Effect of rifampicin on the pharmacokinetics and pharmacodynamics of glimepiride

A Review of CYP-Mediated Drug Interactions: Mechanisms and In Vitro Drug-Drug Interaction Assessment

Drug metabolism is a major determinant of drug concentrations in the body. Drug-drug interactions (DDIs) caused by the co-administration of multiple drugs can lead to alteration in the exposure of the victim drug, raising safety or effectiveness concerns. Assessment of the DDI potential starts with in vitro experiments to determine kinetic parameters and identify risks associated with the use of comedication that can inform future clinical studies. The diverse range of experimental models and techniques has significantly contributed to the examination of potential DDIs. Cytochrome P450 (CYP) enzymes are responsible for the biotransformation of many drugs on the market, making them frequently implicated in drug metabolism and DDIs. Consequently, there has been a growing focus on the assessment of DDI risk for CYPs. This review article provides mechanistic insights underlying CYP inhibition/induction and an overview of the in vitro assessment of CYP-mediated DDIs.

Tuberculosis and comorbidities: treatment challenges in patients with comorbid diabetes mellitus and depression

Tuberculosis is one of the leading causes of death worldwide, primarily affecting low- and middle income countries and individuals with limited-resources within fractured health care systems. Unfortunately, the COVID-19 pandemic has only served to aggravate the already existing diagnostic gap, decreasing the number of people who get diagnosed and thereby complete successful treatment. In addition to this, comorbidities act as an external component that when added to the TB management equation, renders it even more complex. Among the various comorbidities that interact with TB disease, diabetes mellitus and depression are two of the most prevalent among non-communicable diseases within the TB population and merits a thoughtful consideration when the healthcare system provides care for them. TB patients with diabetes mellitus (TB-DM) or depression both have an increased risk of mortality, relapse and recurrence. Both of these diseases when in presence of TB present a ‘vicious-circle-like’ mechanism, meaning that the effect of each disease can negatively add up, in a synergistic manner, complicating the patient’s health state. Among TB-DM patients, high glucose blood levels can decrease the effectiveness of anti-tuberculosis drugs; however, higher doses of anti-tuberculous drugs could potentially decrease the effects of DM drugs. Among the TB-depression patients, not only do we have the adherence to treatment problems, but depression itself can biologically shift the immunological profile responsible for TB containment, and the other way around, TB itself can alter the hormonal balance of several neurotransmitters responsible for depression. In this paper, we review these and other important aspects such as the pharmacological interactions found in the treatment of TB-DM and TB-depression patients and the implication on TB care and pharmacological considerations.

Hypoglycemia possibly caused by CYP2C9-mediated drug interaction in combination with bucolome: a case report

Background

Bucolome is a non-steroidal anti-inflammatory drug and uricosuric agent, currently used only in Japan. It is known to induce drug interactions by inhibiting cytochrome P450 (CYP) 2C9. It is often used to enhance the anticoagulant effect of warfarin by utilizing its drug interactions. There are only a few reports on drug interactions of bucolome and the mechanism remain poorly understood.

Case presentation

An 81-year-old woman with a history of type 2 diabetes mellitus was taking glimepiride 2 mg/day and voglibose 0.6 mg/day. After hospitalization, the patient underwent surgical aortic valve replacement surgery (day 0). Glimepiride and voglibose were resumed on the second postoperative day (day 2), and warfarin was started to prevent thromboembolism. Since the prothrombin time-international normalized ratio on day 9 was low at 1.24, 300 mg/day of bucolome was added to enhance the effect of warfarin. A gradual decrease in blood glucose levels was observed from the day after bucolome administration was initiated. Hypoglycemia in the 56–57 mg/dL range occurred before lunch and dinner on the 6th day (day 14) of bucolome administration, due to which voglibose was discontinued. Hypoglycemia below 70 mg/dL was not observed thereafter, and the general condition of the patient was stable.

Conclusions

Based on the clinical course and literature review, we believe that hypoglycemia in the present case was due to a drug interaction, caused by inhibition of CYP2C9 by bucolome and competitive inhibition of CYP2C9 by warfarin, which affected the pharmacokinetics of glimepiride. The possibility of hypoglycemia due to drug interactions should be considered by physicians, when bucolome is included to enhance the effect of warfarin, in patients taking glimepiride.

Model-based comparative analysis of rifampicin and rifabutin drug-drug interaction profile

Rifamycins are widely used for treating mycobacterial and staphylococcal infections. Drug-drug interactions (DDI) caused by rifampicin (RIF) is a major issue. We used a model-based approach to predict the magnitude of DDI with RIF and rifabutin (RBT) for 217 cytochrome P450 (CYP) substrates. On average, DDI caused by low-dose RIF were twice more potent than those caused by RBT. Contrary to RIF, RBT appears unlikely to cause severe DDI, even with sensitive CYP substrates.

Effects of rifampicin on plasma pharmacokinetics of tulathromycin in goats

We investigated the pharmacokinetic profile of co-administration of tulathromycin with rifampicin. Healthy male goats were allocated to three groups (n = 8) as Group A (single dose 2.5 mg/kg tulathromycin s.c.), B (10 mg kg^-1  day^-1 rifampicin p.o. daily for 7 days and single dose 2.5 mg/kg tulathromycin s.c. on 8th day), and C (10 mg kg^-1  day^-1 rifampicin p.o. daily for 21 days and single dose 2.5 mg/kg tulathromycin s.c. on 8th day). Blood samples were collected from jugular veins. Plasma samples were analyzed for tulathromycin by liquid chromatography-mass spectrometry (LC-MS/MS). Peak plasma concentration (C_max ) values of tulathromycin were 1,390 ± 173, 958 ± 106, and 807 ± 116 ng/ml in groups A, B, and C, respectively. C_max value of group A was greater than other groups (p < .05). Mean residence time based on time zero to last sample time (MRT_last ) values were 52 ± 1, 56 ± 4 and 66 ± 4 hr in A, B, and C groups, respectively whereas mean residence time based on time zero extrapolated to infinity (MRT_{INF_obs} ) values were 69 ± 4, 85 ± 5, and 86 ± 4 hr, respectively. MRT_last and MRT_{INF_obs} values were greater in B and C groups than group A (p < .05). These findings suggest that rifampicin administration may change several pharmacokinetic parameters of tulathromycin in goats.

Changes in Host Response to Mycobacterium tuberculosis Infection Associated With Type 2 Diabetes: Beyond Hyperglycemia

Tuberculosis (TB) remains as the first cause of death among infectious diseases worldwide. Global incidence of tuberculosis is in part coincident with incidence of type 2 diabetes (T2D). Incidence of T2D is recognized as a high-risk factor that may contribute to tuberculosis dissemination. However, mechanisms which favor infection under T2D are just starting to emerge. Here, we first discuss the evidences that are available to support a metabolic connection between TB and T2D. Then, we analyze the evidences of metabolic changes which occur during T2D gathered thus far for its influence on susceptibility to M. tuberculosis infection and TB progression, such as hyperglycemia, increase of 1AC levels, increase of triglycerides levels, reduction of HDL-cholesterol levels, increased concentration of lipoproteins, and modification of the activity of some hormones related to the control of metabolic homeostasis. Finally, we recognize possible advantages of metabolic management of immunity to develop new strategies for treatment, diagnosis, and prevention of tuberculosis.

Effect of glimepiride on the pharmacokinetics of teneligliptin in healthy Korean subjects

WHAT IS KNOWN AND OBJECTIVE

Teneligliptin is a DPP-4 inhibitor used for the treatment of type 2 diabetes mellitus, commonly prescribed in combination with glimepiride. Teneligliptin is metabolized by CYP3A4, and glimepiride might be partly metabolized by CYP3A4. The aim of the study was to investigate the possible effect of glimepiride on the pharmacokinetics of teneligliptin in healthy subjects.

METHODS

A repeated dose, open-label, fixed-sequence study was conducted in 26 healthy subjects. All participants were administered 20 mg teneligliptin daily for 6 days. On day 7, 4 mg glimepiride was administered together with 20 mg teneligliptin. Plasma teneligliptin concentrations were measured at a steady state, and its pharmacokinetic characteristics were compared without and with glimepiride.

RESULTS AND DISCUSSION

No statistically significant difference was found in the effect of glimepiride on teneligliptin pharmacokinetics. The steady-state C_max,ss values of teneligliptin without and with glimepiride were 207.01 ng/mL and 202.15 ng/mL, respectively. Its AUC_τ values at steady-state without and with glimepiride were 1527.8 ng · h/mL and 1578.6 ng · h/mL, respectively. The point estimation of geometric mean ratios (GMR) and the 90% confidence interval for both C_max,ss and AUC_τ were within the equivalence range of 0.8-1.25. The results of the present study revealed that glimepiride did not cause pharmacokinetic interaction with teneligliptin in humans.

WHAT IS NEW AND CONCLUSION

Glimepiride did not affect the pharmacokinetic characteristics of teneligliptin in healthy subjects.

A Model for Predicting the Interindividual Variability of Drug-Drug Interactions

Pharmacokinetic drug-drug interactions are frequently characterized and quantified by an AUC ratio (Rauc). The typical value of the AUC ratio in case of cytochrome-mediated interactions may be predicted by several approaches, based on in vitro or in vivo data. Prediction of the interindividual variability of Rauc would help to anticipate more completely the consequences of a drug-drug interaction. We propose and evaluate a simple approach for predicting the standard deviation (sd) of Ln(Rauc), a metric close to the interindividual coefficient of variation of Rauc. First, a model was derived to link sd(Ln Rauc) with the substrate fraction metabolized by each cytochrome and the potency of the interactors, in case of induction or inhibition. Second, the parameters involved in these equations were estimated by a Bayesian hierarchical model, using the data from 56 interaction studies retrieved from the literature. Third, the model was evaluated by several metrics based on the fold prediction error (PE) of sd(Ln Rauc). The median PE was 0.998 (the ideal value is 1) and the interquartile range was 0.96-1.03. The PE was in the acceptable interval (0.5 to 2) in 52 cases out of 56. Fourth, a surface plot of sd(Ln Rauc) as a function of the characteristics of the substrate and the interactor has been built. The minimal value of sd(Ln Rauc) was about 0.08 (obtained for Rauc = 1) while the maximal value, 0.7, was obtained for interactions involving highly metabolized substrates with strong interactors.

Coadministration of Rifampin Significantly Reduces Odanacatib Concentrations in Healthy Subjects

This open-label 2-period study assessed the effect of multiple-dose administration of rifampin, a strong cytochrome P450 3A (CYP3A) and P-glycoprotein inducer, on the pharmacokinetics of odanacatib, a cathepsin K inhibitor. In period 1, 12 healthy male subjects (mean age, 30 years) received a single dose of odanacatib 50 mg on day 1, followed by a 28-day washout. In period 2, subjects received rifampin 600 mg/day for 28 days; odanacatib 50 mg was coadministered on day 14. Blood samples for odanacatib pharmacokinetics were collected at predose and on day 1 of period 1 and day 14 of period 2. Coadministration of odanacatib and rifampin significantly reduced odanacatib exposure. The odanacatib AUC_0-∞ geometric mean ratio (90% confidence interval) of odanacatib + rifampin/odanacatib alone was 0.13 (0.11-0.16). The harmonic mean ± jackknife standard deviation apparent terminal half-life (t_½ ) was 71.6 ± 10.2 hours for odanacatib alone and 16.0 ± 3.4 hours for odanacatib + rifampin, indicating greater odanacatib clearance following coadministration with rifampin. Samples were collected in period 2 during rifampin dosing (days 1, 14, and 28) and after rifampin discontinuation (days 35, 42, and 56) to evaluate the ratio of plasma 4β-hydroxycholesterol to total serum cholesterol as a CYP3A4 induction biomarker; the ratio increased ∼5-fold over 28 days of daily dosing with 600 mg rifampin, demonstrating sensitivity to CYP3A4 induction.

The effects of colesevelam HCl on the single-dose pharmacokinetics of glimepiride, extended-release glipizide, and olmesartan medoxomil

Bile acid sequestrants can potentially bind to concomitant drugs. Single-dose studies evaluated the effects of colesevelam on the pharmacokinetics of glimepiride, glipizide extended-release (ER), and olmesartan medoxomil. Each study enrolled healthy subjects aged 18-45 years. The olmesartan medoxomil study used a randomized adaptive crossover design that initially compared olmesartan medoxomil alone versus simultaneously with colesevelam, then olmesartan medoxomil alone versus 4 hours before colesevelam. The other studies used a three-period crossover design (test drug alone, test drug simultaneously with colesevelam, and test drug 4 hours before colesevelam). For the colesevelam coadministration periods, 3,750 mg once daily was dosed throughout the pharmacokinetic sampling period. After each single dose of test drug, serial blood samples were collected for determination of plasma drug concentrations and calculation of pharmacokinetic parameters. Administering colesevelam simultaneously with glimepiride or glipizide ER resulted in minor reductions (18% and 13%, respectively) in total exposure that were negated by staggering colesevelam dosing by 4 hours. Administering colesevelam simultaneously with olmesartan medoxomil resulted in a major reduction (39%) in olmesartan exposure that was reduced by staggering colesevelam dosing by 4 hours. This reduction in olmesartan exposure is not predicted to have a clinically significant impact on blood pressure control.

CYP2C metabolism of oral antidiabetic drugs--impact on pharmacokinetics, drug interactions and pharmacogenetic aspects

INTRODUCTION

The cytochrome P4502C enzymes account for the metabolism of approximately 20% of therapeutic drugs including certain oral antidiabetic drugs (OADs).

AREAS COVERED

This review focuses on the effect of CYP2C enzymes on metabolism of sulphonylureas (SUs), meglitinides, and thiazolidinediones (TZDs) discussing their impact on pharmacokinetics, drug interactions and toxicological profiles. Pharmacogenetic aspects reflecting individual gene variants and variable drug effects are also considered.

EXPERT OPINION

Genetic polymorphisms of CYP2C9 enzymes (*2/*2, *2/*3, *3/*3) influence the glycaemic response to SUs and impair their substrate metabolism. Restricted data from small-sized studies with heterogenous definitions of hypoglycaemia revealed no clear association between CYP2C9 genotypes and the risk of hypoglycaemia. Functional polymorphisms of CYP2C8- and CYP2C9 drug metabolizing genes affect markedly pharmacokinetics of meglitinides. Compared to wild-type carriers, patients treated with TZDs and carrying the common CYP2C8*3 and *4 variants showed a reduced glycaemic control. The strong CYP2C8 and OATP1B1 inhibitor gemfibrozil increases substantially the plasma concentrations of repaglinide and TZDs. Numerous metabolic drug interactions exist between SUs and commonly prescribed drugs, especially anti-infectives. The complex pharmacokinetic and pharmacogenetic properties and the unfavourable short and long term risk profile of glibenclamide and glimepiride raise the question whether their use can be justified any longer.

Drug interactions with oral antidiabetic agents: pharmacokinetic mechanisms and clinical implications

There is a growing epidemic of type 2 diabetes (T2DM), and it is associated with various comorbidities. Patients with T2DM are usually treated with multiple drugs, and are therefore at an increased risk of harmful drug-drug interactions (DDIs). Several potentially life-threatening DDIs concerning oral antidiabetic drugs have been identified. This has mostly been initiated by case reports but, more recently, the understanding of their mechanisms has greatly increased. In this article, we review the pharmacokinetic DDIs concerning oral antidiabetics, including metformin, sulfonylureas, meglitinide analogs, thiazolidinediones and dipeptidyl peptidase-4 inhibitors, and the underlying mechanistic basis that can help to predict and prevent DDIs. In particular, the roles of membrane transporters and cytochrome P450 (CYP) enzymes in these DDIs are discussed.

Pharmacokinetic drug interactions of antimicrobial drugs: a systematic review on oxazolidinones, rifamycines, macrolides, fluoroquinolones, and Beta-lactams

Like any other drug, antimicrobial drugs are prone to pharmacokinetic drug interactions. These drug interactions are a major concern in clinical practice as they may have an effect on efficacy and toxicity. This article provides an overview of all published pharmacokinetic studies on drug interactions of the commonly prescribed antimicrobial drugs oxazolidinones, rifamycines, macrolides, fluoroquinolones, and beta-lactams, focusing on systematic research. We describe drug-food and drug-drug interaction studies in humans, affecting antimicrobial drugs as well as concomitantly administered drugs. Since knowledge about mechanisms is of paramount importance for adequate management of drug interactions, the most plausible underlying mechanism of the drug interaction is provided when available. This overview can be used in daily practice to support the management of pharmacokinetic drug interactions of antimicrobial drugs.

Implications of the global increase of diabetes for tuberculosis control and patient care

OBJECTIVES

To review the current knowledge about tuberculosis (TB) and diabetes, assessing the implication of the global increase of diabetes for TB control and patient care.

METHODS

Systematic literature review.

RESULTS

Using public databases, it can be estimated that 12.6% (95% CI 9.2-17.3%) of new TB cases in the 10 countries with the highest TB burden will be attributable to TB in 2030, a relative increase of 25.5% compared to 2010. Diabetes is associated with a higher age and body weight among patients with TB, but probably not with a specific clinical presentation of TB. Rifampicin hampers glycemic control by increasing the metabolism of most oral antidiabetic drugs, while diabetes patients may have lower concentrations of anti-TB drugs. This might be one factor contributing to higher TB treatment failure rates.

CONCLUSIONS

The global epidemic of diabetes has implications for control and treatment of TB. Prospective studies are needed to improve prevention, early detection and treatment of concomitant diabetes and TB, especially in developing countries.

Lack of pharmacokinetic interaction between dapagliflozin, a novel sodium-glucose transporter 2 inhibitor, and metformin, pioglitazone, glimepiride or sitagliptin in healthy subjects

AIMS

Dapagliflozin increases urinary glucose excretion by selectively inhibiting renal sodium-glucose transporter 2, an insulin-independent mechanism of action that may be complementary to that of other oral antidiabetes drugs. The current studies assessed the potential for pharmacokinetic (PK) interaction between dapagliflozin and pioglitazone, metformin, glimepiride or sitagliptin in healthy subjects following single-dose administration.

METHODS

In open-label, randomized, three-period, three-treatment crossover studies, 24 subjects received 50 mg dapagliflozin, 45 mg pioglitazone or the combination, while 18 subjects received 20 mg dapagliflozin, 1000 mg metformin or the combination. In an open-label, randomized, five-period, five-treatment, unbalanced crossover study, 18 subjects first received 20 mg dapagliflozin, 4 mg glimepiride or the combination, and afterward 100 mg sitagliptin or sitagliptin plus 20 mg dapagliflozin. Blood samples were taken over 72 h of each treatment period. Lack of PK interaction was defined as the ratio of geometric means and 90% confidence interval (CI) for combination:monotherapy being within the range of 0.80-1.25.

RESULTS

Co-administration of dapagliflozin with pioglitazone, metformin, glimepiride or sitagliptin had no effect on dapagliflozin maximum plasma concentration (C(max) ) or area under the plasma concentration-time curve (AUC). Similarly, dapagliflozin did not affect the C(max) or AUC for the co-administered drug, except for slight extensions of the 90% CI for the ratio of geometric means for glimepiride AUC (upper limit 1.29) and pioglitazone C(max) (lower limit 0.75). All monotherapies and combination therapies were well tolerated.

CONCLUSION

Dapagliflozin can be co-administered with pioglitazone, metformin, glimepiride or sitagliptin without dose adjustment of either drug.

Glimepiride-Induced Hypoglycemia with Ciprofloxacin, Metronidazole, and Acute Kidney Injury

A 79-year-old white male presented to the emergency room with altered mental status and a blood glucose of 28 mg/dL. He was taking glimepiride 1 mg by mouth daily prior to admission and had recently been prescribed ciprofloxacin and metronidazole for diverticulitis. The patient was also found to have acute-on-chronic renal failure upon presentation. Escalated dextrose infusion with repeated doses of D50W and glucagon failed to sustain his blood glucose, which remained in the range of 30 to 50 mg/dL. Salvage treatment with intravenous octreotide was implemented successfully; only one dose of D50W was required after octreotide initiation and blood glucose normalized within several hours. In the presence of this patient's complex medication therapy, we explore the contributing causes of hypoglycemia. Fluoroquinolones are widely associated with dysglycemias, particularly in diabetic patients receiving hypoglycemic agents. Similarly, renal insufficiency has been implicated to precipitate hypoglycemia with sulfonylureas, with dosage adjustment being required almost class-wide. We also recognize a theoretical drug interaction mediated by metronidazole-induced CYP 2C9 inhibition of glimepiride metabolism. Sulfonylurea-induced hypoglycemia can be serious and refractory to traditional therapy and can be exacerbated by multiple factors, such as drug interactions or impaired renal function. In the era of complex medication therapy for patient populations with multiple disease states, we present a severe episode of glimepiride-induced hypoglycemia with multiple causative factors.

Biological potential study of metal complexes of sulphonylurea glibenclamide on the house fly, Musca domestica (Diptera-Muscidae): preparation, spectroscopic and thermal characterization

The ligatation behaviour of sulphonylurea glibenclamide drug is studied in order to give an idea about its potentiality towards some transition metals in vitro systems. Metal complexes of glibenclamide (GCA; H(3)L) drug are prepared and characterized based on elemental analyses, IR, diffused reflectance, magnetic moment, molar conductance and thermal analysis (TG and DTG) techniques. From the elemental analyses data, the complexes are proposed to have the general formulae [M(H(3)L)Cl(n)(H(2)O)(m)].yH(2)O (where M=Cr(III) (n=3, m=1, y=3); Mn(II) (n=2, m=0, y=1); Fe(III) (n=3, m=1, y=0), Co(II) (n=2, m=2, y=0); Ni(II) (n=2, m=2, y=3); Cu(II) (n=2, m=2, y=2) and Zn(II) (n=2, m=0, y=0). The molar conductance data reveal that all the metal chelates are non-electrolytes. IR spectra show that GCA is coordinated to the metal ions in a neutral bidentate manner with OO donor sites of the amide-O and sulphone-O. From the magnetic and solid reflectance spectra, it is found that the geometrical structures of these complexes are octahedral except Mn(II) and Zn(II) complexes which have tetrahedral structure. The thermal behaviour of these chelates is studied using thermogravimetric analysis (TG and DTG) technique. The activation thermodynamic parameters are calculated using Coats-Redfern method. The GCA drug, in comparison to its metal complexes also is screened for its biological activity against house fly, Musca domestica (Diptera-Muscidae). Dose of 5 microg/insect of GCA is topically applied against 3 days old larval instar of M. domestica. Survival of pupal and adult stages has been affected by the complexes of GCA more than larval instars. Morphogenic abnormalities of larvae, pupae and adults are studied. On the other hand pupation and adult emergence program is deteriorated by the effect of different chemicals.

Oral antidiabetic drug metabolism: pharmacogenomics and drug interactions

BACKGROUND

Type 2 diabetes is progressive in nature and so to control cardiovascular risk, most patients need combinations of oral antidiabetic drugs (OADs) plus or minus insulin. Thus, drug-drug interactions may substantially contribute to harmful effects of intensive glucose lowering therapy.

METHODS

A PubMed literature search was performed to select the most recent and relevant publications examining OAD metabolism and the effects of concomitant use of OADs.

RESULTS/CONCLUSION

Considering the individual sensitivity to OADs, pharmacogenetic factors could be of critical importance. The therapeutic range and efficacy as well as adverse effects of OADs may be significantly affected by genetic polymorphisms of cytochrome P450 drug metabolising enzymes, organic cation transporters or organic anion transporting polypeptides. Although current data suggest that modest pharmacokinetics interferences among some OAD combinations exist, they do not seem to have substantial clinical consequences. As long-term adherence to multi-drug treatment is poor in diabetic patients, the future will show a strong move towards earlier treatment with combination therapies. As metformin is cardiovascular protective and is not metabolised through the hepatic cytochrome P450 system, it is a key compound for any OAD combination. There is an overwhelming amount of small-sized in vitro studies and investigations mostly including healthy volunteers dealing with short-term effects and surrogate parameters of concomitant OAD use. Further evidence from large-scale studies including typical subjects with type 2 diabetes, in particular multimorbid and geriatric patients with polypharmacy, is needed. Postmarketing surveillance using large patients' registries could be helpful to improve the early detection of clinically relevant drug-drug interactions.

Relative impact of genotype and enzyme induction on the metabolic capacity of CYP2C9 in healthy volunteers

Pharmacokinetics in individual subjects is determined by genes and environment. The relative contributions of enzyme induction and inherited genomic variation to cytochrome P450 enzyme 2C9 (CYP2C9) activity are unknown. In 130 volunteers, CYP2C9 activity was measured in vivo using tolbutamide as a probe drug. Tolbutamide was administered orally, and the pharmacokinetics of the drug was analyzed twice--before and after four doses of 450 mg rifampin. Mean total apparent clearances (Cl/F) in the genotype groups CYP2C9*1/*1, *1/*2, *1/*3, *2/*3, and *3/*3 before rifampin were 0.78, 0.74, 0.52, 0.40, and 0.13 l/h, respectively. After rifampin administration, these clearances increased in all genotype groups by a median factor of 1.9 (range 1.1-4.8). The combined effects of genes and environment could be predicted by a simple additive model. Thus, enzyme induction resulted in an approximately twofold difference in CYP2C9 activity, irrespective of the CYP2C9 genotypes. But the difference in activity levels between the CYP2C9*1/*1 and *3/*3 genotypes before the administration of rifampin was sixfold.

Update on rifampin and rifabutin drug interactions

Rifampin is a potent inducer of cytochrome P-450 oxidative enzymes as well as the P-glycoprotein transport system. Several examples of well-documented clinically significant interactions include warfarin, oral contraceptives, cyclosporine, itraconazole, digoxin, verapamil, nifedipine, simvastatin, midazolam, and human immunodeficiency virus-related protease inhibitors. Rifabutin reduces serum concentrations of antiretroviral agents, but less so than rifampin. Examples of clinically relevant interactions demonstrated by recent reports include everolimus, atorvastatin, rosiglitazone/pioglitazone, celecoxib, clarithromycin, caspofungin, and lorazepam. To avoid a decreased therapeutic response, therapeutic failure, or toxic reactions when rifampin is added to or discontinued from medication regimens, clinicians need to be cognizant of these interactions. Studies and cases of rifampin drug interactions continue to increase rapidly. This review is a timely reminder to clinicians to be vigilant.

Drug interactions of clinical importance with antihyperglycaemic agents: an update

Because management of type 2 diabetes mellitus usually involves combined pharmacological therapy to obtain adequate glucose control and treatment of concurrent pathologies (especially dyslipidaemia and arterial hypertension), drug-drug interactions must be carefully considered with antihyperglycaemic drugs. Additive glucose-lowering effects have been extensively reported when combining sulphonylureas (or the new insulin secretagogues, meglitinide derivatives, i.e. nateglinide and repaglinide) with metformin, sulphonylureas (or meglitinide derivatives) with thiazolidinediones (also called glitazones) and the biguanide compound metformin with thiazolidinediones. Interest in combining alpha-glucosidase inhibitors with either sulphonylureas (or meglitinide derivatives), metformin or thiazolidinediones has also been demonstrated. These combinations result in lower glycosylated haemoglobin (HbA(1c)), fasting glucose and postprandial glucose levels than with either monotherapy. Even if modest pharmacokinetic interferences have been reported with some combinations, they do not appear to have important clinical consequences. No significant adverse effects, except a higher risk of hypoglycaemic episodes that may be attributed to better glycaemic control, occur with any combination. Challenging the classical dual therapy with sulphonylurea plus metformin, there is a recent trend to use alternative dual combinations (sulphonylurea plus thiazolidinedione or metformin plus thiazolidinedione). In addition, triple therapy with the addition of a thiazolidinedione to the metformin-sulphonylurea combination has been recently evaluated and allows glucose targets to be reached before insulin therapy is considered. This triple therapy appears to be safe, with no deleterious drug-drug interactions being reported so far.Potential interferences may also occur between glucose-lowering agents and other drugs, and such drug-drug interactions may have important clinical implications. Relevant pharmacological agents are those that are widely coadministered in diabetic patients (e.g. lipid-lowering agents, antihypertensive agents); those that have a narrow efficacy/toxicity ratio (e.g. digoxin, warfarin); or those that are known to induce (rifampicin [rifampin]) or inhibit (fluconazole) the cytochrome P450 (CYP) system. Metformin is currently a key compound in the pharmacological management of type 2 diabetes, used either alone or in combination with other antihyperglycaemics. There are no clinically relevant metabolic interactions with metformin, because this compound is not metabolised and does not inhibit the metabolism of other drugs. In contrast, sulphonylureas, meglitinide derivatives and thiazolidinediones are extensively metabolised in the liver via the CYP system and thus, may be subject to drug-drug metabolic interactions. Many HMG-CoA reductase inhibitors (statins) are also metabolised via the CYP system. Even if modest pharmacokinetic interactions may occur, it is not clear whether drug-drug interactions between oral antihyperglycaemic agents and statins may have clinical consequences regarding both efficacy and safety. In contrast, a marked pharmacokinetic interference has been reported between gemfibrozil and repaglinide and, to a lesser extent, between gemfibrozil and rosiglitazone. This leads to a drastic increase in plasma concentrations of each antihyperglycaemic agent when they are coadministered with the fibric acid derivative, and an increased risk of adverse effects. Some antihypertensive agents may favour hypoglycaemic episodes when co-prescribed with sulphonylureas or meglitinide derivatives, especially ACE inhibitors, but this effect seems to result from a pharmacodynamic drug-drug interaction rather than from a pharmacokinetic drug-drug interaction. No, or only modest, interferences have been described with glucose-lowering agents and other pharmacological compounds such as digoxin or warfarin. The effects of inducers or inhibitors of CYP isoenzymes on the metabolism and pharmacokinetics of the glucose-lowering agents of each pharmacological class has been tested. Significantly increased (with CYP inhibitors) or decreased (with CYP inducers) plasma levels of sulphonylureas, meglitinide derivatives and thiazolidinediones have been reported in healthy volunteers, and these pharmacokinetic changes may lead to enhanced or reduced glucose-lowering action, and thus hypoglycaemia or worsening of metabolic control, respectively. In addition, some case reports have evidenced potential drug-drug interactions with various antihyperglycaemic agents that are usually associated with a higher risk of hypoglycaemia.

Effect of rifampicin on the pharmacokinetics of pioglitazone

AIMS

The effect of enzyme induction on the pharmacokinetics of pioglitazone, a thiazolidinedione antidiabetic drug that is metabolized primarily by CYP2C8, is not known. Rifampicin is a potent inducer of several CYP enzymes and our objective was to study its effects on the pharmacokinetics of pioglitazone in humans.

METHODS

In a randomized, two-phase crossover study, ten healthy subjects ingested either 600 mg rifampicin or placebo once daily for 6 days. On the last day, they received a single oral dose of 30 mg pioglitazone. The plasma concentrations and cumulative excretion of pioglitazone and its active metabolites M-IV and M-III into urine were measured up to 48 h.

RESULTS

Rifampicin decreased the mean total area under the plasma concentration-time curve (AUC(0-infinity)) of pioglitazone by 54% (range 20-66%; P = 0.0007; 95% confidence interval -78 to -30%) and shortened its dominant elimination half-life (t(1/2)) from 4.9 to 2.3 h (P = 0.0002). No significant effect on peak concentration (C(max)) or time to peak (t(max)) was observed. Rifampicin increased the apparent formation rate of M-IV and shortened its t(max) (P < 0.01). It also decreased the AUC(0-infinity) of M-IV (by 34%; P = 0.0055) and M-III (by 39%; P = 0.0026), shortened their t1/2 (M-IV by 50%; P = 0.0008, and M-III by 55%; P = 0.0016) and increased the AUC(0-infinity) ratios of M-IV and M-III to pioglitazone by 44% (P = 0.0011) and 32% (P = 0.0027), respectively. Rifampicin increased the M-IV/pioglitazone and M-III/pioglitazone ratios in urine by 98% (P = 0.0015) and 95% (P = 0.0024). A previously unrecognized metabolite M-XI, tentatively identified as a dihydroxy metabolite, was detected in urine during both phases, and rifampicin increased the ratio of M-XI to pioglitazone by 240% (P = 0.0020).

CONCLUSIONS

Rifampicin caused a substantial decrease in the plasma concentration of pioglitazone, probably by induction of CYP2C8. Concomitant use of rifampicin with pioglitazone may decrease the efficacy of the latter drug.

CYP Induction-Mediated Drug Interactions: in Vitro Assessment and Clinical Implications

Cytochrome P450 (CYP) induction-mediated interaction is one of the major concerns in clinical practice and for the pharmaceutical industry. There are two major issues associated with CYP induction: a reduction in therapeutic efficacy of comedications and an induction in reactive metabolite-induced toxicity. Because CYP induction is a metabolic liability in drug therapy, it is highly desirable to develop new drug candidates that are not potent CYP inducer to avoid the potential of CYP induction-mediated drug interactions. For this reason, today, many drug companies routinely include the assessment of CYP induction at the stage of drug discovery as part of the selection processes of new drug candidates for further clinical development. The purpose of this article is to review the molecular mechanisms of CYP induction and the clinical implications, including pharmacokinetic and pharmacodynamic consequences. In addition, factors that affect the degree of CYP induction and extrapolation of in vitro CYP induction data to in vivo situations will also be discussed. Finally, assessment of the potential of CYP induction at the drug discovery and development stage will be discussed.

The role of sulphonylureas in the management of type 2 diabetes mellitus

The sulphonylureas act by triggering insulin release from the pancreatic beta cell. A specific site on the adenosine triphosphate (ATP)-sensitive potassium channels is occupied by sulphonylureas leading to closure of the potassium channels and subsequent opening of calcium channels. This results in exocytosis of insulin. The meglitinides are not sulphonylureas but also occupy the sulphonylurea receptor unit coupled to the ATP-sensitive potassium channel. Glibenclamide (glyburide), gliclazide, glipizide and glimepiride are the primary sulphonylureas in current clinical use for type 2 diabetes mellitus. Glibenclamide has a higher frequency of hypoglycaemia than the other agents. With long-term use, there is a progressive decrease in the effectiveness of sulphonylureas. This loss of effect is the result of a reduction in insulin-producing capacity by the pancreatic beta cell and is also seen with other antihyperglycaemic agents. The major adverse effect of sulphonylureas is hypoglycaemia. There is a theoretical concern that sulphonylureas may affect cardiac potassium channels resulting in a diminished response to ischaemia. There are now many choices for initial therapy of type 2 diabetes in addition to sulphonylureas. Metformin and thiazolidinediones affect insulin sensitivity by independent mechanisms. Disaccharidase inhibitors reduce rapid carbohydrate absorption. No single agent appears capable of achieving target glucose levels in the majority of patients with type 2 diabetes. Combinations of agents are successful in lowering glycosylated haemoglobin levels more than with a single agent. Sulphonylureas are particularly beneficial when combined with agents such as metformin that decrease insulin resistance. Sulphonylureas can also be given with a basal insulin injection to provide enhanced endogenous insulin secretion after meals. Sulphonylureas will continue to be used both primarily and as part of combined therapy for most patients with type 2 diabetes.

Pharmacokinetic interactions with rifampicin : clinical relevance

The antituberculosis drug rifampicin (rifampin) induces a number of drug-metabolising enzymes, having the greatest effects on the expression of cytochrome P450 (CYP) 3A4 in the liver and in the small intestine. In addition, rifampicin induces some drug transporter proteins, such as intestinal and hepatic P-glycoprotein. Full induction of drug-metabolising enzymes is reached in about 1 week after starting rifampicin treatment and the induction dissipates in roughly 2 weeks after discontinuing rifampicin. Rifampicin has its greatest effects on the pharmacokinetics of orally administered drugs that are metabolised by CYP3A4 and/or are transported by P-glycoprotein. Thus, for example, oral midazolam, triazolam, simvastatin, verapamil and most dihydropyridine calcium channel antagonists are ineffective during rifampicin treatment. The plasma concentrations of several anti-infectives, such as the antimycotics itraconazole and ketoconazole and the HIV protease inhibitors indinavir, nelfinavir and saquinavir, are also greatly reduced by rifampicin. The use of rifampicin with these HIV protease inhibitors is contraindicated to avoid treatment failures. Rifampicin can cause acute transplant rejection in patients treated with immunosuppressive drugs, such as cyclosporin. In addition, rifampicin reduces the plasma concentrations of methadone, leading to symptoms of opioid withdrawal in most patients. Rifampicin also induces CYP2C-mediated metabolism and thus reduces the plasma concentrations of, for example, the CYP2C9 substrate (S)-warfarin and the sulfonylurea antidiabetic drugs. In addition, rifampicin can reduce the plasma concentrations of drugs that are not metabolised (e.g. digoxin) by inducing drug transporters such as P-glycoprotein. Thus, the effects of rifampicin on drug metabolism and transport are broad and of established clinical significance. Potential drug interactions should be considered whenever beginning or discontinuing rifampicin treatment. It is particularly important to remember that the concentrations of many of the other drugs used by the patient will increase when rifampicin is discontinued as the induction starts to wear off.

Effect of rifampicin on the pharmacokinetics and pharmacodynamics of nateglinide in healthy subjects

AIMS

Our aim was to investigate the effects of rifampicin on the pharmacokinetics and pharmacodynamics of nateglinide, a novel short-acting antidiabetic drug.

METHODS

In a randomized crossover study with two phases, 10 healthy volunteers took 600 mg rifampicin or placebo orally once daily for 5 days. On day 6 of both phases, they ingested a single 60 mg dose of nateglinide. Plasma nateglinide and blood glucose concentrations were measured for up to 7 h postdose.

RESULTS

Rifampicin decreased the mean AUC(0,7 h) of nateglinide by 24% (range 5-53%; P = 0.0009) and shortened its half-life (t(1/2)) from 1.6 to 1.3 h (P = 0.001). However, the peak plasma nateglinide concentration (Cmax) remained unchanged. The AUC(0,7 h) of the M7 metabolite of nateglinide was decreased by 19% (P = 0.002) and its t(1/2) was shortened from 2.1 to 1.6 h by rifampicin (P = 0.008). Rifampicin had no significant effect on the blood glucose-lowering effect of nateglinide.

CONCLUSIONS

Rifampicin modestly decreased the plasma concentrations of nateglinide probably by inducing its oxidative biotransformation. In some patients, rifampicin may reduce the blood glucose-lowering effect of nateglinide.