中国2型糖尿病人中CYP2C8、CYP2C9基因多态性

目的：查明CYP2C9、CYV2C8等抗糖尿病药物主要代谢酶的基因多态性在中国2型糖尿病（T2DM）A-群中的分布频率和分布特征。方法：运用多聚酶链反应．限制性长度多态性（PCR．RFLP）方法和变性高效液相色谱法（DHPLC）对222名中国T2DM患者进行了有功能意义的CYP2C8＊3、CYP2C8P404A和CYP2C9＊3,以及可能存在功能意义的CYP2C8IVs2（-5insertt）突变体等等位基因型检测,并计算了各等位基因的频率。结果：222名中国T2DM患者的CYP2C8基因中未检出CYP2C8＊3、P404A型,CYP2C8IVS2（-5insertt）和CYP2C9＊3等位基因的频率分别为43．0％、2．48％,二者突变等位基因在男、女性别分布中不存在差异（P〉0．05）,同时为CYP2C8IVS2（-5insertt）和CYP2C9＊1＊3基因的频率为6．3％,该联合突变基因型的分布也不存在性别差异（P〉0．05）。结论：中国T2DM患者中CYP2C9＊3的等位基因频率为2．48％;未检出CYP2C8。3和P404A型,CYP2C81VS2（-5insertt）突变体发生频率为43．0％,其是否影响CYV2C8的代谢活力有待于进-步研究。     

Population pharmacokinetic modelling of S-warfarin to evaluate the design of drug–drug interaction studies for CYP2C9

This study is to assess pharmacokinetic (PK) sampling time schedules and trial size requirements of drug–drug interaction (DDI) studies for CYP2C9, based on S-warfarin population PK models. S-warfarin plasma concentrations from eight DDI studies were utilized to develop S-warfarin population PK models. Optimal PK sampling times were obtained that minimized mean squared error of geometric mean of the area under the concentration–time curve (AUC_0−∞). The powers and type I error rates of testing the equivalences of the geometric means of AUC_0−∞ only and AUC_0−∞ and maximum concentration (C _max), jointly, were assessed via simulation for two-by-two cross-over designs. The results were compared to those from three bioequivalence sample size calculation methods. Two-compartment population PK models with first order absorption were established for non-Asian and Asian subjects. The optimal PK sampling times of size 17 per individual per period were found to be 0.0, 0.5, 1.0, 2.0, 4.0, 6.0, 10.0, 12.0, 16.0, 24.0, 36.0, 48.0, 60.0, 72.0, 96.0, 120.0, 144.0 h post a single oral dose of 25 mg warfarin. For non-Asian subjects, the minimum numbers of subjects required per trial with the optimal PK sampling schedule to achieve 80% power and 5% type I error rate, ranged from 6 to 19 for the equivalence of AUC_0−∞ and C _max jointly. It has been demonstrated that appropriately selected PK sampling time points can greatly increase the corresponding power of the study without increasing the number of subjects, especially when the true ratio is near the default bioequivalence boundary (0.8–1.25).     

Relative roles of CYP2C19 and CYP3A4/5 in midazolam 1′-hydroxylation

1. During the characterization of recombinant CYP2C19, it was observed that this enzyme metabolized midazolam, which is generally regarded as CYP3A4/5 substrate, and we therefore decided to pursue this observation further.

2. CYP2C19 showed a Michaelis-Menten pattern for midazolam 1′-hydroxylation and was inhibited by (+)-N-3-benzylnirvanol and S-mephenytoin, which are a standard potent inhibitor and a substrate of CYP2C19, respectively.

3. The inhibitory potency by CYP3A4/5 inhibitor on the midazolam 1′-hydroxylation in human liver microsomes (HLM) was correlated with the CYP3A4/5 specific catalytic activity, but such correlation was not observed in CYP2C19 enzyme. The in vitro intrinsic clearance value for midazolam 1′-hydroxylation was not changed by the addition of (+)-N-3-benzylnirvanol in four individual HLM preparations.

4. These results indicated that although CYP2C19 is capable of catalyzing midazolam 1′-hydroxylation, CYP3A4/5 play a more important role.     

Comparison of two endogenous biomarkers of CYP3A4 activity in a drug–drug interaction study between midostaurin and rifampicin

Purpose

Midostaurin, a multitargeted tyrosine kinase inhibitor, is primarily metabolized by CYP3A4. This midostaurin drug–drug interaction study assessed the dynamic response and clinical usefulness of urinary 6β-hydroxycortisol to cortisol ratio (6βCR) and plasma 4β-hydroxycholesterol (4βHC) for monitoring CYP3A4 activity in the presence or absence of rifampicin, a strong CYP3A4 inducer.

Methods

Forty healthy adults were randomized into groups for either placebo or treatment with rifampicin 600 mg QD for 14 days. All participants received midostaurin 50 mg on day 9. Midostaurin plasma pharmacokinetic parameters were assessed. Urinary 6βCR and plasma 4βHC levels were measured on days 1, 9, 11, and 15.

Results

Both markers remained stable over time in the control group and increased significantly in the rifampicin group. In the rifampicin group, the median increases (vs day 1) on days 9, 11, and 15 were 4.1-, 5.2-, and 4.7-fold, respectively, for 6βCR and 3.4-, 4.1-, and 4.7-fold, respectively, for 4βHC. Inter- and intrasubject variabilities in the control group were 45.6 % and 30.5 %, respectively, for 6βCR, and 33.8 % and 7.5 %, respectively, for 4βHC. Baseline midostaurin area under the concentration–time curve (AUC) correlated with 4βHC levels (ρ?=??0.72; P?=?.003), but not with 6βCR (ρ?=?0.0925; P?=?.6981).

Conclusions

Both 6βCR and 4βHC levels showed a good dynamic response range upon strong CYP3A4 induction with rifampicin. Because of lower inter- and intrasubject variability, 4βHC appeared more reliable and better predictive of CYP3A4 activity compared with 6βCR. The data from our study further support the clinical utility of these biomarkers.     

Evaluation of drug–drug interactions in drug metabolism: Differences and harmonization in guidance/guidelines

The U.S. Drugs and Food Administration (FDA) and the Ministry of Health, Labor and Welfare of Japan (MHLW) issued the drastically revised draft guidance and final guideline on drug-drug interactions (DDI) in 2017 and 2018, respectively. One of the most drastic changes for the evaluation of inhibition potential of drug metabolizing enzymes in the liver using a basic model in these guidance and guideline are represented by the concept to use the unbound maximum concentration in the systemic circulation as the investigational drug concentration instead of the total maximum concentration and the corresponding cutoff values are applied in harmonization with the current DDI guideline of Europe. In this review, the current DDI guidance and guidelines of the three regions are compared and the points which are in common are described. In addition, several issues to be considered and/or clarified such as a criterion for the metabolites to be evaluated as perpetrator drugs, details of in vitro study design etc. are also briefly summarized. Based on further accumulation of data and information, and their continuous international scientific discussion, these issues are expected to be solved to make the current DDI guidance and guidelines be much more harmonized and practically available standards.     

Application and prospect of drug discrimination in field of drug abuse北大核心CSCD

药物辨别技术是一种研究药物主观刺激效应的行为药理学技术。目前,药物辨别技术已广泛应用于中枢神经系统药物临床前药物研发中,其中最为广泛的是用于药物的精神依赖性评价。该文简要介绍了药物辨别技术的基本原理,初步阐述了药物辨别的主观效应、时程效应、立体特异性和个体差异,以及受体机制等相关特点和应用,并对其在新型精神活性物质致幻剂和大麻类药物方面的应用进行展望。     

Metabolism of (−)-fenchone by CYP2A6 and CYP2B6 in human liver microsomes

The in vitro metabolism of (?)-fenchone was examined in human liver microsomes and recombinant enzymes. The biotransformation of (?)-fenchone was investigated by gas chromatography-mass spectrometry. (?)-Fenchone was found to be oxidized to 6-exo-hydroxyfenchone, 6-endo-hydroxyfenchone and 10-hydroxyfenchone by human liver microsomal P450 enzymes. The formation of metabolites was determined by the relative abundance of mass fragments and retention times on gas chromatography (GC). CYP2A6 and CYP2B6 were major enzymes involved in the hydroxylation of (?)-fenchone by human liver microsomes, based on the following lines of evidence. First, of 11 recombinant human P450 enzymes tested, CYP2A6 and CYP2B6 catalysed the oxidation of (?)-fenchone. Second, oxidation of (?)-fenchone was inhibited by thioTEPA and (+)-menthofuran. Finally, there was a good correlation between CYP2A6, CYP2B6 contents and (?)-fenchone hydroxylation activities in liver microsomes of 11 human samples. CYP2A6 may be more important than CYP2B6 in human liver microsomes. Kinetic analysis showed that the V_max/K_m values for (?)-fenchone 6-endo-, 6-exo- and 10-hydroxylation catalysed by liver microsomes of human sample HG-03 were 24.3, 44.0 and 1.3?nM^?1?min^?1, respectively. Human recombinant CYP2A6 and CYP2B6 catalysed (?)-fenchone 6-exo-hydroxylation with V_max values of 2.7 and 12.9?nmol?min^?1?nmol^?1 P450 and apparent K_m values of 0.18 and 0.15?mM and (?)-fenchone 6-endo-hydroxylation with V_max values of 1.26 and 5.33?nmol?min^?1?nmol^?1 P450 with apparent K_m values of 0.29 and 0.26?mM. (?)-Fenchone 10-hydroxylation was catalysed by CYP2B6 with K_m and V_max values of 0.2?mM and 10.66?nmol?min^?1?nmol^?1 P450, respectively.     

Association between blood carisoprodol:meprobamate concentration ratios and CYP2C19 genotype in carisoprodol-drugged drivers: decreased metabolic capacity in heterozygous CYP2C19*1/CYP2C19*2 subjects?

Carisoprodol is metabolized to meprobamate by the cytochrome P450 enzyme CYP2C19, encoded by the polymorphic CYP2C19 gene. Most studies on carisoprodol metabolism have been carried out on individuals phenotyped for CYP2C19 activity using the probe drug S-mephenytoin. We aimed to investigate whether the ratio of carisoprodol to meprobamate in a 'real life' setting could be predicted by CYP2C19 genotype or, more specifically, if high carisoprodol : meprobamate ratios in drugged drivers could be ascribed to the presence of mutant CYP2C19 alleles. From original material comprising 358 blood samples from apprehended drivers, two polarized groups were selected; a high-ratio group of 11 subjects where the carisoprodol : meprobamate ratio was >1 and a low-ratio control group of 23 subjects where the ratio was <0.31. Genotyping was carried out for the CYP2C19*2, CYP2C19*3 and CYP2C19*4 alleles. DNA samples from 94 healthy blood donors were used as reference material. The number of mutant alleles in the high-ratio and low-ratio groups was significantly higher and lower, respectively, than in the reference material. The increased number of mutant alleles in the high-ratio group was not due to the presence of many poor metabolizers, but to a high number of heterozygous individuals with the genotype CYP2C19*1/*2. This result indicates a gene dosage effect where the carisoprodol : meprobamate ratio reflects the number of active CYP2C19 alleles. The metabolism of carisoprodol to meprobamate is dependent on CYP2C19 genotype. Heterozygous individuals with the CYP2C19*1/*2 genotype have a reduced capacity for metabolizing carisoprodol, and should probably be regarded as intermediate metabolizers of this drug.     

In vitro assessment of the roles of drug transporters in the disposition and drug–drug interaction potential of olaparib

1.?In vitro assessments were conducted to examine interactions between olaparib (a potent oral inhibitor of poly[ADP-ribose] polymerase) and drug transporters.

2.?Olaparib showed inhibition of the hepatic drug uptake transporters OATP1B1 (IC₅₀ values of 20.3?μM and 27.1?μM) and OCT1 (IC₅₀ 37.9?μM), but limited inhibition of OATP1B3 (25% at 100?μM); inhibition of the renal uptake transporters OCT2 (IC₅₀ 19.9?μM) and OAT3 (IC₅₀ 18.4?μM), but limited inhibition of OAT1 (13.5% at 100?μM); inhibition of the renal efflux transporters MATE1 and MATE2K (IC₅₀s 5.50?μM and 47.1?μM, respectively); inhibition of the efflux transporter MDR1 (IC₅₀ 76.0?μM), but limited inhibition of BCRP (47% at 100?μM) and no inhibition of MRP2. At clinically relevant exposures, olaparib has the potential to cause pharmacokinetic interactions via inhibition of OCT1, OCT2, OATP1B1, OAT3, MATE1 and MATE2K in the liver and kidney, as well as MDR1 in the liver and GI tract. Olaparib was found to be a substrate of MDR1 but not of several other transporters.

3.?Our assessments indicate that olaparib is a substrate of MDR1 and may cause clinically meaningful inhibition of MDR1, OCT1, OCT2, OATP1B1, OAT3, MATE1 and MATE2K.     

In vitro–in vivo extrapolation of CYP2C8-catalyzed paclitaxel 6α-hydroxylation: effects of albumin on in vitro kinetic parameters and assessment of interindividual variability in predicted clearance

Objectives  

This study aimed to characterize the effects of bovine serum albumin (BSA) on the kinetics of CYP2C8-catalyzed paclitaxel 6α-hydroxylation in vitro; determine whether the addition of BSA to incubations improves the prediction of paclitaxel hepatic clearance via this pathway in vivo; and assess interindividual variability in predicted clearance.     

Clinical utility of drug measurement and pharmacokinetics – therapeutic drug monitoring in psychiatry

Based on the assumption that a relationship between blood levels and clinical effects (therapeutic effects, adverse events and toxicity) can be defined and considering that after equal doses plasma concentrations vary markedly between individual patients, therapeutic drug monitoring (TDM) can assist to personalize dose adjustment. Taken together, drug levels and a knowledge of the pharmacological profile of the administered drugs can enable the optimal dosage to be tailored according to the need of the individual patient. Therapeutic drug monitoring has been established for a limited number of drugs. In psychiatry, it has a 40-year-long history, which started with nortriptyline. Evidence has accumulated which shows that TDM is a valid tool for the optimization of psychopharmacotherapy. When used adequately, TDM is helpful for many patients and in many situations. Combined with pharmacogenetic tests, the metabolic status of a patient can be well characterized. Several new observations have been made during routine TDM that have stimulated clinical pharmacological research, such as investigations on inherited differences in drug metabolism that are closely linked to TDM in psychiatry. The contributions of individual forms of cytochrome P450 (CYP) to the metabolism of drugs was elicited by clinical observations on pharmacokinetic drug interactions. Therapeutic drug monitoring requires a close collaboration between the prescribing physician, the laboratory specialist, the clinical pharmacologist and the patient. This complexity may result in errors which can be detected by analysing the appropriate use of TDM in clinical practice. More education has to be provided to the prescribing clinicians on the pharmacology of the drugs and the algorithm of TDM. Moreover, clinical trials should include measurements of blood concentrations during drug development to generate valid data on the relationships between drug concentrations and clinical outcomes under well-controlled conditions. This would merely increase the amount of work and costs, as high-throughput methods are now available in many laboratories. Any progress in TDM has direct benefits for the treatment of many individual patients.     

Method for predicting the risk of drug–drug interactions involving inhibition of intestinal CYP3A4 and P-glycoprotein

1. To develop a method to predict the risk of drug–drug interactions involving the inhibition of intestinal CYP3A4 or P-glycoprotein, data from clinical drug–drug interaction studies of CYP3A4 and/or P-glycoprotein substrates were analysed. The ratio of inhibitor dose (Dose_i) to inhibition constant (K_i), termed the drug-interaction number, was used to index intestinal drug–drug interaction.

2. From the analysis, it was found that (1) CYP3A4 inhibitors with a drug-interaction number below 2.8?L have a low risk of interacting with substrates which exhibit intestinal first-pass metabolism and those with a drug-interaction number above 9.4?L have a high risk; (2) P-glycoprotein inhibitors with a drug-interaction number below 10.8?L have a low risk of interacting with P-glycoprotein substrates and those with a drug-interaction number above 27.9?L have a high risk; and (3) the drug-interaction number indexes, 2.8?L and 9.4?L for CYP3A4 and 10.8?L and 27.9?L for P-glycoprotein were validated by data from dual CYP3A4/P-glycoprotein substrates.

3. In conclusion, the drug-interaction number is useful for classifying the risk of drug–drug interactions involving the inhibition of intestinal CYP3A4 and P-glycoprotein. This drug-interaction number-based approach is similar to the method that the US Food and Drug Administration (USFDA) recently proposed in the draft guidance for predicting P-glycoprotein-mediated drug–drug interaction.

     

Transport and metabolism of the antitumour drug candidate 2′-benzoyloxycinnamaldehyde in Caco-2 cells

1. The transport and metabolism of the antitumour drug candidate 2′-benzoyloxycinnamaldehyde (BCA) was characterized in Caco-2 cells.

2. BCA disappeared rapidly from the donor side without being transported to the receiver side during its absorptive transport across Caco-2 cells. Its metabolites 2′-hydroxycinnamaldehyde (HCA) and o-coumaric acid (OCA) were formed in both the donor and the receiver sides.

3. HCA, in a separate study, also disappeared rapidly from the donor side, mostly being converted to its oxidative metabolite OCA during its absorptive transport across Caco-2 cells.

4. OCA was transported rapidly in the absorptive direction across Caco-2 cells with a P_app of 25.4?±?1.0?×?10^?6?cm s^?1 (mean?±?standard deviation (SD), n?=?3). OCA was fully recovered from both the donor and the receiver side throughout the time-course of this study.

5. Formation of HCA from BCA was inhibited almost completely by bis(p-nitrophenyl)phosphate (BNPP), a selective inhibitor of carboxylesterases (CES), and phenylmethylsulfonyl fluoride (PMSF), a broad specificity inhibitor of esterases in Caco-2 cells, suggesting that this hydrolytic biotransformation was likely mediated predominantly by CES. Conversion of HCA to OCA was inhibited significantly by isovanillin, a selective inhibitor of aldehyde oxidase (AO). Inhibitors for xanthine oxidase (XO) and aldehyde dehydrogenase (ALDH), which are known to be involved in the oxidation of aldehydes to carboxylic acids, did not have a significant effect on the biotransformation of HCA to OCA in Caco-2 cells.

6. In summary, the present work demonstrates that BCA is hydrolysed rapidly to HCA, followed by subsequent oxidation to OCA, in Caco-2 cells. The results provide a mechanistic understanding of the poor absorption and low bioavailability of BCA after oral administration.

     

Clinical disposition,metabolism and in vitro drug–drug interaction properties of omadacycline

1.?Absorption, distribution, metabolism, transport and elimination properties of omadacycline, an aminomethylcycline antibiotic, were investigated in vitro and in a study in healthy male subjects.

2.?Omadacycline was metabolically stable in human liver microsomes and hepatocytes and did not inhibit or induce any of the nine cytochrome P450 or five transporters tested. Omadacycline was a substrate of P-glycoprotein, but not of the other transporters.

3.?Omadacycline metabolic stability was confirmed in six healthy male subjects who received a single 300?mg oral dose of [¹⁴C]-omadacycline (36.6 μCi). Absorption was rapid with peak radioactivity (～610 ngEq/mL) between 1–4?h in plasma or blood. The AUC_last of plasma radioactivity (only quantifiable to 8?h due to low radioactivity) was 3096 ngEq?h/mL and apparent terminal half-life was 11.1?h. Unchanged omadacycline reached peak plasma concentrations (～563?ng/mL) between 1–4?h. Apparent plasma half-life was 17.6?h with biphasic elimination. Plasma exposure (AUC_inf) averaged 9418?ng?h/mL, with high clearance (CL/F, 32.8?L/h) and volume of distribution (Vz/F 828?L). No plasma metabolites were observed.

4.?Radioactivity recovery of the administered dose in excreta was complete (>95%); renal and fecal elimination were 14.4% and 81.1%, respectively. No metabolites were observed in urine or feces, only the omadacycline C4-epimer.     

Consistency of psychotropic drug–drug interactions listed in drug monographs

Background

With an increasing prevalence of psychotropic polypharmacy, clinicians depend on drug–drug interaction (DDI) references to ensure safe regimens, but the consistency of such information is frequently questioned.

Improvement in the handling of drug–drug interactions

Approximately one in 200 hospitalised patients has a serious adverse drug effect caused by drug–drug interactions (DDIs). Such adverse effects should be avoidable, but current information provided on DDIs is often incomplete and difficult or even impossible to translate into true risk and appropriate tangible action. Clinicians need to know the mean and maximal expected effect of a DDI on clinical endpoints, any dose adjustments required, and how to monitor tolerability and efficacy in patients subject to a DDI. To this end, improved study designs should take the objective of improving treatment explicitly into account, and any existing DDI data should be publicly accessible. Modelling needs to be used more extensively in order to quantitatively predict the effects of DDIs on clinical endpoints in patients and to relate clinical endpoint effects considered as acceptable to respective changes in experimental and clinical studies. Computer-based expert systems will be required to convert such DDI data into recommendations applicable to the individual patient. Therefore, the incorporation of DDIs in a more general procedure for personalisation of drug therapy is desirable.     

Effect of buffer conditions on CYP2C8-mediated paclitaxel 6α-hydroxylation and CYP3A4-mediated triazolam α- and 4-hydroxylation by human liver microsomes

Abstract

1.?Buffer conditions in in vitro metabolism studies using human liver microsomes (HLM) have been reported to affect the metabolic activities of several cytochrome P450 (CYP) isozymes in different ways, although there are no reports about the dependence of CYP2C8 activity on buffer conditions.

2.?The present study investigated the effect of buffer components (phosphate or Tris-HCl) and their concentration (10–200?mM) on the CYP2C8 and CYP3A4 activities of HLM, using paclitaxel and triazolam, respectively, as marker substrates.

3.?The K_m (or S₅₀) and V_max values for both paclitaxel 6α-hydroxylation and triazolam α- and 4-hydroxylation, estimated by fitting analyses based on the Michaelis–Menten or Hill equation, greatly depended on the buffer components and their concentration.

4.?The CL_int values in phosphate buffer were 1.2–3.0-fold (paclitaxel) or 3.1–6.4-fold (triazolam) higher than in Tris-HCl buffer at 50–100?mM. These values also depended on the buffer concentration, with a maximum 2.3-fold difference observed between 50 and 100?mM which are both commonly used in drug metabolism studies.

5.?These findings suggest the necessity for optimization of the buffer conditions in the quantitative evaluation of metabolic clearances, such as in vitro–in vivo extrapolation and also estimating the contribution of a particular enzyme in drug metabolism.     

Recognition and management of potential drug–drug interactions in patients on internal medicine wards

INTRODUCTION: Our aim was to study and possibly improve the clinical management of potential drug-drug interactions (pDDIs) in hospitalized patients by specific interventions. METHODS: During the initial period, inpatients on three medical wards were screened for major and moderate pDDIs using the interaction screening program Pharmavista. During the second period, patients at discharge were screened similarly. After assessment of the detected pDDIs for clinical relevance, written recommendations and/or information about the pDDIs were sent to the treating physicians. Feedback from the physicians and implementation of the recommendations were analyzed. RESULTS: During the initial period, 502 inpatients were exposed to 567 pDDIs, of which 419 (74%) were judged to be clinically relevant. Three hundred and forty-nine substantiated recommendations and 70 simple information leaflets were handed out to the physicians. Eighty percent (278 of 349) of the recommendations were accepted and implemented. During the second period, 792 patients at hospital discharge were exposed to 392 pDDIs, of which 258 (66%) were judged to be clinically relevant. Two hundred and forty-seven substantiated recommendations and 11 simple information leaflets were sent to the physicians. Seventy-three percent (180 of 247) of the recommendations were accepted. At hospital discharge, 47 of 71 interventions recommending checkable medication changes were implemented. One year after hospital discharge, 11 of 13 checked medication changes were still in place. CONCLUSIONS: Clinically relevant pDDIs are common in patients on medical wards, and their management can be influenced by providing substantiated recommendations to physicians. Most changes in medication following such recommendations are still in place 1 year after discharge.