Clin Pharmacokinet DOI 10.1007/s40262-015-0270-6

REVIEW ARTICLE

A Comprehensive Review of Drug–Drug Interactions with Metformin Tore Bjerregaard Stage1 • Kim Brøsen1 • Mette Marie Hougaard Christensen1

 Springer International Publishing Switzerland 2015

Abstract Metformin is the world’s most commonly used oral glucose-lowering drug for type 2 diabetes, and this is mainly because it protects against diabetes-related mortality and all-cause mortality. Although it is an old drug, its mechanism of action has not yet been clarified and its pharmacokinetic pathway is still not fully understood. There is considerable inter-individual variability in the response to metformin, and this has led to many drug–drug interaction (DDI) studies of metformin. In this review, we describe both in vitro and human interaction studies of metformin both as a victim and as a perpetrator. We also clarify the importance of including pharmacodynamic end points in DDI studies of metformin and taking pharmacogenetic variation into account when performing these studies to avoid hidden pitfalls in the interpretation of DDIs with metformin. This evaluation of the literature has revealed holes in our knowledge and given clues as to where future DDI studies should be focused and performed.

1 Introduction Type 2 diabetes (T2D) is mainly a lifestyle disease, with a minor genetic component and both the prevalence and incidence is increasing. The disease is associated with an increased risk of cardiovascular complications and mortality. While lifestyle modification can help in both the prevention and treatment quite significantly [1, 2], pharmacological treatment is often indicated. Metformin is the most & Tore Bjerregaard Stage [email protected] 1

Clinical Pharmacology, Department of Public Health, University of Southern Denmark, J.B. Winsloews vej 19, 2nd Floor, 5000 Odense, Denmark

commonly prescribed oral antidiabetic drug in the world, and it works primarily by reducing hepatic glucose production through a complex mechanism of action [3–6], which is still widely debated. Thus, treatment with metformin leads to lower blood sugar levels, with only a minimal risk of hypoglycaemia. Metformin is the only oral glucose-lowering drug that has been shown to decrease allcause mortality in obese patients with T2D [7], it is weight neutral [8], and it does not cause hypoglycaemia, which consolidates its place as the first choice for treatment of T2D. However, metformin is sufficient as monotherapy in only one third of patients [9], and we have shown a large variation in the pharmacokinetics and the response to metformin in individuals with T2D [10]. As metformin is not metabolized but is excreted unchanged via the kidneys [11], kidney function can affect metformin pharmacokinetics. Because it is not metabolized, metformin was not expected to be involved in many drug–drug interactions (DDIs). This led to the belief that the observed variation in the pharmacokinetics and the response could be caused by genetic variations in transporters involved in metformin disposition, which has been summarized in previous literature reviews [12–14]. While a recent study indicated that heritability of the response to metformin is 34 % [15], heritability of metformin pharmacokinetics is most likely much lower, as was indicated in a recent twin study [16]. It is therefore likely that variation caused by DDIs is more important than has hitherto been anticipated. It is well known that patients with T2D suffer from several co-morbid conditions and ingest a wide array of co-medications [17]. Further, pharmacokinetic variation could cause the rare, serious side effect lactic acidosis. This supports the relevance of investigating possible DDIs with oral glucose-lowering drugs. Metformin is not completely absorbed from the gut. Its bioavailability (F) is only 40–60 %, and it reaches a

T. B. Stage et al. Fig. 1 Overview of transporters relevant to drug– drug interactions with metformin. MATE multidrug and toxin extrusion transporter, OCT organic cation transporter, PMAT plasma membrane monoamine transporter

maximum plasma concentration (Cmax) after 2–3 h [18]. When absorbed, metformin is neither metabolized in the liver nor excreted in the faeces; it is excreted unchanged through the kidneys and has renal clearance (CLR) of approximately 30 L/h and apparent total oral clearance (CL/ F) of approximately 65–70 L/h [18]. The elimination of metformin is biphasic, with an initial elimination half-life (t‘) of 4–5 h and a longer terminal t‘ [18]. As metformin is a strong base and hence a cation at physiological pH, it is dependent on drug transporters in order to be absorbed, distributed and excreted. There are three different families of transporters involved in the transport of metformin: organic cation transporters (OCTs) [19], multidrug and toxin extrusion transporters (MATEs) [20] and plasma membrane monoamine transporter (PMAT) [21]. In the intestine, OCT1 [22], OCT3 [19] and PMAT [21] are responsible for the uptake of metformin into the bloodstream. More recently, serotonin transporter and choline high-affinity transporter have also been described as being involved in the absorption of metformin [23]. Paracellular absorption has also been described [24], which might be an important factor in intestinal uptake of metformin. In the hepatocytes, OCT1 [22] and OCT3 [25] mediate hepatic uptake of metformin [26]. As metformin is a small molecule, it is filtrated freely by glomerular secretion; however, as its CLR is much higher than the glomerular filtration rate, it is also secreted in the proximal tubules. In the kidneys, OCT2, MATE1 and MATE2-K are involved in the excretion of metformin to the urine [27]. An overview of transporters

relevant to DDIs with metformin is shown in Fig. 1. Drugs that inhibit or induce the transporters have the potential to interfere with the transport of metformin and ultimately affect both plasma and intracellular concentrations of metformin. In this review, we give an overview of the currently available literature regarding DDIs that involve metformin. We go through both in vitro and human pharmacokinetic and/or pharmacodynamic studies, and we assess the clinical relevance of these interactions and pharmacogenetic influence on these DDIs. Finally, we give an overview of possible interactions that need further investigation.

2 Methods We performed searches on PubMed, Medline and Embase, combining the following search terms: ‘metformin’, ‘pharmacokinetics’, ‘pharmacodynamics’, ‘drug interactions’, ‘drug–herb interactions’ and ‘in vitro’. We excluded all studies that did not involve metformin as a substrate, perpetrator or victim.

3 In Vitro DDIs with Metformin As human DDI studies are expensive and time consuming, in vitro studies can be used as an indicator of whether a human study is required. The US Food and Drug

Metformin Drug–Drug Interactions

Administration (FDA) has suggested that it is worth considering a clinical transporter-based DDI study if the in vitro I/IC50 (maximum plasma unbound inhibitor concentration/half-maximal inhibitory concentration of the inhibitor) value is C0.1 [28]. The European Medicines Agency (EMA) has suggested that in vivo inhibition can be excluded if the inhibition constant (Ki) is higher than or equal to the local concentration (defined as [intestinal concentration] = (0.1 9 maximum oral dose)/250 mL; [hepatic concentration] = 25 9 [maximum unbound hepatic inlet concentration]; [renal concentration] = 50 9 [unbound Cmax]) [29]. In this review, we focus on in vitro studies that have used metformin as a substrate for OCT transport, as other OCT substrates might not be representative thereof [30]. Further, in this section, we include only DDIs that are found in vitro and are believed to be of clinical relevance. Thus, this section is not totally exhaustive. In vitro–in vivo extrapolation is complex for multifaceted transporter substrates such as metformin. Thus, it has been estimated that when multiple transporters are involved in the transport of a substrate, the total exposure will change only to a minor extent when only one transporter is inhibited [31]. This means that even strong inhibition of one transporter in vitro will not necessarily lead to a pharmacokinetic change in vivo. An alphabetical overview of in vitro studies of metformin and I/IC50, using the IC50 values obtained in the referenced studies and clinically obtained maximal plasma concentrations from the literature, is shown in Table 1. 3.1 Other Antidiabetic Drugs The glucose-lowering drugs repaglinide and rosiglitazone both inhibit OCT1; however, only repaglinide leads to I/ IC50 values [0.1, as rosiglitazone is highly bound to plasma proteins [32]. Thus, repaglinide could theoretically affect the intestinal and hepatic uptake of metformin, which may alter the effect of metformin. The antidiabetic drug sitagliptin has been shown to inhibit both OCT1- and OCT2-mediated transport of metformin [33]. The I/Ki values were slightly above 0.1 for both transporters, which indicated that there might be a minor interaction between the two drugs. A clinical study showed no influence on metformin pharmacokinetics, but, as the study did not measure any pharmacodynamic end points, the presence of a pure pharmacodynamic interaction cannot be excluded [34].

flecainide, amiodarone and quinidine) inhibit the transport of metformin via OCT1, OCT2 and OCT3 to some extent [35]. However, all of the observed IC50 values were below the observed in vivo concentrations and thus are not likely to be clinically relevant. This finding was supported by another study that examined the effect of four beta-blockers (bisoprolol, carvedilol, metoprolol and propranolol) on OCT2-mediated transport of metformin [36]. Thus, no clinically relevant DDIs between metformin and betablockers are expected. The antiplatelet drug clopidogrel, its metabolite clopidogrel carboxylate and the anti-arrhythmic drug quinidine inhibit OCT1-mediated uptake of metformin [37]. As the t‘ of clopidogrel is very short, the time above the IC50 is very brief, and we do not expect this substrate to affect metformin transport significantly. However, clopidogrel carboxylate has a longer t‘ (*10 h) and, as the I/IC50 is close to 0.1, it may affect hepatic uptake and thus the effect of metformin to a minor extent. Quinidine has a I/IC50 [0.1 and thus may affect OCT1-mediated metformin transport (the quinidine IC50 was higher than observed previously [35] and described above). Finally, clopidogrel carboxylate is a weak inhibitor of OCT2-mediated uptake of metformin. This is at very high concentrations (100 lM) and is not likely to be clinically relevant. 3.3 Gastric Acid–Reducing Agents Five gastric acid–reducing proton pump inhibitors (PPIs) (omeprazole, pantoprazole, lansoprazole, rabeprazole and tenatoprazole) have been shown to inhibit metformin uptake by OCT1, OCT2 and OCT3 in a concentration-dependent manner, even though they are not substrates of any OCTs [38]. For most PPIs, the IC50 is below the clinical Cmax; however, because of high protein binding, which leads to low unbound concentrations, it is uncertain whether PPIs inhibit OCTs in vivo. 3.4 Antibiotics In a recent study, in vitro inhibition of OCT1, OCT2, MATE1 and MATE2-K by the antibiotic trimethoprim was investigated [39]. Trimethoprim showed competitive inhibition of OCT2, MATE1 and MATE2-K, which led to I/ IC50 values above 0.1; in particular, MATE2-K was inhibited with an I/IC50 of 24. OCT1 was inhibited in a noncompetitive manner. 3.5 Anticancer Drugs

3.2 Drugs that Affect the Cardiovascular System A large group of cardiovascular agents (propranolol, metoprolol, pindolol, atenolol, oxprenolol, diltiazem,

Four different anticancer drugs that belong to the tyrosine kinase inhibitor group have been shown to inhibit relevant metformin transporters [40]. Imatinib, nilotinib, gefitinib

OCT1 and OCT2

MDCK

Clopidogrel and clopidogrel carboxylate

HEK293

MDCK HEK293 MDCK

HEK293

Proton pump inhibitors

Repaglinide and rosiglitazone

Screening of 910 cationic compounds

Sitagliptin

Trimethoprim

Quinidine

OCT1, OCT2 and OCT3

HEK293

Cardiovascular agents

OCT1, OCT2, MATE1 and MATE2-K

OCT1 and OCT2

OCT1, OCT2, MATE1 and MATE2-K

OCT1

OCT1, OCT2 and OCT3

OCT1 and OCT2

HEK293

Berberine

Transporters

Cell system

Perpetrator drugs

Clopidogrel carboxylate: 10 lM (94 %)

Clopidogrel: 0.307 lM Clopidogrel carboxylate: 6.25 lM

0.11 MATE1 0.51 MATE2-K 24.3

MATE1 29.1 lM MATE2-K 0.61 lM

OCT2 133.9 lM

14.8 lM

0.014b

40.8 lMa OCT2

OCT2

OCT2

OCT1



Repaglinide: 0.015 Rosiglitazone: \0.001

0.017b

950 nM (38 %)



Repaglinide: 0.2 lM (98.5 %) Rosiglitazone: 1.7 lM (99.9 %)

34.9 lMa

OCT1

See text

Repaglinide: 1.6 lM Rosiglitazone: 6.9 lM

3.0–22.9 lM

OCT3

2.8–20.3 lM

OCT2

3.8–8.8 lM



NA

See text 1.8–10 lM (variable)

OCT2

OCT2 OCT1

Quinidine: 0.3

Quinidine: 4.60 lM

Quinidine: 5–15 lM (*85 %)

OCT1 Clopidogrel: 0.007 Clopidogrel carboxylate: 0.096



Clopidogrel: 0.1 lM (98 %)

OCT1

\0.001 –

11.3 lM See text

OCT2

OCT2

OCT1

0.9–1.2 nM (?) \0.001

I/IC50

Cmax in vivo (plasma binding)

7.28 lM

OCT1

IC50

In vitro parameters

Table 1 Overview of relevant in vitro studies examining drug–drug interactions with metformin as the victim

[39]

[33]

[42]

[32]

[38, 56]

[37]

[35]

[41]

References

T. B. Stage et al.

and erlotinib all had I/IC50 values [0.1 for various metformin transporters (OCT1, OCT3, MATE1 and MATE2K). Inhibition of these transporters could potentially lead to alterations in the absorption, effect and excretion of metformin. Other tyrosine kinase inhibitors (dasatinib, sunitinib, lapatinib, sorafenib, N-desmethyl imatinib, Odesmethyl gefitinib and O-desmethyl erlotinib) did not inhibit metformin transporters. 3.6 Other Drugs Berberine—the active component of the herbal medicine Rhizoma Coptidis, which is thought to have antibiotic and cardiac effects—has been show to inhibit OCT1- and OCT2-mediated transport of metformin [41]. However, after oral dosing, berberine does not reach plasma levels that would potentially affect metformin transport; thus, clinical relevance of this interaction is unlikely. A study identified six potential OCT2 inhibitors (disopyramide, dipyridamole, imipramine, tacrine, orphenadrine and cimetidine) [42] with I/IC50 values above 0.1. Some of these also inhibited other cation transporters, such as OCT1, MATE1 and MATE2-K; for more information, readers are referred to Kido et al. [42]. We were not able to find any in vitro studies that used metformin as the perpetrator in possible pharmacokinetic DDIs, besides one study showing that metformin did not affect nateglinide metabolism [43].

4 Impact of DDIs on the Pharmacokinetics and Pharmacodynamics of Metformin in Humans

I/Ki; I maximum unbound plasma concentration b

Ki value

4.1 Metformin as a Victim

a

Cmax maximum plasma concentration, HEK293 human embryonic kidney 293 cells, I maximum plasma unbound inhibitor concentration, IC50 half-maximal inhibitory concentration of the inhibitor, Ki inhibition constant, MATE multidrug and toxin extrusion transporter, MDCK Madin–Darby canine kidney cells, OCT organic cation transporter

– – See text OCT1, OCT2, OCT3, MATE1 and MATE2-K Tyrosine kinase inhibitors

HEK293

Cmax in vivo (plasma binding) IC50

Transporters Cell system Perpetrator drugs

Table 1 continued

In vitro parameters

I/IC50

[40]

References

Metformin Drug–Drug Interactions

In order for a DDI to be clinically relevant in humans, changes in the area under the plasma concentration–time curve (AUC), Cmax or CLR have to exceed 25 % or have to have a statistically significant influence on a pharmacodynamic end point such as glycosylated haemoglobin A1c (HbA1c) or an oral glucose tolerance test (OGTT). An alphabetical overview of relevant DDI studies performed in humans is shown in Table 2. 4.2 DDIs with Other Antidiabetic Drugs The alpha glucosidase inhibitor acarbose, which is used to lower glucose absorption, has been shown to decrease the metformin Cmax and AUC from 0 to 9 h (AUC9) [44]. This study had some limitations, such as a small sample size (n = 6) and a short period of blood sampling (9 h), but its findings were recently confirmed in a larger (n = 33)

-35 -26

Healthy subjects (6)

Healthy subjects (33)

Acarbose

NS

?74 NS

?50

?22

?38

?18

NS

?22 NS

?53

?42

?22

?15

?15

?111

?66

?18

?81

?34

-34

-35

Cmax

NS

-52

-27

-32

NR

-9

NR ?16

NR

-35

NS

NS

-13

NR

NR

-30

-27

-14

NR

NR

CLR

180 mg daily

800 mg single dose

200 mg twice daily

200 mg twice daily

100 mg twice daily

900 lg twice daily

500 mg twice daily 600 mg once daily

1000 mg twice daily

50 mg single dose

20 mg once daily on day -2, on day 1 and at 0 hours

40 mg once daily on day -2, on day 1 and at 0 hours

30 mg single dose

50 mg twice daily

50 mg once daily

400 mg twice daily

400 mg twice daily

500 mg single dose

50 mg once daily

100 mg twice daily

Perpetrator drug

Dose

750 mg on days 2 and 14

1 g on days 1 and 13

1 g single dose

850 mg at -12 hours and at 0 hours

500 mg three times daily

500 mg twice daily

1 g twice daily

750 mg on days 2 and 14

1000 mg twice daily 1 g on days 1 and 13

1000 mg twice daily

250 mg single dose

750 mg on day -1 and 500 mg at 0 hours

1 g on day 1 and 750 mg on day 2

500 mg twice daily

500 mg single dose

250 mg once daily

500 mg single dose

500 mg once daily

1000 mg single dose

Metformin

OCT1 inhibition

OCT2 inhibition

MATE2-K inhibition

Unknown

Unknown

OCT1 and OCT2 upregulation

Unknown

MATE1 and MATE2-K inhibition

OCT1 inhibition

OCT2 inhibition

MATE1 and OCT2 inhibition

MATE1 and OCT2 inhibition

MATE1 inhibition

Unknown

Proposed mechanism

[47]

[63]

[39]

[52]

[66]

[65]

[60]

[48]

[64]

[55]

[54]

[67]

[52]

[51]

[57]

[45]

[44]

References

b

a

Decreased effect of metformin during an oral glucose tolerance test

Increased effect of metformin during an oral glucose tolerance test

AUC area under the plasma concentration–time curve, CLR renal clearance, Cmax maximum plasma concentration, MATE multidrug and toxin extrusion transporter, NR not reported, NS not statistically significant, OCT organic cation transporter, PD pharmacodynamics, PK pharmacokinetics, T2D type 2 diabetes

Healthy subjects (13)

Healthy subjects (12)

Verapamilb

?44

Healthy subjects (23)

Healthy subjects (12)

Trimethoprim

Vandetanib

?37

Healthy subjects (18)

Topiramate

?25

Healthy subjects (20)

St John’s worta NS

?37 ?13

T2D patients (25) Healthy subjects (16)

Rifampicin

?79

T2D patients (28)

Ranolazine

a

?39

Healthy subjects (8)

Pyrimethamine

NS

NS

Healthy subjects (23)

Pantoprazole

?17

Rabeprazole

Healthy subjects (20)

?145

Lansoprazole

?79

Healthy subjects (14)

Healthy subjects (14)

?20

Healthy subjects (14)

Dolutegravir

?50

Healthy subjects (7)

Cimetidine

?24

Healthy subjects (12)

Cephalexin

AUC

Changes in metformin pk/pd (%)

Subjects (n)

Perpetrator drug

Table 2 Overview of clinically relevant human studies examining drug–drug interactions with metformin as the victim

T. B. Stage et al.

Metformin Drug–Drug Interactions

randomized trial [45]. This interaction presumably reflects decreased intestinal absorption of metformin during coadministration of acarbose, which might lead to higher doses of metformin being required to maintain blood sugar levels. However, this combination is used in clinical practice because the combination additively reduces blood sugar levels [46]. 4.3 DDIs with Drugs that Affect the Cardiovascular System The calcium channel blocker verapamil, which is used in the treatment of hypertension, angina pectoris and cardiac arrhythmia, did not affect the pharmacokinetic properties of metformin. However, it almost abolished the effect of metformin during an OGTT in healthy individuals [47]. This is likely explained by OCT1 inhibition, which means that intestinal and hepatic uptake of metformin is inhibited and thus the effect is lowered. Hence, verapamil might inhibit the glucose-lowering properties of metformin, but the extent of this DDI should be investigated in T2D patients. Another calcium channel blocker, ranolazine, which is used to treat chronic angina, has been shown to increase the AUC and Cmax of metformin in a dose-dependent manner in T2D patients [48]. Minor OCT2 inhibition was shown in in vitro assays, but this is not likely to be strong enough to support the extent of this DDI. The extent of this interaction is moderate, and dose adjustment of metformin should be considered, especially in those patients receiving a high ranolazine dose. 4.4 DDIs with Gastric Acid-Reducing Agents The antihistamine cimetidine (an H2 receptor antagonist) competitively inhibits MATE1 in the kidneys [49, 50], and at high concentrations (1 mM), cimetidine also inhibits OCT2 in vitro [49]. Cimetidine has been shown to decrease renal elimination of metformin significantly and thus increases the AUC from 0 to 24 h (AUC24) and Cmax [51]. Another study showed much lower inhibition of metformin secretion [52]. However, this study had an overrepresentation of individuals with reduced function of OCT2, which has been shown to lower the extent of this DDI; thus, in OCT2 wild types, the extent of the DDI was equal to that reported by Somogyi et al. [51]. Lactic acidosis, which is a rare but serious side effect, has been described in a case report when cimetidine and metformin were co-administered in a patient with orlistat-induced diarrhoea [53]. The dose of metformin should be reduced if cimetidine is indicated, especially in patients with reduced kidney

function. However, other acid-inhibiting drugs are available and can be used instead. Two studies have investigated metformin DDIs with PPIs. In a single-dose study, lansoprazole induced a minor increase in the metformin AUC24 and Cmax, which was caused by a small decrease in CL/F and CLR. This is not clinically relevant as the effect of metformin assessed by an OGTT was not affected [54]. Lansoprazole is not transported by OCT but has been shown to inhibit OCT2- and OCT3-mediated metformin transport in vitro, as mentioned above [38]. The Cmax of lansoprazole was reported to be 2.7 lM in plasma, and the IC50 of lansoprazole to inhibit metformin transport via OCT2 was 9.5 lM. This indicates that the observed interaction is likely caused by minor OCT2 inhibition, even though the in vitro I/IC50 is \0.1. Neither pantoprazole or rabeprazole affected metformin pharmacokinetics in a clinically relevant manner [55]. Finally, an observational cohort study found that PPIs did not alter the clinical effect of metformin [56]. 4.5 DDIs with Antibiotics The cephalosporin antibiotic cephalexin has been shown to reduce CLR of metformin and thus increases the AUC24 and Cmax [57]. Cephalexin is a zwitterionic drug and, as with metformin, its renal elimination depends on MATE1 transport [58]. Thus, cephalexin might competitively inhibit MATE1. As these changes are minor, we do not expect that dose adjustment of metformin should be necessary. The pregnane X receptor agonist rifampicin, which has antibiotic properties, has been shown to upregulate OCT1 and OCT2 expression in the liver and kidneys in rats [59]. In humans, 10 days of treatment with rifampicin induced increases in metformin CLR and AUC24 values, and the glucose-lowering effect of metformin increased during an OGTT [60]. Increased SLC gene expression and transporter formation of both OCT1 and OCT2, which leads to increases in both absorption and CL, is the presumed mechanism of action. This interaction is supported by the finding that rifampicin alone can cause increased glucose levels in healthy individuals [61]. This DDI might potentiate the effect of metformin, and additional blood sugar control is suggested. When trimethoprim was given in combination with metformin, metformin CLR decreased and, consequently, the AUC from 0 to 8 h (AUC8) and Cmax increased [62]. This was recently confirmed in a smaller study, which showed a similar decrease in CLR, leading to increased AUC and Cmax values [39]. The extent of this DDI is moderate, and dose adjustment of metformin should be considered.

T. B. Stage et al.

4.6 DDIs with Anticancer Drugs Vandetanib is used in the treatment of advanced medullary thyroid cancer. In vitro data have suggested that vandetanib inhibits OCT2 and could affect the transport of metformin. Indeed, vandetanib increased the metformin AUC from time zero to infinity (AUC?) and the Cmax and reduced CLR in healthy OCT2 wild-type subjects [63]. As these changes are pronounced, dose adjustment of metformin should be considered when it is co-administered with vandetanib. 4.7 DDIs with Other Drugs The antiprotozoal agent pyrimethamine competitively inhibits both MATE1 and MATE2-K, and has been shown to decrease renal elimination and increase the AUC from 0 to 12 h (AUC12) and Cmax of metformin [64]. The extent of this interaction is moderate, and dose adjustment should be considered. Another pregnane X receptor agonist, the herbal medicine St John’s wort, which is used to treat depression, was found to decrease CLR of metformin to a minor degree but with an almost unaffected AUC24 [65]. Furthermore, like rifampicin, it increased the effect of metformin during an OGTT. As St John’s wort is available over the counter in many countries, it is not possible to control the use of it; fortunately, it does not appear to be a dangerous combination with metformin, as it increases the effect of metformin without increasing metformin exposure. If T2D patients start or stop taking St John’s wort while being treated with metformin, additional blood sugar control is suggested. Topiramate is an anti-epileptic drug, which has recently been approved by the EMA for treating overweight subjects. During steady-state conditions, topiramate induced a decrease in metformin CL/F, while the AUC12 and Cmax were increased [66]. Topiramate is eliminated mainly by renal excretion and, theoretically, the increased amount of metformin in the plasma could be a result of decreased renal excretion, but the mechanism is unknown. An integrase inhibitor, dolutegravir, which is used in the treatment of HIV infection, increased exposure to metformin in a dose-dependent manner [67]. Both the AUC at steady state (AUCss) and the Cmax at steady state (Cmax,ss) were increased in a two-arm study with 14 participants in each arm, which was likely caused by MATE1 and OCT2 inhibition. This DDI is the most potent pharmacokinetic DDI described in the literature, and metformin dose adjustment is advised for patients being treated with both drugs, especially those treated with dolutegravir 50 mg twice daily.

Contrast fluid-induced nephropathy increases the risk of metformin accumulation. Several international guidelines have made recommendations on when to stop and restart metformin treatment in patients scheduled to undergo intravenous contrast examinations [68]. Generally, knowledge of the estimated glomerular filtration rate at baseline and the amount of contrast to be used during the procedure is essential for a correct assessment. A recent study by Dujic et al. [69] showed an increased risk of metformin intolerance (defined as an increased risk of gastrointestinal side effects and drug discontinuation) when users also ingested drugs known to inhibit OCT1 in vitro (such as tricyclic antidepressants, citalopram, PPIs, verapamil, diltiazem, doxazosin, codeine and clopidogrel). Citalopram, codeine, doxazosin, PPIs and verapamil were associated with an increased risk of intolerance. The pharmacokinetics of metformin have not been shown to be affected to any significant degree by co-administration with aliskiren [70], alogliptin [71], dapagliflozin [72], dutogliptin [73], eslicarbazepine [74], gemigliptin [75], hydrochlorthiazide [76], ibandronate [77], ipragliflozin [78], linagliptin [79], lobeglitazone [80], orlistat [81], memantine [82], pantoprazole [55], rabeprazole [55], rosiglitazone [83], rosuvastatin [84], saxagliptin [85], sitagliptin [34], trospium [86], vildagliptin [87] or voglibose [88]. Previously, angiotensin-converting enzyme (ACE) inhibitors were suspected to increase the glucose-lowering effect of oral antidiabetics, but this was more likely caused by an independent glucose-lowering effect of ACE inhibitors themselves [89]. The opposite was shown for the diuretic hydrochlorthiazide, where one study reported a small increase in fasting blood sugar levels during long-term treatment with hydrochlorthiazide [90], which was not explained by a change in pharmacokinetics [76]. There is a list of drugs that can cause hyperglycaemia (such as corticosteroids, oestrogens and phenytoin) and may antagonize the glucose-lowering effect of metformin. Finally, there are some drugs and substances (ethanol and carbonic anhydrase inhibitors) that cause acidosis and, when co-administered with metformin, theoretically could increase the risk of lactic acidosis. However, as all of the abovementioned events are not DDIs, they are not discussed in this review.

5 DDI with Metformin as a Perpetrator Even though metformin is more often the victim in DDIs, its role as a perpetrator has also been investigated. An alphabetical overview of relevant DDI studies of metformin as a perpetrator is shown in Table 3.

Metformin Drug–Drug Interactions Table 3 Overview of clinically relevant human studies examining drug–drug interactions with metformin as the perpetrator Victim drug

Subjects (n)

Changes in victim drug pk/pd (%)

Dose

Proposed mechanism

References

AUC

Cmax

CL/F

Perpetrator (metformin)

Victim drug

-29

NR

1000 mg once daily

300 mg once daily

Unknown

[70]

NR

Unknown

[92]

Aliskiren

Healthy subjects (19)

-27

Phenprocoumon

Observational, patients (13)

Higher dose of phenprocoumon required in patients receiving metformin

0.6-3.0 g

Database (27)

Higher dose of phenprocoumon required to maintain INR after addition of metformin

NR

Topiramate

Healthy subjects (18)

?50

?50

-20

500 mg twice daily

100 mg twice daily

Unknown

[66]

Trospium

Healthy subjects (43)

-29

-34

CLR: NS

500 mg twice daily

60 mg once daily

OCT1/OCT2 inhibition

[86]

[95]

AUC area under the plasma concentration–time curve, CL/F apparent total oral clearance, CLR renal clearance, Cmax maximum plasma concentration, INR international normalized ratio, NR not reported, OCT organic cation transporter, PD pharmacydynamics, PK pharmacokinetics

5.1 Drugs Affecting the Cardiovascular System that are Affected by Metformin Metformin reduced the Cmax and AUC24 of aliskiren (a renin inhibitor used for hypertension) [70], but as the changes were only minor, no clinically relevant DDI is expected. Aliskiren is a substrate of intestinal P-glycoprotein, cytochrome P450 (CYP) 3A4 and the solute carrier (SLC) transporter OATP2B1 (organic anion transporting polypeptide) [91], which means that no apparent pathway interference can explain this observation. Isolated case reports have suggested that metformin affects the anticoagulant effects of phenprocoumon and warfarin [92–94]. This was confirmed in a recent observational database study, which showed that addition of metformin in patients treated with phenprocoumon induced the need for an 18 % increase in the phenprocoumon dose [95]. This requires further mechanistic explanation and clarification, but it might represent a clinically relevant interaction, and patients being treated with phenprocoumon might need a higher dose after initiating treatment with metformin. 5.2 Other Drugs that are Affected by Metformin In one study, during concomitant treatment with metformin, the topiramate Cmax and AUC12 were increased,

while CL/F was decreased [66]. No baseline topiramate pharmacokinetic profile was measured in this study, but topiramate pharmacokinetics during metformin exposure were compared with measurements from the literature; thus, the results may have been biased. If an effect is present, it is likely caused by competitive inhibition of topiramate renal secretory clearance; however, because of weaknesses in the study design, this observation needs further verification before clinical relevance can be judged and recommendations made. This possible DDI is complicated by the fact that both drugs seem to affect each other; thus, the interpretation may be difficult. For the organic cation trospium (a spasmolytic agent used in the treatment of overactive urinary bladder disease), the Cmax and AUC24 were decreased when it was coadministrated with metformin [86]. Both OCT1 and OCT2 have been shown to transport trospium in vitro [96]. As CL/F increased but CLR was unaffected, metformin may inhibit the oral absorption of trospium. Despite a decrease in systemic exposure to trospium, the therapeutic efficacy of the drug is not likely to be affected, because it has a wide therapeutic window. Clinically, metformin has not been found to significantly affect the pharmacokinetics of alogliptin [71], dapagliflozin [72], dutogliptin [73], gemigliptin [75], linagliptin [79], lobeglitazone [80], rosiglitazone [83], rosuvastatin [84], saxagliptin [85], sitagliptin [34] or vildagliptin [87].

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6 Pharmacogenetics that Affect Interaction Studies of Metformin In the design and interpretation of DDI studies of metformin, genetic variations in transporter genes (OCT1, OCT2, MATE1, MATE2-K and PMAT) involved in metformin transport may bias the study results. In vitro, the common OCT1 variant M420del (which has a minor allele frequency of around 17 % in Caucasians [10]) has been shown to be more sensitive to inhibition than the reference OCT1. Cells with M420del were more sensitive to inhibition by amitriptyline (with a *4.5 times lower IC50) and verapamil (with a *7 times lower IC50) than OCT1 wild-type cells [97]. This indicates that carriers of reducedfunction alleles may be more sensitive to inhibition of OCT1, which could decrease intestinal and hepatic absorption of metformin. The observed IC50 of amitriptyline was higher than clinically observed concentrations in plasma and thus might not be of clinical relevance for metformin transport in the liver, but as intestinal concentrations of amitriptyline are much higher, it may be relevant to metformin absorption. The observed IC50 of verapamil in OCT1 reduced-function cells was well below clinical concentrations, which indicates that this interaction might be more relevant to carriers of M420del. The study further indicated that carriers of the less common R61C variant might be even more sensitive to these interactions. This was supported recently by Dujic et al. [69] who showed that individuals carrying reduced-function OCT1 alleles and treated with OCT1-inhibiting drugs had a fourfold higher risk of DDIinduced metformin intolerance than wild-type individuals not treated with any of the potentially interacting drugs. A study that examined inhibition of metformin tubular secretion clearance by cimetidine showed that carriers of the 808G[T variant (which has a minor allele frequency of around 10 % in Caucasians) in OCT2 were more tolerant of this interaction. Cimetidine reduced the tubular secretion clearance of metformin by up to 50 % in OCT2 wild types, whereas it reduced tubular secretion clearance by only 20 % in carriers of the reduced-function OCT2 variant [52]. This clinical finding was supported by in vitro data on cimetidine, which showed 4-fold higher IC50 values for inhibition of 1-methyl-4-phenylpyridinium (MPP?) uptake in cells with reduced-function OCT2 than in those with wild-type OCT2 [98]. Conversely, the 808G[T OCT2 variant alone did not affect the metformin–trimethoprim DDI [62]; however, the interaction was abolished in carriers of variants of both OCT2 and MATE1 (rs2289669). Because classical DDI studies include only small numbers of individuals, the results of such studies may be sensitive to variations in the interaction. As shown above, certain genotypes may increase or decrease the extent of

the DDI, and genotyping in DDI studies of metformin is warranted to avoid bias in the interpretation of the results.

7 DDIs that Need Further Investigation or Confirmation An in vitro study by Minematsu and Giacomini [40] revealed several tyrosine kinase inhibitors as potential inhibitors of both OCT and MATE, with I/IC50 values [0.1, which, according to FDA guidelines, could lead to potential DDIs in humans; thus, these DDIs should be investigated. Another in vitro study [42] revealed several possible OCT2 inhibitors, the effects of which also need to be confirmed in humans. There have been reports indicating that metformin might induce a requirement for higher doses of the anticoagulant phenprocoumon [92, 95]. Furthermore, in vitro studies have shown that the metabolite of the antiplatelet agent clopidogrel might inhibit OCT1 [37]. These findings have not been confirmed in vitro or in clinical studies, and, as there might be an overlap in the users of these drugs, further research on this possible DDI is relevant. Metformin was shown to increase topiramate exposure, and topiramate increased metformin exposure [66]. The mechanism of this DDI has not been clarified; thus, in vitro studies might lead to understanding of the DDI, which could provide new knowledge regarding the pathway of either drug. Finally, there is still a list of drugs—for example, glycopyrrolate [99], dofetilide [100], bupropion [101], dalfampridine [102] and morphine [103]—that are transported by the same transporters as metformin and thus may influence metformin pharmacokinetics or pharmacodynamics, but these possible DDIs remain unexplored.

8 Concluding Remarks Over the last few years, we have gained increased knowledge about transporter-related DDIs that involve metformin, and we have tried to extract the most important information in this review. We found many DDI studies of metformin, but only a small number of clinically relevant ones; the relevant drugs, listed in alphabetical order, are cimetidine, contrast agents, dolutegravir, phenprocoumon, pyrimethamine, ranolazine, rifampicin, St John’s wort, trimethoprim, vandetanib and verapamil. While most interaction studies have focused on interactions where metformin was the victim, quite a few have shown that metformin has the potential to be the perpetrator in DDIs. Surprisingly, a number of DDI studies reporting changes in the pharmacodynamic response to

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metformin without pharmacokinetic changes have been reported lately [47, 60, 65]. These DDIs are not based on measurable pharmacokinetic changes but are observable only in terms of the metformin effect, which indicates that even though the hepatic influx of metformin is affected, it is not reflected in plasma concentrations. This highlights the importance of including pharmacodynamic measures in DDI studies of metformin, as not all DDIs will be explained solely by changes in plasma concentrations of metformin. For further guidelines on study design etc. for DDI studies, readers are referred to the EMA [29] and/or FDA guidelines [104] on DDI studies. The knowledge gained from DDI studies adds to the existing information regarding metformin and may improve our understanding of the large variation in observed inter-individual responses to metformin. In conclusion, we have given an overview of DDIs with metformin. Generally, most of the DDIs that we found are fairly harmless and are manageable for both clinicians and patients. Theoretically, patients with reduced kidney function are likely to be more sensitive to these DDIs, as this may push metformin exposure to dangerous heights. Acknowledgments The Danish Council for Independent Research|Medical Science provided financial support for this study (protocol number 12-126791). Conflicts of interest Tore Bjerregaard Stage has given paid lectures for Astellas Pharma, Orifarm, Novartis and Eisai. None of the other authors has any relevant conflicts of interest to declare.

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A Comprehensive Review of Drug-Drug Interactions with Metformin.

Metformin is the world's most commonly used oral glucose-lowering drug for type 2 diabetes, and this is mainly because it protects against diabetes-re...
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