Current Drug Metabolism - Volume 24, Issue 3, 2023

Background: The special environment of high-altitude hypoxia not only changes the physiological state of the body but also affects the metabolic process of many drugs, which may affect the safety and efficacy of these drugs. The number of drugs is huge, so it is not wise to blindly repeat the pharmacokinetic studies of all of them on the plateau. Mastering the law of drug metabolism on the plateau is conducive to the comprehensive development of rational drug use on the plateau. Therefore, it is very important to determine the impacts and elucidate the mechanism of drug metabolism in hypobaric hypoxia conditions. Methods: In this review, we searched published studies on changes in drug metabolism in hypoxia conditions to summarize and analyze the mechanisms by which hypoxia alters drug metabolism. Results: Although the reported effects of high-altitude hypoxia on drug metabolism are sometimes controversial, metabolism kinetics for most of the tested drugs are found to be affected. Mechanism studies showed that the major reasons causing metabolism changes are: regulated drug-metabolizing enzymes expression and activity mediated by HIF-1, nuclear receptors and inflammatory cytokines, and change in direct or indirect effects of intestinal microflora on drug metabolism by itself or the host mediated by microflora-derived drug-metabolizing enzymes, metabolites, and immunoregulation. Conclusion: Altered enzyme expression and activity in the liver and altered intestinal microflora are the two major reasons to cause altered drug metabolism in hypoxia conditions.

Protein transporters not only have essential functions in regulating the transport of endogenous substrates and remote communication between organs and organisms, but they also play a vital role in drug absorption, distribution, and excretion and are recognized as major determinants of drug safety and efficacy. Understanding transporter function is important for drug development and clarifying disease mechanisms. However, the experimental-based functional research on transporters has been challenged and hinged by the expensive cost of time and resources. With the increasing volume of relevant omics datasets and the rapid evolution of artificial intelligence (AI) techniques, next-generation AI is becoming increasingly prevalent in the functional and pharmaceutical research of transporters. Thus, a comprehensive discussion on the state-of-the-art application of AI in three cutting-edge directions was provided in this review, which included (a) transporter classification and function annotation, (b) structure discovery of membrane transporters, and (c) drug-transporter interaction prediction. This study provides a panoramic view of AI algorithms and tools applied to the field of transporters. It is expected to guide a better understanding and utilization of AI techniques for in-depth studies of transporter-centered functional and pharmaceutical research.

Drug-metabolizing enzymes and transporters are major determinants of the absorption, disposition, metabolism, and excretion (ADME) of drugs, and changes in ADME gene expression or function may alter the pharmacokinetics/ pharmacodynamics (PK/PD) and further influence drug safety and therapeutic outcomes. ADME gene functions are controlled by diverse factors, such as genetic polymorphism, transcriptional regulation, and coadministered medications. MicroRNAs (miRNAs) are a superfamily of regulatory small noncoding RNAs that are transcribed from the genome to regulate target gene expression at the post-transcriptional level. The roles of miRNAs in controlling ADME gene expression have been demonstrated, and such miRNAs may consequently influence cellular drug metabolism and disposition capacity. Several types of miRNA mimics and small interfering RNA (siRNA) reagents have been developed and widely used for ADME research. In this review article, we first provide a brief introduction to the mechanistic actions of miRNAs in post-transcriptional gene regulation of drug-metabolizing enzymes, transporters, and transcription factors. After summarizing conventional small RNA production methods, we highlight the latest advances in novel recombinant RNA technologies and applications of the resultant bioengineered RNA (BioRNA) agents to ADME studies. BioRNAs produced in living cells are not only powerful tools for general biological and biomedical research but also potential therapeutic agents amenable to clinical investigations.

Background: Carboxylesterase 2 (CES2) is mainly distributed in the human liver and gut, and plays an active role in the metabolic activation of many prodrugs and lipid metabolism. Although CES2 is of great significance, there are still few animal models related to CES2. Objectives: This research aims to construct Ces2c gene knockout (KO) rats and further study the function of CES2. Methods: CRISPR/Cas9 gene editing technology was used to target and cleave the rat Ces2c gene. Compensatory effects of major CES subtypes both in the liver and small intestine of KO rats were detected at mRNA levels. Meanwhile, diltiazem and aspirin were used as substrates to test the metabolic capacity of Ces2c in KO rats. Results: This Ces2c KO rat model showed normal growth and breeding without off-target effects. The metabolic function of Ces2c KO rats was verified by the metabolic study of CES2 substrates in vitro. The results showed that the metabolic capacity of diltiazem in KO rats was weakened, while the metabolic ability of aspirin did not change significantly. In addition, the serum physiological indexes showed that the Ces2c deletion did not affect the liver function of rats.. Conclusion: The Ces2c KO rat model was successfully constructed by CRISPR/Cas9 system. This rat model can not only be used as an important tool to study the drug metabolism mediated by CES2, but also as an important animal model to study the physiological function of CES2.

Background: Global xenobiotic profiling (GXP) is to detect and structurally characterize all xenobiotics in biological samples using mainly liquid chromatography-high resolution mass spectrometry (LC-HRMS) based methods. GXP is highly needed in drug metabolism study, food safety testing, forensic chemical analysis, and exposome research. For detecting known or predictable xenobiotics, targeted LC-HRMS data processing methods based on molecular weights, mass defects and fragmentations of analytes are routinely employed. For profiling unknown xenobiotics, untargeted and LC-HRMS based metabolomics and background subtraction-based approaches are required. Objective: This study aimed to evaluate the effectiveness of untargeted metabolomics and the precise and thorough background subtraction (PATBS) in GXP of rat plasma. Methods: Rat plasma samples collected from an oral administration of nefazodone (NEF) or Glycyrrhizae Radix et Rhizoma (Gancao, GC) were analyzed by LC-HRMS. NEF metabolites and GC components in rat plasma were thoroughly searched and characterized via processing LC-HRMS datasets using targeted and untargeted methods. Results: PATBS detected 68 NEF metabolites and 63 GC components, while the metabolomic approach (MS-DIAL) found 67 NEF metabolites and 60 GC components in rat plasma. The two methods found 79 NEF metabolites and 80 GC components with 96% and 91% successful rates, respectively. Conclusion: Metabolomics methods are capable of GXP and measuring alternations of endogenous metabolites in a group of biological samples, while PATBS is more suited for sensitive GXP of a single biological sample. A combination of metabolomics and PATBS approaches can generate better results in the untargeted profiling of unknown xenobiotics.

Drug-related adverse events are higher in older patients than in non-older patients, increasing the risk of medication and reducing compliance. Aging is accompanied by a decline in physiological functions and metabolic weakening. Most tissues and organs undergo anatomical and physiological changes that may affect the pharmacokinetic (PK) and pharmacodynamic (PD) characteristics of drugs. Clinical trials are the gold standard for selecting appropriate dosing regimens. However, older patients are generally underrepresented in clinical trials, resulting in a lack of evidence for establishing an optimal dosing regimen for older adults. The physiologically based pharmacokinetic (PBPK) model is an effective approach to quantitatively describe the absorption, distribution, metabolism, and excretion of drugs in older adults by integrating physiological parameters, drug physicochemical properties, and preclinical or clinical PK data. The PBPK model can simulate the PK/PD characteristics of clinical drugs in different scenarios, ultimately compensating for inadequate clinical trial data in older adults, and is recommended by the Food and Drug Administration for clinical pharmacology studies in older adults. This review describes the effects of physiological changes on the PK/PD process in older adults and summarises the research progress of PBPK models. Future developments of PBPK models are also discussed, together with the application of PBPK models in older adults, aiming to assist the development of clinical study strategies in older adults.

Background: Benzodiazepines (BZDs) are compounds that contain one diazepine ring and two benzene rings, and are widely used to treat central nervous system diseases. However, drug abuse and BZDs' illegal addition may affect normal life and even lead to grave social harm. As BZDs may be metabolized and eliminated quickly, it is of great theoretical and practical significance to clarify their metabolic profile. Objective: In this paper, LC-Q-TOF/MS-based fragmentation behavior has been investigated for nine benzodiazepine drugs available and widely used in clinical treatment (diazepam, nitrazepam, clonazepam, oxazepam, lorazepam, alprazolam, estazolam, triazolam, and midazolam), and their metabolic profile has been studied by using in vitro human liver microsomal incubation. Methods: A regular human liver microsomal system was used to investigate the potential biotransformation of the nine benzodiazepines in vitro, and an LC-Q/TOF-MS was used to perform fragmentation behavior studies and metabolite identification. Results: As a result, characteristic fragmentation pathway and diagnostic fragment ions of the nine BZDs were analyzed, and 19 metabolites of the 9 benzodiazepines were found and identified, with glucuronidation and hydroxylation considered as their most important metabolic pathways. Conclusion: These experimental data add to our knowledge of the nine benzodiazepine drugs and their metabolism study, which could provide useful information and evidence of their in vivo metabolic profile prediction and help promote their monitoring in both clinical use and social/illegal abuse.