratory experimentation. Scientists are exploring complex models in magnificent details with advancement in computational power and technology. Mathematical models of skin permeability are highly relevant with respect to transdermal drug delivery, assessment of dermal exposure to industrial and environmental hazards as well as in developing fundamental understanding of biotransport processes. Present review focuses on various mathematical models developed till now for the transdermal drug delivery along with their applications.
... The descriptors used to define the model elements are based on the previously published experimental data. 17,22,23,[27][28][29][30][31][32][33][34][35][36][37][38] These were combined and integrated into the Simcyp R simulator (version 10 and above) with a user-friendly interface aiming for wider usage beyond the modelling experts. ...
Estimation of systemic exposure after absorption of any xenobiotic from the skin is very important in development of dermal pharmaceutical products as well as assessing un-intended exposures due to cosmetic products or environmental and occupational compounds. Historically, animal models have been used to evaluate dermal drug absorption before conducting human trials. However, occasional disparity between the animal and human data plus rising public interest and regulatory requirements to reduce animal usage in research combined with high cost and time-consuming attributes of animal experiments have prompted many academic and industrial researchers to develop economically viable and scientifically robust in silico and in vitro methods to assess dermal drug absorption. There are a number of in silico models available in literature from quantitative structure-activity relationship to semi-mechanistic to physiologically based mechanistic models. Nonetheless, to the best of our knowledge, so far, there has been no attempt to combine mechanistic skin absorption model with database of physiological variability to simulate the inter- and intra-individual variability observed in human trials. Thus, we report here mechanistic dermal absorption model with formulation, stratum corneum, viable epidermis-dermis and blood compartments along with datab"ase of human dermal physiological variability including gender, ethnic and site of application variations. The developed model is incorporated into the Simcyp simulator which is a 'bottom-up' platform and database for mechanistic modelling and simulation of the drug disposition process using full body physiologically based pharmacokinetics model. The built model is validated using the clinical pharmacokinetic data from five different topical formulations of diclofenac. The effect of penetration enhancers, site of application, gender and ethnic variations were incorporated to simulate the clinical trials. The applied mechanistic dermal absorption model when combined with skin physiological database was able to recover well the observed clinical pharmacokinetics and population variability in all the five validation studies.
... The strategies employed have sometimes been quite novel, and have brought new tools to bear on the problem. Such approaches include chemical structure-based approaches, for example, fragment descriptor and neural network-based modeling approaches using large pools of theoretical molecular descriptors (Katritzky et al., 2006;Baert et al., 2007;Luo et al., 2007;Neely et al., 2009), ensemble modeling using nearest-neighbor theories (Neumann et al., 2006), topostructural, topochemical, shape and/or quantum Johnson et al. (1997). Key model parameters are the corneocyte aspect ratio, ˛ = d/t; the lipid/corneocyte thickness ratio, ˇ = g/t; and the offset ratio, ω = d l /ds. ...
Mathematical models of skin permeability play an important role in various fields including prediction of transdermal drug delivery and assessment of dermal exposure to industrial chemicals. Extensive research has been performed over the last several decades to yield predictions of skin permeability to various molecules. These efforts include the development of empirical approaches such as quantitative structure-permeability relationships and porous pathway theories as well as the establishment of rigorous structure-based models. In addition to establishing the necessary mathematical framework to describe these models, efforts have also been dedicated to determining the key parameters that are required to use these models. This article provides an overview of various modeling approaches with respect to their advantages, limitations and future prospects.
... Hinz et al. (36) recognized molecular volume as a determinant of J max , while Mitragotri's algorithm for k p was based on molecular radius or cross-sectional area (37). Size, rather than weight, may be a more meaningful parameter, as the presence of bulky side groups in molecules with similar molecular weights reduces human skin flux (52) or permeability coefficients (53). ...
The prediction of skin absorption remains a major goal in a number of fields including topical drug discovery, the cosmetic and cosmeceutical industries, and risk assessment for dermal exposure to toxic substances. There are obvious advantages in developing reliable predictive techniques that can eliminate or reduce the need for extensive and expensive experimental studies. Since the early recognition that the lipid-rich stratum corneum (SC) formed the major barrier to skin penetration by exogenous substances (1) and that physicochemical properties could determine the rate of penetration (2), much work has been done on identifying the relevant physicochemical properties. The outcome of such work has usually been in the form of algorithms known as quantitative structure-activity relationships (QSARs) or quantitative structure-permeability relationships (QSPRs) to predict skin transport. Recent reviews on QSAR/QSPR use in regulatory risk assessment (3) and general skin permeability (4) have highlighted the limitations that remain with the technique.
Toxicological Effects of Veterinary Medicinal Products in Humans is the first definitive guide to discuss the adverse effects of veterinary medicinal products in humans. The chapters focus on occupational safety and consumer issues and examine the circumstances under which exposure is likely to occur. To be in context, it reviews this against the background of adverse health effects from other sources in the veterinary and farming professions. The book examines adverse drug effects reported to regulatory agencies (mainly the FDAÆs Center for Veterinary Medicine) and then considers a series of individual drugs, including antibiotics, anaesthetics and organophosphorus compounds. The chapters also discuss the fundamental aspects of regulatory issues relating to safety assessment, and examine the manner in which user safety is assessed prior to authorisation/approval and what measures can be taken after authorisation/approval in the light of findings from pharmacovigilance activities. There is growing concern over the issue of antimicrobial resistance and the contribution made by veterinary medicinal products. This too is addressed along with the significance to human health and measures that can be taken to mitigate the effects (if any) of the use of antibiotics in animals e.g. prudent use measures. The book will be an essential resource for medical practitioners in hospitals and general practice, pharmaceutical industry scientists, analysts, regulators and risk managers.
Consumer and environmental protection depend on the careful regulation of all classes of chemicals. Toxicology is the key science used to evaluate safety and so underpins regulatory decisions on chemicals. With the growing body of EU legislation involved in chemical regulation, there is a concomitant need to understand the toxicological principles underlying safety assessments
Regulatory Toxicology in the European Union is the first book to cover regulatory toxicology specifically in Europe. It addresses the need for a wider understanding of the principles of regulatory toxicology and their application and presents the relationship between toxicology and legislative processes in regulating chemical commodities across Europe. This title has a broad scope, covering historical and current chemical regulation in Europe, the role of European agencies and institutions, and also the use of toxicology data for important classes of chemicals, including human and veterinary medicines, animal feed and food additives, biocides, pesticides and nanomaterials. This book is therefore extremely pertinent and timely in the toxicology field at present.
This book is an essential reference for regulatory authorities, industrialists, academics, undergraduates and postgraduates working within safety and hazards, toxicology, the biological sciences, and the medicinal and pharmaceutical sciences across the European Union.
This paper reviews in silico models currently available for the prediction of skin permeability. A comprehensive discussion on the currently available methods is presented, focusing on quantitative structure-permeability relationships. In addition, the mechanistic models and comparative studies that analyse different models are discussed. Limitations and strengths of the different approaches are highlighted together with the emergent issues and perspectives.
This review examines recent progress made in the field of modelling and predicting percutaneous absorption. It describes initial qualitative modelling and how quantitative approaches were pioneered and then developed, particularly in the context of the analysis of specific subsets of data. It then focuses on recent developments, including non-linear modelling and discusses recommendations in model construction, development and validation, suggesting that some models do not fit proposed guidelines.
