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Journal of Pharmacokinetics and... Apr 2019Here we characterize and summarize the pharmacokinetic changes for metabolized drugs when drug-drug interactions and pharmacogenomic variance are observed. Following... (Review)
Review
Here we characterize and summarize the pharmacokinetic changes for metabolized drugs when drug-drug interactions and pharmacogenomic variance are observed. Following multiple dosing to steady-state, oral systemic concentration-time curves appear to follow a one-compartment body model, with a shorter rate limiting half-life, often significantly shorter than the single dose terminal half-life. This simplified disposition model at steady-state allows comparisons of measurable parameters (i.e., area under the curve, half-life, maximum concentration and time to maximum concentration) following drug interaction or pharmacogenomic variant studies to be utilized to characterize whether a drug is low versus high hepatic extraction ratio, even without intravenous dosing. The characteristics of drugs based on the ratios of area under the curve, maximum concentration and half-life are identified with recognition that volume of distribution is essentially unchanged for drug interaction and pharmacogenomic variant studies where only metabolic outcomes are changed and transporters are not significantly involved. Comparison of maximum concentration changes following single dose interaction and pharmacogenomic variance studies may also identify the significance of intestinal first pass changes. The irrelevance of protein binding changes on pharmacodynamic outcomes following oral and intravenous dosing of low hepatic extraction ratio drugs, versus its relevance for high hepatic extraction ratio drugs is re-emphasized.
Topics: Area Under Curve; Drug Interactions; Half-Life; Humans; Metabolic Clearance Rate; Pharmaceutical Preparations; Pharmacogenetics
PubMed: 30911879
DOI: 10.1007/s10928-019-09626-7 -
Classification of drugs for evaluating drug interaction in drug development and clinical management.Drug Metabolism and Pharmacokinetics Dec 2021During new drug development, clinical drug interaction studies are carried out in accordance with the mechanism of potential drug interactions evaluated by in vitro... (Review)
Review
During new drug development, clinical drug interaction studies are carried out in accordance with the mechanism of potential drug interactions evaluated by in vitro studies. The obtained information should be provided efficiently to medical experts through package inserts and various information materials after the drug's launch. A recently updated Japanese guideline presents general procedures that are considered scientifically valid at the present moment. In this review, we aim to highlight the viewpoints of the Japanese guideline and enumerate drugs that were involved or are anticipated to be involved in evident pharmacokinetic drug interactions and classify them by their clearance pathway and potential intensity based on systematic reviews of the literature. The classification would be informative for designing clinical studies during the development stage, and the appropriate management of drug interactions in clinical practice.
Topics: Drug Development; Drug Interactions; Pharmaceutical Preparations
PubMed: 34666290
DOI: 10.1016/j.dmpk.2021.100414 -
Drug Safety Apr 2014Proton pump inhibitors (PPIs) are used extensively for the treatment of gastric acid-related disorders, often over the long term, which raises the potential for... (Review)
Review
Proton pump inhibitors (PPIs) are used extensively for the treatment of gastric acid-related disorders, often over the long term, which raises the potential for clinically significant drug interactions in patients receiving concomitant medications. These drug-drug interactions have been previously reviewed. However, the current knowledge is likely to have advanced, so a thorough review of the literature published since 2006 was conducted. This identified new studies of drug interactions that are modulated by gastric pH. These studies showed the effect of a PPI-induced increase in intragastric pH on mycophenolate mofetil pharmacokinetics, which were characterised by a decrease in the maximum exposure and availability of mycophenolic acid, at least at early time points. Post-2006 data were also available outlining the altered pharmacokinetics of protease inhibitors with concomitant PPI exposure. New data for the more recently marketed dexlansoprazole suggest it has no impact on the pharmacokinetics of diazepam, phenytoin, theophylline and warfarin. The CYP2C19-mediated interaction that seems to exist between clopidogrel and omeprazole or esomeprazole has been shown to be clinically important in research published since the 2006 review; this effect is not seen as a class effect of PPIs. Finally, data suggest that coadministration of PPIs with methotrexate may affect methotrexate pharmacokinetics, although the mechanism of interaction is not well understood. As was shown in the previous review, individual PPIs differ in their propensities to interact with other drugs and the extent to which their interaction profiles have been defined. The interaction profiles of omeprazole and pantoprazole sodium (pantoprazole-Na) have been studied most extensively. Several studies have shown that omeprazole carries a considerable potential for drug interactions because of its high affinity for CYP2C19 and moderate affinity for CYP3A4. In contrast, pantoprazole-Na appears to have lower potential for interactions with other medications. Lansoprazole and rabeprazole also seem to have a weaker potential for interactions than omeprazole, although their interaction profiles, along with those of esomeprazole and dexlansoprazole, have been less extensively investigated. Only a few drug interactions involving PPIs are of clinical significance. Nonetheless, the potential for drug interactions should be considered when choosing a PPI to manage gastric acid-related disorders. This is particularly relevant for elderly patients taking multiple medications, or for those receiving a concomitant medication with a narrow therapeutic index.
Topics: Cytochrome P-450 CYP2C19; Cytochrome P-450 CYP3A; Drug Interactions; Humans; Proton Pump Inhibitors
PubMed: 24550106
DOI: 10.1007/s40264-014-0144-0 -
Briefings in Bioinformatics Nov 2023In clinical treatment, two or more drugs (i.e. drug combination) are simultaneously or successively used for therapy with the purpose of primarily enhancing the... (Review)
Review
In clinical treatment, two or more drugs (i.e. drug combination) are simultaneously or successively used for therapy with the purpose of primarily enhancing the therapeutic efficacy or reducing drug side effects. However, inappropriate drug combination may not only fail to improve efficacy, but even lead to adverse reactions. Therefore, according to the basic principle of improving the efficacy and/or reducing adverse reactions, we should study drug-drug interactions (DDIs) comprehensively and thoroughly so as to reasonably use drug combination. In this review, we first introduced the basic conception and classification of DDIs. Further, some important publicly available databases and web servers about experimentally verified or predicted DDIs were briefly described. As an effective auxiliary tool, computational models for predicting DDIs can not only save the cost of biological experiments, but also provide relevant guidance for combination therapy to some extent. Therefore, we summarized three types of prediction models (including traditional machine learning-based models, deep learning-based models and score function-based models) proposed during recent years and discussed the advantages as well as limitations of them. Besides, we pointed out the problems that need to be solved in the future research of DDIs prediction and provided corresponding suggestions.
Topics: Humans; Drug Interactions; Drug-Related Side Effects and Adverse Reactions; Databases, Factual; Computer Simulation; Drug Combinations
PubMed: 38113076
DOI: 10.1093/bib/bbad445 -
The Analyst Jan 2023Proteins are major drug targets, and drug-target interaction identification and analysis are important factors for drug discovery. Atomic force microscopy (AFM) is a... (Review)
Review
Proteins are major drug targets, and drug-target interaction identification and analysis are important factors for drug discovery. Atomic force microscopy (AFM) is a powerful tool making it possible to image proteins with nanometric resolution and probe intermolecular forces under physiological conditions. We review recent studies conducted in the field of target protein drug discovery using AFM-based analysis technology, including drug-driven changes in nanomechanical properties of protein morphology and interactions. Underlying mechanisms (including thermodynamic and kinetic parameters) of the drug-target interaction and drug-modulating protein-protein interaction (PPI) on the surfaces of models or living cells are discussed. Furthermore, challenges and the outlook for the field are likewise discussed. Overall, this insight into the mechanical properties of protein-drug interactions provides an unprecedented information framework for rational drug discovery in the pharmaceutical field.
Topics: Microscopy, Atomic Force; Proteins; Kinetics; Thermodynamics; Drug Interactions
PubMed: 36398684
DOI: 10.1039/d2an01591a -
CNS & Neurological Disorders Drug... 2021A large number of individuals today use herbs as a drug alongside medicine and non-physician recommended medications, as herbs are thought to be natural and safe.... (Review)
Review
BACKGROUND
A large number of individuals today use herbs as a drug alongside medicine and non-physician recommended medications, as herbs are thought to be natural and safe. However, there are many herbs that can potentially interact with other drugs, causing hazardous effects and/or diminished therapeutic effects of other prescriptions.
OBJECTIVE
It is ought to be comprehended that herbal drugs contain multiple active compounds in different percentages, which can change the enzymatic frameworks, transporters, and, additionally, the physiological processes.
METHODS
Different search engines, such as Google Scholar, Scopus, and ScienceDirect, were used for the search of the data on the subject: pharmacokinetic drug interactions with the herbal products.
RESULTS
This worldwide increment in herbal drug popularity has risen with respect to HDIs. These PD or PK interactions are particularly significant for medications. Assessment of herbal drug interaction is difficult because of inconsistency in herbal drug composition and frequently meager information of active constituent pharmacokinetic. These restrictions are bewildered further by the differing points of view concerning herbal product regulation.
CONCLUSION
It is concluded that a basic assessment of certain pharmacokinetic HDI is needed to settle on educated choices in regard to patient safety. The expanding comprehension of HDPKI will direct more attention to potential interactions.
Topics: Drugs, Chinese Herbal; Herb-Drug Interactions; Humans; Phytotherapy
PubMed: 33032517
DOI: 10.2174/1871527319666201008151710 -
Advances in Experimental Medicine and... 2019Drug transporters are considered to be determinants of drug disposition and effects/toxicities by affecting the absorption, distribution, and excretion of drugs. Drug... (Review)
Review
Drug transporters are considered to be determinants of drug disposition and effects/toxicities by affecting the absorption, distribution, and excretion of drugs. Drug transporters are generally divided into solute carrier (SLC) family and ATP binding cassette (ABC) family. Widely studied ABC family transporters include P-glycoprotein (P-GP), breast cancer resistance protein (BCRP), and multidrug resistance proteins (MRPs). SLC family transporters related to drug transport mainly include organic anion-transporting polypeptides (OATPs), organic anion transporters (OATs), organic cation transporters (OCTs), organic cation/carnitine transporters (OCTNs), peptide transporters (PEPTs), and multidrug/toxin extrusions (MATEs). These transporters are often expressed in tissues related to drug disposition, such as the small intestine, liver, and kidney, implicating intestinal absorption of drugs, uptake of drugs into hepatocytes, and renal/bile excretion of drugs. Most of therapeutic drugs are their substrates or inhibitors. When they are comedicated, serious drug-drug interactions (DDIs) may occur due to alterations in intestinal absorption, hepatic uptake, or renal/bile secretion of drugs, leading to enhancement of their activities or toxicities or therapeutic failure. This chapter will illustrate transporter-mediated DDIs (including food drug interaction) in human and their clinical significances.
Topics: ATP Binding Cassette Transporter, Subfamily G, Member 2; ATP-Binding Cassette Transporters; Biological Transport; Drug Interactions; Food-Drug Interactions; Humans; Neoplasm Proteins; Organic Anion Transporters; Pharmaceutical Preparations
PubMed: 31571167
DOI: 10.1007/978-981-13-7647-4_5 -
American Journal of Therapeutics
Topics: Humans; Drug Interactions; Algorithms; Probability
PubMed: 37449932
DOI: 10.1097/MJT.0000000000001446 -
IEEE/ACM Transactions on Computational... 2022The detection of drug-drug interactions (DDIs) is a crucial task for drug safety surveillance, which provides effective and safe co-prescriptions of multiple drugs.... (Review)
Review
The detection of drug-drug interactions (DDIs) is a crucial task for drug safety surveillance, which provides effective and safe co-prescriptions of multiple drugs. Since laboratory researches are often complicated, costly and time-consuming, it's urgent to develop computational approaches to detect drug-drug interactions. In this paper, we conduct a comprehensive review of state-of-the-art computational methods falling into three categories: literature-based extraction methods, machine learning-based prediction methods and pharmacovigilance-based data mining methods. Literature-based extraction methods detect DDIs from published literature using natural language processing techniques; machine learning-based prediction methods build prediction models based on the known DDIs in databases and predict novel ones; pharmacovigilance-based data mining methods usually apply statistical techniques on various electronic data to detect drug-drug interaction signals. We first present the taxonomy of drug-drug interaction detection methods and provide the outlines of three categories of methods. Afterwards, we respectively introduce research backgrounds and data sources of three categories, and illustrate their representative approaches as well as evaluation metrics. Finally, we discuss the current challenges of existing methods and highlight potential opportunities for future directions.
Topics: Data Mining; Databases, Factual; Drug Interactions; Machine Learning; Natural Language Processing
PubMed: 34003753
DOI: 10.1109/TCBB.2021.3081268 -
Current Drug Metabolism 2023Herb medicine has a long history of application and is still used worldwide. With the development of complementary and alternative medicine, the interaction between herb... (Review)
Review
Herb medicine has a long history of application and is still used worldwide. With the development of complementary and alternative medicine, the interaction between herb and drugs has attracted more and more attention. Herb-drug interactions (HDI) could cause decreased efficiency, increased toxicity, and affect the drug absorption and disposition processes due to the interference of their pharmacological or pharmacokinetic effects. Hence, the mechanisms and results of herb-pharmacokinetic interactions should be comprehensively summarized. Here, we have summarized the mechanisms of HDI and pharmacokinetic interactions in the last ten years based on searching on PubMed, Science Direct, and Web of Science with different keywords. Besides, the pharmacokinetic interactions were related to nine commonly used herbs and drugs, including Ginseng, Salvia miltiorrhiza, Ginkgo biloba, Garlic, Coptis chinensis, St. John's wort, Ginger, Licorice, Silythistle and Fructus Schisandrae. This review provides an overview of HDI to provide a reference for the rational and safe clinical use of herbs and drugs.
Topics: Humans; Herb-Drug Interactions; Plants, Medicinal; Biological Products
PubMed: 36650621
DOI: 10.2174/1389200224666230116113240