Current Drug Metabolism - Volume 23, Issue 5, 2022

Numerous dermal contact products, such as drugs or cosmetics, are applied on the skin, the first protective barrier to their entrance into the organism. These products contain various xenobiotic molecules that can penetrate the viable epidermis. Many studies have shown that keratinocyte metabolism could affect their behavior by biotransformation. While aiming for detoxification, toxic metabolites can be produced. These metabolites may react with biological macromolecules often leading to sensitization reactions. After passing through the epidermis, xenobiotics can reach the vascularized dermis and therefore, be bioavailable and distributed into the entire organism. To highlight these mechanisms, dermatokinetics, based on the concept of pharmacokinetics, has been developed recently. It provides information on the action of xenobiotics that penetrate the organism through the dermal route. The purpose of this review is first to describe and synthesize the dermatokinetics mechanisms to consider when assessing the absorption of a xenobiotic through the skin. We focus on skin absorption and specifically on skin metabolism, the two main processes involved in dermatokinetics. In addition, experimental models and methods to assess dermatokinetics are described and discussed to select the most relevant method when evaluating, in a specific context, dermatokinetics parameters of a xenobiotic. We also discuss the limits of this approach as it is notably used for risk assessment in the industry where scenario studies generally focus only on one xenobiotic and do not consider interactions with the rest of the exposome. The hypothesis of adverse effects due to the combination of chemical substances in contact with individuals and not to a single molecule, is being increasingly studied and embraced in the scientific community.

Cancer is a leading cause of mortality globally. Cytochrome P450 (CYP) enzymes play a pivotal role in the biotransformation of both endogenous and exogenous compounds. Various lines of evidence from epidemiological, animal, and clinical studies point to the instrumental role of CYPs in cancer initiation, metastasis, and prevention. Substantial research has found that CYPs are involved in activating different carcinogenic chemicals in the environment, such as polycyclic aromatic hydrocarbons and tobacco-related nitrosamines. Electrophilic intermediates produced from these chemicals can covalently bind to DNA, inducing mutation and cellular transformation that collectively result in cancer development. While bioactivation of procarcinogens and promutagens by CYPs has long been established, the role of CYP-derived endobiotics in carcinogenesis has only emerged in recent years. Eicosanoids derived from arachidonic acid via CYP oxidative pathways have been implicated in tumorigenesis, cancer progression and metastasis. The purpose of this review is to update the current state of knowledge about the molecular cancer mechanism involving CYPs with a focus on the biochemical and biotransformation mechanisms in the various CYP-mediated carcinogenesis and the role of CYP-derived reactive metabolites, from both external and endogenous sources, in cancer growth and tumor formation.

Background: The representative anti-COVID-19 herbs, i.e., Poriacocos, Pogostemon, Prunus, and Glycyrrhiza plants, are commonly used in the prevention and treatment of COVID-19, a pandemic caused by SARSCoV- 2. Diverse medicinal compounds with favorable anti-COVID-19 activities are abundant in these plants, and their unique pharmacological/pharmacokinetic properties have been revealed. However, the current trends in Drug Metabolism/Pharmacokinetic (DMPK) investigations of anti-COVID-19 herbs have not been systematically summarized. Methods: In this study, the latest awareness, as well as the perception gaps regarding DMPK attributes, in the anti- COVID-19 drug development and clinical usage was critically examined and discussed. Results: The extracts and compounds of P.cocos, Pogostemon, Prunus, and Glycyrrhiza plants show distinct and diverse absorption, distribution, metabolism, excretion, and toxicity (ADME/T) properties. The complicated herbherb interactions (HHIs) and herb-drug interactions (HDIs) of anti-COVID-19 Traditional Chinese Medicine (TCM) herb pair/formula dramatically influence the PK/pharmacodynamic (PD) performance of compounds thereof, which may inspire researchers to design innovative herbal/compound formulas for optimizing the therapeutic outcome of COVID-19 and related epidemic diseases. The ADME/T of some abundant compounds in anti-COVID-19 plants have been elucidated, but DMPK studies should be extended to more compounds of different medicinal parts, species, and formulations and would be facilitated by various omics platforms and computational analyses. Conclusion: In the framework of pharmacology and pharmacophylogeny, the DMPK knowledge base would promote the translation of bench findings into the clinical practice of anti-COVID-19 and speed up the anti-COVID-19 drug discovery and development.

Background: High Content Image (HCI), an automatic imaging and analysis system, provides a fast drug screening method by detecting the subcellular distribution of protein in intact cells. Objective: This study established the first standardized HCI platform for lipopolysaccharide (LPS)-induced RAW264.7 macrophages to screen anti-inflammatory compounds by measuring nuclear factor-ΚB (NF-ΚB) nuclear translocation. Methods: The influence of the cell passages, cell density, LPS induction time and concentration, antibody dilution, serum, dimethyl sulfoxide, and analysis parameters on NF-ΚB nuclear translocation and HCI data quality was optimized. The BAY-11-7085, the positive control for inhibiting NF-ΚB, and the Western blot assay were separately employed to verify the stability and reliability of the platform. Lastly, the effect of BHA on NO release, iNOS expression, IL-1β, IL-6, and TNF-α mRNA in LPS-induced RAW264.7 cells was detected. Results: The optimal conditions for measuring NF-ΚB translocation in LPS-induced RAW264.7 cells by HCI were established. Cells that do not exceed 22 passages were seeded at a density of 10 k cells/well and pretreated with compounds following 200 ng/mL LPS for 40 min. Parameters including the nuclear area of 65 μm2, cell area of 80 μm2, collar of 0.9 μm, and sensitivity of 25% were recommended for image segmentation algorithms in the analysis workstation. Benzoylhypaconine from aconite was screened for the first time as an anti-inflammatory candidate by the established HCI platform. The inhibitory effect of benzoylhypaconine on NF-ΚB translocation was verified by Western blot. Furthermore, benzoylhypaconine reduced the release of NO, inhibited the expression of iNOS, and decreased the mRNA levels of IL-1β, IL-6, and TNF-α. Conclusion: The established HCI platform could be applied to screen anti-inflammatory compounds by measuring the NF-ΚB nuclear translocation in LPS-induced RAW264.7 cells.

Background: Warfarin is an anticoagulant with wide inter-individual variations in drug responses monitored based on the International Normalized Ratio (INR). It is commonly prescribed for Atrial Fibrillation (AF) and stroke. Oral anticoagulants (e.g., warfarin) reduce the risk of getting a stroke but increase the risk of hemorrhage. The proton Nuclear Magnetic Resonance (1H-NMR) pharmacometabonomics technique is useful for determining drug responses. Furthermore, pharmacometabonomics analysis can help identify novel biomarkers of warfarin outcome/ INR stability in urine. Objectives: The focus of this research was to determine if urine metabolites could predict the warfarin response based on INR in patients who were already taking warfarin (identification; phase I) and to determine if urine metabolites could distinguish between unstable and stable INR in patients who had just started taking warfarin (validation; phase II). Methods: A cross-sectional study was conducted. Ninety urine samples were collected for phase 1, with 49 having unstable INR and 41 having stable INR. In phase II, 21 urine samples were obtained, with 13 having an unstable INR and eight having a stable INR. The metabolites associated with unstable INR and stable INR could be determined using univariate and multivariate logistic regression analysis. Results: Multivariate Logistic Regression (MVLR) analysis showed that unstable INR was linked with seven regions. Discussion: The urine pharmacometabonomics technique utilized could differentiate between the urine metabolite profiles of the patients on warfarin for INR stability. Conclusion: ¹H-NMR-based pharmacometabonomics can help lead to a more individualized, controlled side effect for warfarin, thus minimizing undesirable effects in the future.

Background: Meropenem is a carbapenem antibiotic and is commonly used with other antibiotics for the treatment of bacterial infections. It is primarily eliminated renally by glomerular filtration and renal tubular secretion. Objective: This study aimed to evaluate the roles of renal uptake and efflux transporters in the excretion of meropenem and potential drug interactions mediated by renal drug transporters. Methods: Uptake and inhibition studies were conducted in human embryonic kidney 293 cells stably transfected with Organic Anion Transporter (OAT) 1, OAT3, Multidrug and Toxin Extrusion Protein (MATE) 1, and MATE2K, as well as membrane vesicles containing breast cancer resistance-related protein (BCRP), multidrug resistance protein 1 (MDR1), and Multidrug Resistance-associated Protein 2 (MRP2). Probenecid and piperacillin were used to assess potential drug interactions with meropenem in rats. Results: We observed that meropenem was a low-affinity substrate of OAT1/3 and had a weak inhibitory effect on OAT1/3 and MATE2K. BCRP, MDR1, MRP2, MATE1, and MATE2K could not mediate renal excretion of meropenem. Moreover, meropenem was not an inhibitor of BCRP, MDR1, MRP2, or MATE1. Among five tested antibiotics, moderate inhibition on OAT3-mediated meropenem uptake was observed for linezolid (IC50 value was 69.2 μM), weak inhibition was observed for piperacillin, benzylpenicillin, and tazobactam (IC50 values were 282.2, 308.0 and 668.1 μM, respectively), and no inhibition was observed for sulbactam. Although piperacillin had a relatively high drug-drug interaction index (ratio of maximal unbound plasma concentration to IC50 was 1.42) in vitro, no meaningful impact was reported on the pharmacokinetics of meropenem in rats. Conclusion: Our results indicated that clinically significant interactions between meropenem and these five antibiotics are low.