Inhibitory Mechanisms of Lekethromycin in Dog Liver Cytochrome P450 Enzymes Based on UPLC-MS/MS Cocktail Method

Lekethromycin (LKMS) is a synthetic macrolide compound derivative intended for use as a veterinary medicine. Since there have been no in vitro studies evaluating its potential for drug-drug interactions related to cytochrome P450 (CYP450) enzymes, the effect of the inhibitory mechanisms of LKMS on CYP450 enzymes is still unclear. Thus, this study aimed to evaluate the inhibitory effects of LKMS on dog CYP450 enzymes. A cocktail approach using ultra-performance liquid chromatography-tandem mass spectrometry was conducted to investigate the inhibitory effect of LKMS on canine CYP450 enzymes. Typical probe substrates of phenacetin, coumarin, bupropion, tolbutamide, dextromethorphan, chlorzoxazone, and testosterone were used for CYP1A2, CYP2A6, CYP2B6, CYP2C9, CYP2D6, CYP2E1, and CYP3A4, respectively. This study showed that LKMS might not be a time-dependent inhibitor. LKMS inhibited CYP2A6, CYP2B6, and CYP2D6 via mixed inhibition. LKMS exhibited mixed-type inhibition against the activity of CYP2A6 with an inhibition constant (Ki) value of 135.6 μΜ. LKMS inhibited CYP2B6 in a mixed way, with Ki values of 59.44 μM. A phenotyping study based on an inhibition assay indicated that CYP2D6 contributes to the biotransformation of LKMS. A mixed inhibition of CYP2D6 with Ki values of 64.87 μM was also observed. Given that this study was performed in vitro, further in vivo studies should be conducted to identify the interaction between LKMS and canine CYP450 enzymes to provide data support for the clinical application of LKMS and the avoidance of adverse interactions between other drugs.

A Review: Effects of Macrolides on CYP450 Enzymes

As a kind of haemoglobin, cytochrome P450 enzymes (CYP450) participate in the metabolism of many substances, including endogenous substances, exogenous substances and drugs. It is estimated that 60% of common prescription drugs require bioconversion through CYP450. The influence of macrolides on CYP450 contributes to the metabolism and drug-drug interactions (DDIs) of macrolides. At present, most studies on the effects of macrolides on CYP450 are focused on CYP3A, but a few exist on other enzymes and drug combinations, such as telithromycin, which can decrease the activity of hepatic CYP1A2 and CYP3A2. This article summarizes some published applications of the influence of macrolides on CYP450 and the DDIs of macrolides caused by CYP450. And the article may subsequently guide the rational use of drugs in clinical trials. To a certain extent, poisoning caused by adverse drug interactions can be avoided. Unreasonable use of macrolide antibiotics may enable the presence of residue of macrolide antibiotics in animal-origin food. It is unhealthy for people to eat food with macrolide antibiotic residues. So it is of great significance to guarantee food safety and protect the health of consumers by the rational use of macrolides. This review gives a detailed description of the influence of macrolides on CYP450 and the DDIs of macrolides caused by CYP450. Moreover, it offers a perspective for researchers to further explore in this area.

Genetic and pharmacological relationship between P-glycoprotein and increased cardiovascular risk associated with clarithromycin prescription: An epidemiological and genomic population-based cohort study in Scotland, UK

BACKGROUND

There are conflicting reports regarding the association of the macrolide antibiotic clarithromycin with cardiovascular (CV) events. A possible explanation may be that this risk is partly mediated through drug-drug interactions and only evident in at-risk populations. To the best of our knowledge, no studies have examined whether this association might be mediated via P-glycoprotein (P-gp), a major pathway for clarithromycin metabolism. The aim of this study was to examine CV risk following prescription of clarithromycin versus amoxicillin and in particular, the association with P-gp, a major pathway for clarithromycin metabolism.

METHODS AND FINDINGS

We conducted an observational cohort study of patients prescribed clarithromycin or amoxicillin in the community in Tayside, Scotland (population approximately 400,000) between 1 January 2004 and 31 December 2014 and a genomic observational cohort study evaluating genotyped patients from the Genetics of Diabetes Audit and Research Tayside Scotland (GoDARTS) study, a longitudinal cohort study of 18,306 individuals with and without type 2 diabetes recruited between 1 December 1988 and 31 December 2015. Two single-nucleotide polymorphisms associated with P-gp activity were evaluated (rs1045642 and rs1128503 -AA genotype associated with lowest P-gp activity). The primary outcome for both analyses was CV hospitalization following prescription of clarithromycin versus amoxicillin at 0-14 days, 15-30 days, and 30 days to 1 year. In the observational cohort study, we calculated hazard ratios (HRs) adjusted for likelihood of receiving clarithromycin using inverse proportion of treatment weighting as a covariate, whereas in the pharmacogenomic study, HRs were adjusted for age, sex, history of myocardial infarction, and history of chronic obstructive pulmonary disease. The observational cohort study included 48,026 individuals with 205,227 discrete antibiotic prescribing episodes (34,074 clarithromycin, mean age 73 years, 42% male; 171,153 amoxicillin, mean age 74 years, 45% male). Clarithromycin use was significantly associated with increased risk of CV hospitalization compared with amoxicillin at both 0-14 days (HR 1.31; 95% CI 1.17-1.46, p < 0.001) and 30 days to 1 year (HR 1.13; 95% CI 1.06-1.19, p < 0.001), with the association at 0-14 days modified by use of P-gp inhibitors or substrates (interaction p-value: 0.029). In the pharmacogenomic study (13,544 individuals with 44,618 discrete prescribing episodes [37,497 amoxicillin, mean age 63 years, 56% male; 7,121 clarithromycin, mean age 66 years, 47% male]), when prescribed clarithromycin, individuals with genetically determined lower P-gp activity had a significantly increased risk of CV hospitalization at 30 days to 1 year compared with heterozygotes or those homozygous for the non-P-gp-lowering allele (rs1045642 AA: HR 1.39, 95% CI 1.20-1.60, p < 0.001, GG/GA: HR 0.99, 95% CI 0.89-1.10, p = 0.85, interaction p-value < 0.001 and rs1128503 AA 1.41, 95% CI 1.18-1.70, p < 0.001, GG/GA: HR 1.04, 95% CI 0.95-1.14, p = 0.43, interaction p-value < 0.001). The main limitation of our study is its observational nature, meaning that we are unable to definitively determine causality.

CONCLUSIONS

In this study, we observed that the increased risk of CV events with clarithromycin compared with amoxicillin was associated with an interaction with P-glycoprotein.

Development of an Adult Physiologically Based Pharmacokinetic Model of Solithromycin in Plasma and Epithelial Lining Fluid

Solithromycin is a fluoroketolide antibiotic under investigation for community-acquired bacterial pneumonia (CABP). We developed a whole-body physiologically based pharmacokinetic (PBPK) model for solithromycin in adults using PK-Sim and MoBi version 6.2, which incorporated time-dependent CYP3A4 auto-inhibition. The model was developed and evaluated using plasma and epithelial lining fluid (ELF) concentration data from 100 healthy subjects and 22 patients with CABP (1,966 plasma, 30 ELF samples). We performed population simulations and calculated the number of observations falling outside the 90% prediction interval. For the oral regimen (800 mg on day 1 and 400 mg daily on days 2-5) that was evaluated in phase III studies, 11% and 23% of observations from healthy adults fell outside the 90% prediction interval for plasma and ELF, respectively. This regimen should be effective because ≥97% of simulated adults achieved area under the concentration vs. time curve (AUC) to minimum inhibitory concentration ratios associated with a log₁₀ colony forming unit reduction in ELF.

Towards a rational design of solid drug nanoparticles with optimised pharmacological properties

Solid drug nanoparticles (SDNs) are a nanotechnology with favourable characteristics to enhance drug delivery and improve the treatment of several diseases, showing benefit for improved oral bioavailability and injectable long‐acting medicines. The physicochemical properties and composition of nanoformulations can influence the absorption, distribution, and elimination of nanoparticles; consequently, the development of nanoparticles for drug delivery should consider the potential role of nanoparticle characteristics in the definition of pharmacokinetics. The aim of this study was to investigate the pharmacological behaviour of efavirenz SDNs and the identification of optimal nanoparticle properties and composition. Seventy‐seven efavirenz SDNs were included in the analysis. Cellular accumulation was evaluated in HepG2 (hepatic) and Caco‐2 (intestinal), CEM (lymphocyte), THP1 (monocyte), and A‐THP1 (macrophage) cell lines. Apparent intestinal permeability (P_app) was measured using a monolayer of Caco‐2 cells. The P_app values were used to evaluate the potential benefit on pharmacokinetics using a physiologically based pharmacokinetic model. The generated SDNs had an enhanced intestinal permeability and accumulation in different cell lines compared to the traditional formulation of efavirenz. Nanoparticle size and excipient choice influenced efavirenz apparent permeability and cellular accumulation, and this appeared to be cell line dependent. These findings represent a valuable platform for the design of SDNs, giving an empirical background for the selection of optimal nanoparticle characteristics and composition. Understanding how nanoparticle components and physicochemical properties influence pharmacological patterns will enable the rational design of SDNs with desirable pharmacokinetics.

Development of a Multicompartment Permeability-Limited Lung PBPK Model and Its Application in Predicting Pulmonary Pharmacokinetics of Antituberculosis Drugs

Achieving sufficient concentrations of antituberculosis (TB) drugs in pulmonary tissue at the optimum time is still a challenge in developing therapeutic regimens for TB. A physiologically based pharmacokinetic model incorporating a multicompartment permeability-limited lung model was developed and used to simulate plasma and pulmonary concentrations of seven drugs. Passive permeability of drugs within the lung was predicted using an in vitro-in vivo extrapolation approach. Simulated epithelial lining fluid (ELF):plasma concentration ratios showed reasonable agreement with observed clinical data for rifampicin, isoniazid, ethambutol, and erythromycin. For clarithromycin, itraconazole and pyrazinamide the observed ELF:plasma ratios were significantly underpredicted. Sensitivity analyses showed that changing ELF pH or introducing efflux transporter activity between lung tissue and ELF can alter the ELF:plasma concentration ratios. The described model has shown utility in predicting the lung pharmacokinetics of anti-TB drugs and provides a framework for predicting pulmonary concentrations of novel anti-TB drugs.