DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392

Title DRUG DISPOSITION AND DRUG-DRUG INTERACTION DATA IN 2013 FDA NEW DRUG APPLICATIONS: A SYSTEMATIC REVIEW Jingjing Yu, Tasha K. Ritchie, Aditi Mulgaonkar, and Isabelle Ragueneau-Majlessi Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, USA (J.Y., T.K.R., A.M., I.R-M.)

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 Running Title Page a) Running title: A review of drug disposition and DDIs in the 2013 NDAs b) Corresponding author: Isabelle Ragueneau-Majlessi, Drug Interaction Database Program, Department of Pharmaceutics, University of Washington, Box 357610, Seattle, WA 98195, Phone: 206.543.4669, Fax: 206.543.3204, E-mail: [email protected] c) Number of text pages: Number of tables: 8 Number of figures: 1 Number of references: 44 Number of words in the Abstract: 168 Number of words in the Introduction: 662 Number of words in the Discussion: 146 d) Abbreviations: AUC, area under the curve; BCRP, breast cancer resistance protein; BID, twice daily, BLA, biologic license application; BSEP, bile salt export pump; CYP, cytochrome P450; DDI, drug-drug interaction; DIDB, Drug Interaction Database®; EM, extensive metabolizer; EMA, European Medicines Agency; FDA, Food and Drug Administration; FMO, flavin monoooxygenase; HI, hepatic impairment; HLM, human liver microsomes; IM, intermediate metabolizer; ITC, international transporter consortium; MATE, multidrug and toxin extrusion; MRP, multidrug resistance-associated protein; NDA, new drug application; NME, new molecular entity; NTCP, sodium-taurocholate co-transporting polypeptide; OAT, organic anion transporter; OATP, organic anion transporting polypeptide; OCT, organic cation transporter; OCTN, organic cation transporter, novel; PBPK, physiologically based pharmacokinetic, PGx, pharmacogenetics; P-gp, P-glycoprotein; PM, poor metabolizer; PXR, pregnane X receptor; QD, once daily; RI, renal impairment; SD, single dose; TDI, time-dependent inhibition; TID, three times a day; UGT, UDP-glucuronosyltransferase; URAT, urate transporter

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 Abstract The aim of the present work was to perform a systematic review of drug metabolism, transport, pharmacokinetics, and DDI data available in the NDAs approved by the FDA in 2013, using the University of Washington Drug Interaction Database©, and to highlight significant findings. Among 27 NMEs approved, 22 (81%) were well-characterized with regard to drug metabolism, transport or organ impairment, in accordance with the FDA drug interaction guidance (2012), and were fully analyzed in this review. In vitro, a majority of the NMEs were found to be substrates or inhibitors/inducers of at least one drug metabolizing enzyme or transporter. However, in vivo, only half (n = 11) showed clinically relevant drug interactions, with most related to the NMEs as victim drugs and CYP3A being the most affected enzyme. As perpetrators, the overall effects for NMEs were much less pronounced, compared to when they served as victims. In addition, the pharmacokinetic evaluation in patients with hepatic or renal impairment provided useful information for further understanding of these complex interactions.

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 Introduction Pharmacokinetic drug interactions can lead to severe side effects, and can result in early termination of development, or withdrawal of drugs from the market. Thus, determining the risk of clinically significant drug-drug interactions (DDIs) during the development of a new molecular entity (NME) is critical. With the advancement of pharmaceutical research and novel drug discoveries, it is becoming increasingly challenging for pharmaceutical companies to design safer and more effective drug molecules, as well as to devise new approaches circumventing DDIs mediated by various enzymes and transporters (Huang et al., 2008). Over the past several years, the pharmaceutical regulatory agencies in the US (Food and Drug Administration, FDA) and Europe (European Medicines Agency, EMA) have issued a series of guidance documents for in vitro and in vivo drug interaction studies that must be conducted during drug development (FDA, 1997; FDA, 1999; FDA, 2006; EMA, 2012; FDA, 2012). These guidelines include assessment of the DDI potential of NMEs, using individual pre-clinical evaluations and clinical pharmacology studies, with recommended probe substrates and specific inhibitors/inducers of drug metabolizing enzymes and transporters. Based on the results of these evaluations, one can then predict the interaction potential of the NME with a series of drugs that are likely to be co-administered (evidencebased theoretical interactions). The guidance documents reflect a drive by regulatory authorities to harmonize approaches and study designs to allow for better assessment and comparison of different NMEs, and to facilitate consistent communication of drug interaction risks to healthcare providers, through drug labeling. Both the FDA and EMA documents emphasize the use of an integrated and mechanistic approach to evaluate DDIs and, as such, have dramatically changed the outlook for assessing the potential incidence of clinically significant interactions, in pre- and post-marketing stages (Huang et al., 2008; Zhao et al., 2012). This review encompasses an overall detailed analysis of the pre-clinical and clinical enzyme- and transporter-mediated DDIs observed for new drug applications (NDAs) approved by the FDA in 2013, highlighting the main mechanistic findings and discussing their clinical relevance. The analysis was

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 performed using the University of Washington Drug Interaction Database® (DIDB) drug interactions, pharmacogenetics, and organ impairment modules (http://www.druginteractioninfo.org). All of the parameters were directly extracted from the database, and the changes in mean AUC values are presented in this review. The DIDB data were curated from a thorough review of the NDA approval packages, including, but not limited to, the product labels and clinical pharmacology and biopharmaceutics reviews for

each

of

the

NMEs,

available

at

the

FDA approved

drugs

website

([email protected],

http://www.accessdata.fda.gov/scripts/cder/drugsatfda/). The analysis utilized a mechanistic approach for evaluating DDIs reported for the individual NMEs, based on the decision criteria recommended by the most recent FDA drug interaction guidance document (FDA, 2012). In addition to the individual enzyme and transporter pre-clinical and clinical studies reported in the NDAs, studies looking at mechanisms for enzyme-transporter interplay, as well as those conducted in diseased populations (i.e., hepatic and renal impairment) were also systematically analyzed. The metrics used for evaluation of clinical studies is the area under the curve (AUC) ratio, defined as AUCinhibited or induced/AUCcontrol, with a clinically-significant interaction resulting in an AUC ratio ≥ 2. In addition, important or significant labeling modifications or recommendations were also noted. In 2013, a total of 25 NDAs and 2 biologic license applications (BLAs) were approved by the FDA. A summary of the NDA/BLAs, including DDIs, pharmacogenetics (PGx), and organ impairment studies, as well as therapeutic classes and approval dates, is presented in Table 1, with the chemical structures presented in Supplemental Table 1. Eight of these (30%) were cancer treatments, including 4 kinase inhibitors, making oncology the most represented therapeutic area. Among the 27 NMEs approved in 2013, 22 (81%) had drug metabolism or transporter data available, and 18 (67%) provided hepatic and/or renal impairment studies, and therefore were fully analyzed in this review. The NDAs without those studies were not evaluated in this review and comprised radioactive diagnostic or therapeutic agents, as well as a cytolytic antibody. Pre-clinical Drug Interaction Data Metabolism and Enzyme-Mediated DDIs

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 The most recent drug interaction guidance released by the FDA has focused on criteria which would streamline the evaluation procedure for drug metabolizing enzymes, highlighting decision criteria for evaluation of NMEs as substrates, inhibitors or inducers of clinically important cytochrome P450 (CYP) enzymes, including: CYP1A2, 2B6, 2C8, 2C9, 2C19, 2D6, and 3A. Furthermore, with the growing interest in studying DDIs mediated by UGTs, the guidance also highlights the decision criteria for in vitro and in vivo studies to evaluate the same for UGT1A1, 1A3, 1A4, 1A6, 1A9, 2B7, and 2B15 (FDA, 2012). In accordance with the guidance, the metabolic profile of the NMEs approved in 2013 were wellcharacterized from in vitro studies using recombinant enzymes and human liver tissues such as human liver microsomes (HLMs) or human hepatocytes. Twenty two compounds were shown to be metabolized by at least one enzyme, though the majority of compounds were primarily metabolized by CYPs. Not surprisingly, CYP3A4/5 was shown to metabolize the largest number of NMEs in vitro (n = 17, 77% of NMEs evaluated), although not necessarily as the major enzyme contributing to the drug’s metabolism. In vivo studies further confirmed that 10 of these compounds (45% of NMEs evaluated) were CYP3A substrates, with systemic exposure increases of greater than 20% (FDA cut-off: 25%), when coadministered with potent or moderate CYP3A inhibitors, resulting in the following maximum AUC ratios: ibrutinib, 23.9; simeprevir, 6.5; riociguat, 2.5; macitentan, 2.3; vilanterol (in combination with umeclidinium), 1.9; dabrafenib, 1.6; fluticasone (in combination with vilanterol), 1.4; ospemifene, 1.4; vortioxetine, 1.3; and dolutegravir, 1.2. Inhibition of transporters, especially P-glycoprotein (P-gp), might also contribute to the increased exposure of some of the drugs which were shown to also be P-gp substrates (reviewed in the next section). The highest AUC ratio was observed for ibrutinib (over 20) with concurrent use of ketoconazole (400 mg QD 6 days), indicating the primary role of CYP3A in the disposition of the drug. Accordingly, contraindications of strong and moderate CYP3A inhibitors and strong CYP3A inducers were clearly addressed in the product label (FDA, 2013j). The next largest interaction observed was simeprevir, with an AUC ratio over 5 when co-administered with the CYP3A inhibitor erythromycin (500 mg TID 7 days), suggesting simeprevir as a sensitive substrate of CYP3A.

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 Based on these results, the potential for DDIs with moderate or strong inducers or inhibitors of CYP3A must be considered prior to and during treatment with this drug, as indicated in the product label (FDA, 2013r). Other CYP isoforms, such as CYP2D6, 2C19, 2C9, and 2C8 were involved in the metabolism of 8, 7, 4, and 3 NMEs, respectively (Figure 1A). In addition, some NMEs were primarily metabolized by non-CYP enzymes. For example, sofosbuvir, as a prodrug, is metabolically activated through pathways involving sequential hydrolysis by human cathepsin A (CatA) or carboxylesterase 1 (CES1) and subsequent phosphorylation to the active triphosphate compound by kinases. Additionally, the major metabolic pathway of 3 NMEs, canagliflozin, dolutegravir, and bazedoxifene, is through phase II glucuronidation by UGT2B7/1A9, UGT1A1, and UGT1A1/1A10, respectively. In vivo, in the case of canagliflozin, its systemic exposure (AUC) was slightly increased by 21% when co-administered with the general UGT inhibitor probenecid. Similarly, for dolutegravir, the concurrent use of the UGT1A1 inhibitor atazanavir significantly increased the AUC by 91%. When NMEs were considered as perpetrators, the potential to inhibit drug metabolizing enzymes was investigated in vitro using HLMs or cDNA-expressed enzymes to determine the inhibitory mechanisms (e.g., reversible or time-dependent inhibition) and inhibition potency. Seventeen (77%) NMEs inhibited at least one CYP enzyme (Table 3, Figure 1B), with the most affected enzymes being CYP3A4 (n = 11), 2C9 (n = 10), 2C19 (n = 10), 2C8 (n = 9), and 2D6 (n = 8). Simeprevir was also found to inhibit UGT1A1 weakly in vitro. With regard to the inhibitory mechanism, most inhibitory drug interactions with CYP enzymes are reversible with the exception of mertansine, the active component of ado-trastuzumab emtansine, an antibody-drug conjugate for the treatment of cancer, which showed time-dependent inhibition of CYP3A4 with an IC50 of 0.16 µM after preincubation, while no inhibition was observed under co-incubation conditions up to 0.678 µM. However, no further in vitro studies were available to obtain the time-dependent inhibition parameters. In line with the drug interaction guidance (FDA, 2012), the basic model was first applied by estimating intrinsic clearance values (R value) in the absence and presence of an inhibitor (or inducer) using both in

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 vitro and clinical pharmacokinetic data to determine if an in vivo DDI study was warranted. Based on the R1 values (for reversible inhibition), the majority of the in vitro inhibitory interactions were not considered clinically relevant (R1 ≤ 1.1). Among drugs with R1 > 1.1, in vivo studies with sensitive CYP substrates found only 2 NMEs with positive enzyme inhibition, where simeprevir weakly inhibited intestinal but not hepatic CYP3A (midazolam, AUC ratio = 1.4), CYP1A2 (caffeine, AUC ratio = 1.3) and CYP2C19 (omeprazole, AUC ratio = 1.3), while alogliptin weakly inhibited CYP2D6 (dextromethorphan, AUC ratio = 1.3). More complex models, such as mechanistic static models and PBPK models, were also well incorporated for some drugs in predicting the in vivo DDI risks. For example, canagliflozin showed positive inhibition of CYP2B6 (IC50 = 16 µM) in vitro and a large R1 value (2.51), however, a physiologically based pharmacokinetic (PBPK) model showed no interaction with co-administration of the CYP2B6 probe bupropion, hence, no in vivo study was warranted. It should be noted that although bupropion is considered as the most sensitive CYP2B6 substrate, currently there are no sensitive CYP2B6 substrates available based on the FDA guidance classification (AUC ratio of at least 5-fold, or decrease in oral clearance of 80% or more when co-administered with a known inhibitor) (FDA, 2012). In terms of enzyme induction potential, 21 NMEs were evaluated using human hepatocytes, and 6 (29%) were found to induce CYP enzyme expression to some extent (Table 4): alogliptin (CYP3A4), dabrafenib (CYP2B6/3A4), dolutegravir (PXR activator), macitentan (CYP3A4), ospemifene (CYP1A2/2B6/3A4), and trametinib (CYP2B6/3A4). In vivo, only dabrafenib (R3 = 0.54) was found to be a moderate CYP3A inducer, and decreased the systemic exposure of the co-administered CYP3A probe substrate midazolam by 74% and 61% in AUC and Cmax, respectively. Interestingly, ospemifene, in addition to inducing CYP2B6 mRNA expression, also showed inhibition of the same enzyme in HLMs, and overall in vivo, the exposure of the CYP2B6 probe substrate bupropion was not significantly affected (AUC ratio = 0.83, FDA cut-off: 25%). In contrast, for the prodrug eslicarbazepine acetate, none of its pharmacologically active metabolites, including eslicarbazepine (main), (R)-licarbazepine, and oxcarbazepine, induced

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 CYP3A when tested at concentrations up to 100 µg/mL (eslicarbazepine Cmax = 15 µg/mL) in the in vitro screenings performed by the sponsor. However, when tested in vivo, co-administration of eslicarbazepine acetate decreased the exposure of simvastatin by 50% and the oral contraceptive ethinyl estradiol by 31%, which may be due to CYP3A induction. Warfarin exposure was also decreased by 21%, which may be reflective of possible CYP2C9 induction. In vitro, eslicarbazepine was also found to not induce CYP1A, CYP2C19, UGTs, or sulfotransferase by the sponsor. It should be noted that the magnitude of induction from the positive controls used in these CYP induction screenings were lower than expected. In addition, oxcarbazepine was previously reported to induce CYP3A mRNA expression as well as enzyme activity in human hepatocytes (Fahmi et al., 2010). In summary, regarding drug metabolizing enzymes, CYP3A was involved in the metabolism of the most NMEs in vitro (17 of 22), and 10 were further confirmed to be substrates of CYP3A, in vivo. In addition, the largest DDI observed in vivo was caused by CYP3A inhibition, with ibrutinib being the victim drug. As perpetrators, 17 drugs (77%) showed positive inhibition or induction towards at least one enzyme in vitro. In contrast, in vivo, only 3 NMEs (simeprevir, alogliptin, and eslicarbazepine acetate) were found to be enzyme inhibitors and 2 NMEs (dabrafenib and eslicarbazepine acetate) to be enzyme inducers, highlighting the challenge of translating inhibition and induction data from in vitro to in vivo. The overall in vivo effect of NMEs as perpetrators was much less pronounced, with the largest AUC ratio less than 2, compared to when the NMEs served as victim drugs, where the largest AUC ratio observed was greater than 20. Transport and Transporter-Mediated DDIs In addition to drug metabolizing enzymes, the recent guidance documents, in conjunction with the International Transporter Consortium (ITC), have advocated the importance of transporters as additional driving mechanisms for DDIs, along with aiding the enzyme-mediated DDI events (Giacomini et al., 2010; Huang et al., 2010; Tweedie et al., 2013). The previous FDA guidance (FDA, 2006) only specifically named P-gp as a transporter that NMEs should be screened against, while the most recent

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DMD #60392 document adds six additional transporters to be considered: breast cancer resistance protein (BCRP), organic anion transporting polypeptides 1B1 and 1B3 (OATP1B1, OATP1B3), organic cation transporter 2 (OCT2), and organic anion transporters 1 and 3 (OAT1 and OAT3). This guidance document recommends that all NMEs should be screened as inhibitors for these 7 transporters, and also as substrates for P-gp and BCRP. Additionally, depending on the route of elimination, NMEs should be screened as substrates for the remaining 5 transporters (> 25% renal excretion, or unknown – OAT1, OAT3 and OCT2; > 25% biliary excretion, or unknown – OATP1B1, OATP1B3). Finally, other transporters, such as MRPs, MATEs and/or BSEP should also be considered, when appropriate (FDA, 2012). Out of the 22 NDAs approved in 2013 which contain DDI studies, nearly all of them (n = 20) include some type of transporter study, which is reflective of the recent guidance document. Within those 20 NDAs, more than 120 in vitro transporter assays are described, screening compounds against a total of 16 transporters. Not surprisingly, P-gp was the most represented transporter, both in substrate and inhibition assays performed, as well as positive interactions identified. Though the most recent guidance document is still in draft form, and only recently released, the remaining transporters recommended therein were also well represented, along with the following additional transporters: multidrug resistance-associated protein 2 (MRP2), OCT1, OATP2B1, bile salt export pump (BSEP), multidrug and toxin extrusion transporter 1 (MATE1), organic cation transporters, novel, 1 and 2 (OCTN1, OCTN2), sodiumtaurocholate co-transporting polypeptide (NTCP), and urate transporter 1 (URAT1). With the exception of eslicarbazepine acetate and bazedoxifene, all of the NMEs were screened as substrates of P-gp, and 12 were shown to be substrates, in vitro. In the case of eslicarbazepine acetate, in vivo drug interaction studies were preemptively performed with two known P-gp inhibitors, cyclosporine and verapamil, and no interaction was observed in either study. For bazedoxifene, in vitro screening studies had been published previously (Shen et al., 2010), thus no studies were included in the filing. Out of the 12 positive P-gp in vitro results, 7 in vivo studies were performed, with the largest interaction observed in the case of sofosbuvir (AUC ratio = 3.6, when co-administered with cyclosporine). In

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 addition to being a P-gp substrate, sofosbuvir was also one of the 4 compounds shown to be a BCRP substrate in vitro. As cyclosporine is also a BCRP inhibitor, BCRP may have contributed to the effect seen in the in vivo interaction study. The next largest interaction observed also involved sofosbuvir, with another NME, simeprevir. Both are antiviral treatments for hepatitis C and could be co-administered in patients, and both NMEs were shown to be P-gp substrates, however only simeprevir was shown to be a P-gp inhibitor, in vitro. An AUC ratio of 3.2 was observed for sofosbuvir when co-administered with simeprevir, however, at the time of NDA submission, the clinical study was still ongoing, and comparisons were made to historical data. Of the remaining NMEs tested as the victims in in vivo DDI studies, six were tested as P-gp substrates (afatinib, alogliptin, canagliflozin, riociguat, umeclidinium, and vilanterol) and two as OATP substrates (simeprevir and macitentan). With the exception of riociguat, all resulted in < 50% change in AUC with co-administration of the transporter inhibitor or inducer. Despite this, the product label for afatinib contains a warning that co-administration of P-gp inhibitors or inducers may alter afatinib exposure and the dose should be adjusted as necessary, and if tolerated (FDA, 2013i). In the case of riociguat, there was a 150% increase in AUC when co-administered with ketoconazole. While most of this is likely due to CYP3A inhibition, the sponsor postulates some of the effect could be due to inhibition of P-gp and/or BCRP, as riociguat was shown to be a substrate of both transporters, in vitro. Therefore, the product label advises to consider starting at a lower dose of riociguat when strong CYP3A, P-gp, or BCRP inhibitors are co-administered (FDA, 2013a). With regard to inhibitory interactions, P-gp was again the most represented transporter, with 7 NMEs shown to be inhibitors in vitro (Table 5). Only one NME, trametinib, resulted in both [I]1/IC50 and [I]2/IC50 values below the guidance cut-off values (0.1 and 10, respectively), therefore no in vivo studies were warranted (FDA, 2012). Another compound, vilanterol, present in two approved NDAs with fluticasone or umeclidinium, was shown to inhibit P-gp in vitro, although the IC50 was estimated to be greater than 100 μM, and given that systemic concentrations of vilanterol are in the sub-nM range, the

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DMD #60392 [I]1/IC50 value is far below 0.1. Moreover, as an orally inhaled drug, there is no expected gut interaction with P-gp. Two NMEs, canagliflozin and simeprevir, resulted in both [I]1/IC50 and [I]2/IC50 values greater than the cut-off values, warranting in vivo interaction studies. However, in vivo, only limited increases in digoxin AUC were observed when co-administered with canagliflozin (AUC ratio = 1.2) or simeprevir (AUC ratio = 1.4). The product label for both compounds reflects this, stating that patients taking digoxin concomitantly should be monitored appropriately (FDA, 2013r; FDA, 2013k). In addition, three NMEs resulted in [I]1/IC50 values less than 0.1, but [I]2/IC50 values greater than 10 (vortioxetine, ibrutinib and afatinib). In the case of vortioxetine, the [I]2/IC50 value was neither provided nor discussed in the NDA Reviews and was calculated by the DIDB Editorial Team based on a 10 mg dose. For ibrutinib, instead of performing an in vivo interaction study, the sponsor used PBPK modeling to simulate ibrutinib drug absorption kinetics. The model predicted quick absorption, generally completed in less than 2.5 hours, therefore by staggering the dose of a P-gp substrate and ibrutinib by at least 2.5 hours, the potential for an interaction could be minimized. The ibrutinib product label, however, does warn that co-administration of oral narrow therapeutic index P-gp substrates, such as digoxin, may result in increased blood concentrations of those compounds (FDA, 2013j). Finally, in the case of afatinib, the sponsor submitted data from three clinical settings demonstrating no clinically relevant effects of afatinib on orally administered P-gp substrates, including digoxin, thus, no further in vivo studies were carried out. There were two NMEs where only in vivo (no in vitro) studies were performed with regard to P-gp inhibition – alogliptin and eslicarbazepine acetate. Both compounds had no effect on digoxin AUC (0.3% and 5.7% decrease, respectively). Fexofenadine, a substrate of P-gp and OATPs, was also used as a victim in an alogliptin in vivo DDI study where, in contrast, an effect was observed (though fairly small, AUC ratio of 1.26), which could be reflective of inhibition of P-gp, as well as OATPs. Six NMEs were shown to inhibit OATP1B1 and/or 1B3 in vitro. Of those, only 2 had Cmax/IC50 values above the FDA guidance cut-off of 0.1 (FDA, 2012) – dabrafenib and simeprevir (Table 6). In the case of dabrafenib, the sponsor evaluated the DDI risk using static mathematical models, as described in the FDA

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DMD #60392 guidance, which resulted in R values equal to 1.0 for both transporters, below the cut-off value of 1.25, suggesting that the DDI risk was minimal and an in vivo study was not warranted. For simeprevir, three in vivo studies were performed with simeprevir as a perpetrator using statins – atorvastatin, simvastatin (both also CYP3A and P-gp substrates) and rosuvastatin. The largest change in AUC, and, in fact, the largest change for any of the transporter-based in vivo inhibition studies, was with rosuvastatin where an AUC ratio of 2.8 was observed. For atorvastatin and simvastatin, the effect was marginally less, with AUC ratios equal to 2.2 and 1.7, respectively. Consequently, the product label for simeprevir advises careful monitoring of patients taking any statins, and particularly with rosuvastatin and atorvastatin not to exceed a daily dose of 10 or 40 mg statin per day, respectively, when co-administered with simeprevir (FDA, 2013r). In summary, 3 NMEs were shown to be in vivo inhibitors of P-gp – alogliptin, canagliflozin, and simeprevir, with simeprevir also inhibiting OATP1B1 in vivo. In vitro, in contrast, 85% of NMEs showed a positive interaction with at least one transporter, either as a substrate or inhibitor. Only three NMEs showed no interaction with any transporter, and in all three cases, P-gp was the only transporter tested. These data indicate that when tested in vitro, many NMEs appear to be substrates or inhibitors of at least one transporter. However, this does not necessarily translate in vivo, and the clinical relevance of the transporter interaction may be minimal, especially when compared to the effect of drug metabolizing enzymes. Reasons for this may include extensive protein binding of drugs, resulting in low free circulating concentrations, as well as interplay between drug metabolizing enzymes and transporters, both of which have been reviewed recently (Benet, 2010; Giacomini et al., 2010; Chu et al., 2013). For example, canagliflozin and simeprevir are both greater than 98% protein bound, while simeprevir is also a substrate and inhibitor of several CYPs, all of which may contribute to the moderate effects observed in the digoxin interaction studies mentioned earlier. In addition, with the exception of P-gp, for which the probe substrates or inhibitors used both in vivo and in vitro were fairly consistent among the NMEs, less

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DMD #60392 consensus was observed regarding probe substrates and inhibitors for the other transporters, which may confound translation of in vitro data to the clinical setting. Pharmacogenetic Studies As documented in the FDA drug interaction guidance (FDA, 2012), comparative pharmacokinetic data in subjects with various enzyme genotypes may be used to identify metabolic pathways and estimate the possible extent of interactions. Two NMEs, dolutegravir and umeclidinium (in combination with vilanterol), provided pharmacogenetic analyses to evaluate the effect of the genetic status of primary enzymes on the pharmacokinetics of these drugs. In the case of dolutegravir, which is primarily metabolized by the polymorphic enzyme UGT1A1, with some contribution from CYP3A, the effect of the genetic status of UGT1A1 on dolutegravir pharmacokinetics was evaluated through a meta-analysis using samples (n = 89) collected from subjects with low (poor metabolizers, PMs, *28/*28, *28/*37, *37/*37), reduced (intermediate metabolizers, IMs, *1/*28, *1/*37, *28/*36, *36/*37), and normal (extensive metabolizers, EMs, *1/*1, *1/*36, *36/*36) UGT1A1 activity. The analysis showed that, compared to subjects with normal UGT1A1 activity, the AUC and Cmax increased by 30-50% and 20-30%, respectively, while clearance decreased by 20-30% in subjects with low and reduced UGT1A1 activity. According to the sponsor, as the therapeutic index of dolutegravir is wide and adverse effects are mild and not associated with higher exposures, the effect of UGT1A1 polymorphisms on dolutegravir exposure is not considered clinically significant, hence no dose adjustment is required for subjects with the UGT1A1 *28/*28 and *28/*37 genotypes (FDA, 2013y). The influence of CYP3A4, CYP3A5, and PXR variants on dolutegravir pharmacokinetics was also explored, and polymorphisms in CYP3A4/5 were found not to be associated with any pharmacokinetic changes. Similarly, for umeclidinium, which is mainly metabolized by the polymorphic enzyme CYP2D6, no clinically significant changes were observed in systemic exposure in CYP2D6 PMs compared with EMs (specific alleles not available in the NDA Review). Overall, polymorphisms in primary metabolizing enzymes did not affect the pharmacokinetic parameters of the metabolized drugs to any clinically significant extent.

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 In addition, for simeprevir, while no genotyping data was available and no specific pharmacogenetic analyses were performed in the NDA reviews, it was discovered that in Phase 3 clinical trials subjects of East Asian ancestry (n=14) had 3.4-fold higher exposure of simeprevir than the pooled Phase 3 population, and that this higher exposure was associated with an increased frequency of adverse reactions. The increase in simeprevir exposure is may be clinically relevant and is likely due to some as-yetunidentified genetic variation, therefore the product label states, “There are insufficient safety data to recommend an appropriate dose for patients of East Asian ancestry. The potential risks and benefits should be carefully considered prior to use in patients of East Asian ancestry” (FDA, 2013r). Clinically Significant Drug-Drug Interactions Clinical DDI studies assess the exposure to a potential victim drug (AUC) with and without coadministration of the perpetrator and the AUC ratio often constitutes the main quantitative DDI outcome measurement. However, assigning a clinical significance to the pharmacokinetic outcome can be complex. Additional information is often needed on the drug pharmacokinetic-pharmacodynamic relationship, the within- and between-individual variability in response, and the clinical context of patient status and underlying disease. Nevertheless, it is usually acknowledged that a 2-fold change in drug exposure will often trigger dosing recommendations and thus, an AUC ratio of 2 was considered in this analysis as a cut-off for further consideration. Overall, it was found that 10 of the 22 drugs analyzed (45%) had at least one metabolism-based in vivo DDI study with a change in exposure of clinical significance (AUC increase ≥ 2-fold or AUC decrease ≥ 50% for the affected drugs), with NMEs being mainly victim drugs. All clinically significant inhibition and induction results observed with NMEs as victims or perpetrators are presented in Tables 7 (inhibition) and 8 (induction). For inhibition studies (Table 7), alteration of CYP3A activity was the most common underlying mechanism, except for ospemifene and vortioxetine. For ospemifene, its exposure was increased by almost 3-fold when co-administered with the multi-CYP inhibitor fluconazole (200 mg QD for 8 days). Ospemifene is primarily metabolized by CYP3A, 2C9, and 2C19, each of these enzymes being

15

DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 responsible for approximately 40-50%, 25%, and 25% of its clearance, respectively, and fluconazole is known to inhibit all three of these enzymes. Of note, concurrent administration of the strong CYP3A inhibitor ketoconazole increased ospemifene AUC by only 1.4-fold, while co-administration of the CYP2C19 inhibitor omeprazole increased its exposure by 1.2-fold (FDA, 2013t). In addition, ospemifene is also sensitive to CYP induction, as concomitant dosing with rifampin decreased ospemifene AUC by 58% and Cmax by 51%. Co-administration of both fluconazole and rifampin is contraindicated with ospemifene (FDA, 2013t). As for vortioxetine, which is primarily metabolized by CYP2D6, coadministration of the strong CYP2D6 inhibitor bupropion (150 mg BID) increased vortioxetine exposure by 2.3-fold. A reduction in vortioxetine dose by half is recommended when a strong CYP2D6 inhibitor (bupropion, fluoxetine, paroxetine, or quinidine) is co-administered (FDA, 2013e). Two NMEs, ibrutinib and simeprevir, were found to be sensitive substrates of CYP3A, with AUC ratios greater than 5 when coadministered with known CYP3A inhibitors (ketoconazole and erythromycin, respectively). For ibrutinib, based on the very large increase in AUC observed (over 20-fold) when co-administered with ketoconazole (400 mg QD for 6 days), concomitant use of strong CYP3A inhibitors which are taken chronically is not recommended. Preliminary data also showed that the strong CYP3A inducer rifampin caused a 14-fold decrease in ibrutinib Cmax and a 12.5-fold decrease in ibrutinib AUC, therefore the concomitant use of strong CYP3A4 inducers should be avoided, as a dose adjustment cannot be recommended (there is, however, no specific recommendation when ibrutinib is co-administered with a weak or moderate inducer (FDA, 2013j)). Simeprevir exposure was increased by 7.2- and 6.5-fold when co-administered with the strong CYP3A4 inhibitor ritonavir and the moderate CYP3A4 inhibitor erythromycin, respectively. In addition, co-administration of the CYP3A inducers rifampin and efavirenz resulted in decreases in simeprevir exposure close to 50%. Based on these results, concomitant use of simeprevir with strong and moderate CYP3A inhibitors or inducers should be avoided (FDA, 2013r). Regarding clinical induction data, significant inductions were mainly related to NMEs as victim drugs and, in most cases, involved induction of CYP3A by known inducers (Table 8). When NMEs were

16

DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 considered as perpetrators, two compounds were found to significantly induce CYP3A, dabrafenib and eslicarbazepine acetate. Dabrafenib significantly reduced the AUC of the sensitive CYP3A substrate midazolam by over 70%, while eslicarbazepine acetate decreased simvastatin exposure by 50%. Both drugs have recommendations in their labels regarding their possible inductive effect on co-administered drugs (FDA, 2013w; FDA, 2013c). Finally, there were very few purely transporter-based drug interactions with over 2-fold changes in substrates exposure. Only the interaction between sofosbuvir (400 mg single dose) and cyclosporine (administered as a high single dose of 600 mg) was related to inhibition of P-gp and BCRP, and yielded an increase in sofosbuvir AUC of almost 4-fold. However, the exposure of the predominant circulating inactive metabolite (GS-331007) was unchanged, and considering sofosbuvir safety margins, the effect of cyclosporine on sofosbuvir pharmacokinetics was not considered clinically significant by the sponsor and no dose adjustment is required. Also of note, sofosbuvir plasma exposure was also increased by coadministration of simeprevir (150 mg QD 12 or 24 weeks), an inhibitor of P-gp (AUC ratio of 3.2, as previously discussed). Overall, when a cut-off of 2-fold change in drug exposure was considered for clinical relevance, almost half of the NMEs analyzed had clinically significant DDIs, most of them related to the NMEs as victim drugs. Not surprisingly, the underlying mechanism for a large number of these interactions was inhibition or induction of CYP3A. Hepatic and Renal Impairment studies Hepatic and renal impairment are important disease conditions to consider while evaluating the potential plasma exposure that a particular NME would achieve clinically. In addition, such organ impairment may overlap with different critical disease conditions (e.g., in cancer patients), or may be associated with patients in certain age groups (e.g., geriatrics). As such, individuals may be receiving a multitude of medications, and this could lead to more complex DDIs potentially occurring due to multiple mechanisms involving metabolism and/or transport. Moreover, depending on the severity of impairment of these

17

DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 eliminating organs (mild, moderate or severe), the probability and extent of these DDIs may be affected significantly. Therefore, it has become critical to assess the pharmacokinetics of NMEs in impaired populations in the pre-marketing drug development stages. For the purpose of this review, the major outcome measurement of the NMEs was the AUC change or AUC ratio (AUCimpaired/AUCcontrol), studied using patients with HI or RI and healthy control populations. For this assessment, similar to the in vivo clinical significance evaluation, an AUC ratio of 2 was considered as a cut-off to systematically evaluate the NDAs for any dosing and labeling recommendations for the NMEs in question. Among the 15 NMEs evaluated for HI studies, 4 demonstrated an AUC ratio greater than 2 in the HI patients versus normal controls. The highest AUC ratio (6.0) was observed for ibrutinib in the moderate HI population (Child-Pugh B). However, the ibrutinib label states that there was “insufficient data to recommend a dose in patients with baseline HI,” and recommended that ibrutinib should be avoided in these patients (FDA, 2013j). The next largest change in AUC was observed for simeprevir, showing 2.4and 5.2-fold increases in AUC for moderate and severe HI patients, respectively. Although no dose recommendations have been provided for simeprevir in these patients, the label states that the potential risks and benefits of simeprevir should be carefully considered prior to the use in patients with moderate or severe HI (FDA, 2013r). Moreover, bazedoxifene (with conjugated estrogens) demonstrated AUC ratios of 3.6, 2.1, and 4.3 in patients with mild, moderate, and severe HI, respectively, hence has been contraindicated in women with any known HI or disease (FDA, 2013g). The increases in AUC observed in HI patients may be attributed to the fact that these compounds all undergo extensive hepatic metabolism, and have also shown high biliary excretion, with > 80% being eliminated in the feces. Finally, sofosbuvir showed AUC ratios greater than 2 in both moderate and severe HI patients. However, considering its renal elimination pathway (discussed in the following RI section), no dose adjustment has been recommended for any HI patients (FDA, 2013v). With regard to RI studies, 4 out of 17 NMEs demonstrated an AUC ratio greater than 2 in RI patients versus normal controls. Gadoterate meglumine showed the largest effect in RI patients, with 3.5- and 9.3-

18

DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 fold increases in AUC, and 87.3% and 61.3% decreases in clearance, in moderate and severe RI patients, respectively. These data are reflective of the elimination pathway of gadoterate meglumine, where renal clearance approximates total clearance. No dose adjustment was suggested for RI populations; however, the product label contains a black box warning for the risk of the life-threatening adverse event, nephrogenic systemic fibrosis, in patients with chronic severe kidney disease (FDA, 2013f). The next largest change in AUC involved alogliptin, where AUC ratios of 2.0, 3.6, and 4.7 were observed in moderate, severe RI, and the end-stage renal disease (ESRD) populations, respectively, consistent with fact that almost 80% of alogliptin is eliminated renally. Accordingly, a dose adjustment is recommended for moderate and severe RI, and ESRD patients (FDA, 2013q). Sofosbuvir, as a prodrug, is eliminated approximately 80% through renal excretion in the form of metabolites. Mild increases in AUC (AUC ratios between 1.6 and 2.7) were observed for sofosbuvir in the mild, moderate, severe RI and ESRD populations. However, the AUC of main (inactive) metabolite, GS-331007, was found to increase by 5.5fold in severe RI, and 13.8- and 21.7-fold in ESRD, 1 h before and after dialysis, respectively. Based on these results, no dose adjustment is needed for patients with mild or moderate renal impairment. However, as the safety and efficacy of sofosbuvir has not been established in patients with severe RI or ESRD requiring hemodialysis, dosing recommendations have not been made for these populations (FDA, 2013v). Similarly, the prodrug eslicarbazepine acetate is also primarily eliminated by renal excretion as eslicarbazepine (the main active metabolite) and its glucuronide conjugate, together accounting for more than 90% of total metabolites excreted in the urine. In RI patients, 1.6-, 2.1-, 2.5-, and 1.4-fold increases in eslicarbazepine AUC, as well as 37.9%, 52.6%, 60.6%, and 28.9% decreases in clearance, were observed in mild, moderate, severe RI and ESRD, respectively. Hence, a dose reduction has been recommended in the product label for patients with moderate and severe RI (FDA, 2013c). Overall, 19 NMEs were assessed for the influence of HI or RI on drug pharmacokinetics. One NME, sofosbuvir, showed significant pharmacokinetic effects in both HI and RI populations (AUC ratio ≥ 2), however due to the metabolism and excretion properties of the compound, no dose adjustments were

19

DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 recommended for either population. Six additional NMEs showed significant effects in the impaired population (three for HI and three for RI), which resulted in contraindications for respective populations in five out of six product labels. These data illustrate the importance of studying drug pharmacokinetics in impaired populations, as the AUC ratios observed in HI or RI patients may be on the same order of magnitude as those observed in clinical drug interaction studies. Conclusion The evaluation of DDIs during the drug development process has profoundly changed over the past two decades and an integrated and mechanistic approach to these studies is highly recommended. The results of the detailed analysis of NDA reviews for drugs that have been approved by the FDA in 2013 were generally consistent with current regulatory recommendations. The drug interaction profiles were wellcharacterized using probe markers and known inhibitors and inducers of drug metabolizing enzymes. Moreover, as significant scientific efforts have focused on elucidating the mechanisms and clinical significance of drug transporters, many NMEs were also thoroughly evaluated for transporter-based DDIs. Additionally, a majority of NMEs were also assessed in hepatic or renal impaired populations. These evaluations shows that, using the knowledge gained from dedicated pre-clinical and clinical studies, the most significant clinical drug interactions can be identified, allowing effective and targeted dosing recommendations to be made.

Authorship Contributions: Participated in research design: Yu, Ritchie, Molgaonkar, Ragueneau-Majlessi Performed data analysis: Yu, Ritchie, Molgaonkar, Ragueneau-Majlessi Wrote or contributed to the writing of the manuscript: Yu, Ritchie, Molgaonkar, Ragueneau-Majlessi

20

DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 References Benet LZ (2010) Predicting drug disposition via application of a Biopharmaceutics Drug Disposition Classification System. Basic Clin Pharmacol Toxicol 106:162-167. Bruderer S, Aänismaa P, Homery MC, Häusler S, Landskroner K, Sidharta PN, Treiber A, and Dingemanse J (2012) Effect of cyclosporine and rifampin on the pharmacokinetics of macitentan, a tissue-targeting dual endothelin receptor antagonist. AAPS J 14:68-78. Chen G, Lee R, Højer AM, Buchbjerg JK, Serenko M, and Zhao Z (2013) Pharmacokinetic drug interactions involving vortioxetine (Lu AA21004), a multimodal antidepressant. Clin Drug Investig 33:727-736. Chu X, Korzekwa K, Elsby R, Fenner K, Galetin A, Lai Y, Matsson P, Moss A, Nagar S, Rosania GR, Bai JP, Polli JW, Sugiyama Y, Brouwer KL, and Consortium IT (2013) Intracellular drug concentrations and transporters: measurement, modeling, and implications for the liver. Clin Pharmacol Ther 94:126-141. EMA (2012) Guideline on the Investigation of Drug Interactions. Fahmi OA, Kish M, Boldt S, and Obach RS (2010) Cytochrome P450 3A4 mRNA is a more reliable marker than CYP3A4 activity for detecting pregnane X receptor-activated induction of drugmetabolizing enzymes. Drug Metab Dispos 38:1605-1611. Falcão A, Pinto R, Nunes T, and Soares-da-Silva P (2013) Effect of repeated administration of eslicarbazepine acetate on the pharmacokinetics of simvastatin in healthy subjects. Epilepsy Res 106:244-249. FDA (1997) Guidance for Industry: Drug Metabolism/Drug Interaction Studies in the Drug Development Process: Studies In vitro. FDA (1999) Guidance for Industry: In vivo Drug Metabolism/Drug Interaction Studies -Study Design, Data Analysis, and Recommendations for Dosing and Labeling.

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DMD #60392 FDA (2006) Draft guidance for industry: Drug Interaction Studies —Study Design, Data Analysis, and Implications for Dosing and Labeling. FDA (2012) Draft guidance for industry: Drug Interaction Studies —Study Design, Data Analysis, and Implications for Dosing and Labeling Recommendations. FDA (2013a) Drug approval package: ADEMPAS® (Riociguat) [FDA application no, (NDA) 204819]. FDA (2013b) Drug approval package: ANORO ELLIPTA® (Umeclidinium and vilanterol) [FDA application no, (NDA) 203975]. FDA (2013c) Drug approval package: APTIOM® (Eslicarbazepine acetate) [FDA application no, (NDA) 022416]. FDA (2013d) Drug approval package: BREO ELLIPTA® (Fluticasone and vilanterol) [FDA application no, (NDA) 204275]. FDA (2013e) Drug approval

package: BRINTELLIX® (Vortioxetine) [FDA application

no,

(NDA) 204447]. FDA (2013f) Drug approval package: DOTAREM® (Gadoterate meglumine) [FDA application no, (NDA) 204781]. FDA (2013g) Drug approval package: DUAVEE® (Conjugated estrogens and bazedoxifene) [FDA application no, (NDA) 022247]. FDA

(2013h)

Drug

approval

package: GAZYVA®

(Obinutuzumab)

[FDA

application

no,

(BLA) 125486]. FDA (2013i) Drug approval package: GILOTRIF® (Afatinib) [FDA application no, (NDA) 201192]. FDA (2013j) Drug approval package: IMBRUVICA® (Ibrutinib) [FDA application no, (NDA) 205552]. FDA

(2013k)

Drug

approval

package: INVOKANA®

(Canagliflozin) [FDA

application

no,

(NDA) 204042]. FDA (2013l) Drug approval package: KADCYLA® (Ado-trastuzumab emtansine) [FDA application no, (BLA) 125427].

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 FDA (2013m)

Drug

approval

package: KYNAMRO®

(Mipomersen)

[FDA application

no,

(NDA) 203568]. FDA (2013n) Drug approval package: LUZU® (Luliconazole) [FDA application no, (NDA) 204153]. FDA (2013o) Drug approval package: LYMPHOSEEK® (Technetium Tc-99M Tilmanocept) [FDA application no, (NDA) 202207]. FDA (2013p) Drug approval package: MEKINIST® (Trametinib) [FDA application no, (NDA) 204114]. FDA (2013q) Drug approval package: NESINA® (Alogliptin) [FDA application no, (NDA) 022271]. FDA (2013r) Drug approval package: OLYSIO® (Simeprevir) [FDA application no, (NDA) 205123]. FDA (2013s) Drug approval package: OPSUMIT® (Macitentan) [FDA application no, (NDA) 204410]. FDA (2013t) Drug approval package: OSPHENA® (Ospemifene) [FDA application no, (NDA) 203505]. FDA (2013u) Drug approval package: POMALYST® (Pomalidomide) [FDA application no, (NDA) 204026]. FDA (2013v) Drug approval package: SOVALDI® (Sofosbuvir) [FDA application no, (NDA) 204671]. FDA (2013w) Drug approval package: TAFINLAR® (Dabrafenib) [FDA application no, (NDA) 202806]. FDA (2013x) Drug approval package: TECFIDERA® (Dimethyl fumarate) [FDA application no, (NDA) 204063]. FDA (2013y) Drug approval package: TIVICAY® (Dolutegravir) [FDA application no, (NDA) 204790]. FDA (2013z) Drug approval package: VIZAMYL® (Flutemetammol F18 injection) [FDA application no, (NDA) 203137]. FDA (2013{) Drug approval package: XOFIGO® (Radium Ra-223 dichloride) [FDA application no, (NDA) 203971]. Giacomini KM, Huang SM, Tweedie DJ, Benet LZ, Brouwer KL, Chu X, Dahlin A, Evers R, Fischer V, Hillgren KM, Hoffmaster KA, Ishikawa T, Keppler D, Kim RB, Lee CA, Niemi M, Polli JW, Sugiyama Y, Swaan PW, Ware JA, Wright SH, Yee SW, Zamek-Gliszczynski MJ, Zhang L, and Consortium IT (2010) Membrane transporters in drug development. Nat Rev Drug Discov 9:215236.

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 Huang SM, Strong JM, Zhang L, Reynolds KS, Nallani S, Temple R, Abraham S, Habet SA, Baweja RK, Burckart GJ, Chung S, Colangelo P, Frucht D, Green MD, Hepp P, Karnaukhova E, Ko HS, Lee JI, Marroum PJ, Norden JM, Qiu W, Rahman A, Sobel S, Stifano T, Thummel K, Wei XX, Yasuda S, Zheng JH, Zhao H, and Lesko LJ (2008) New era in drug interaction evaluation: US Food and Drug Administration update on CYP enzymes, transporters, and the guidance process. J Clin Pharmacol 48:662-670. Huang SM, Zhang L, and Giacomini KM (2010) The International Transporter Consortium: a collaborative group of scientists from academia, industry, and the FDA. Clin Pharmacol Ther 87:32-36. Shen L, Ahmad S, Park S, DeMaio W, Oganesian A, Hultin T, Scatina J, Bungay P, and Chandrasekaran A (2010) In vitro metabolism, permeability, and efflux of bazedoxifene in humans. Drug Metab Dispos 38:1471-1479. Tweedie D, Polli JW, Berglund EG, Huang SM, Zhang L, Poirier A, Chu X, Feng B, and Consortium IT (2013) Transporter studies in drug development: experience to date and follow-up on decision trees from the International Transporter Consortium. Clin Pharmacol Ther 94:113-125. Zhao P, Rowland M, and Huang SM (2012) Best practice in the use of physiologically based pharmacokinetic modeling and simulation to address clinical pharmacology regulatory questions. Clin Pharmacol Ther 92:17-20.

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DMD #60392 Footnotes A.M. current affiliation: Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA

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DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 Figure 1. Quantitation of NMEs acting as substrates or inhibitors of drug metabolizing enzymes, in vitro. A – Contribution of phase I and II enzymes to NME metabolism (n = 22); * esterases, nucleases, and flavin monooxygenases (FMOs). B – CYP isoforms inhibited by NMEs (n = 17).

26

DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 TABLE 1. NDA/BLAs approved by the FDA in 2013 (ordered by approval date) Compound Name

DDI

PGx

HI/RI

Therapeutic Class

Approval Date

Reference

Alogliptin

Y

N

Y

Endocrinology

01/25

(FDA, 2013q)

Mipomersen

Y

N

Y (RI)

Endocrinology

01/29

(FDA, 2013m)

Pomalidomide

Y (in vitro)

N

N

Hematology/Oncology

02/08

(FDA, 2013u)

Ado-trastuzumab emtansine

Y (in vitro)

N

Y (RI)

Hematology/Oncology

02/22

(FDA, 2013l)

Ospemifene

Y

N

Y

Obstetrics/Gynecology

02/26

(FDA, 2013t)

Technetium Tc-99M tilmanocepta

N

N

N

Diagnostics

03/13

(FDA, 2013o)

Gadoterate meglumine

N

N

Y (RI)

Diagnostics

03/20

(FDA, 2013f)

Dimethyl fumarate

Y

N

N

Neurology/Neurosurgery

03/27

(FDA, 2013x)

Canagliflozin

Y

N

Y

Endocrinology

03/29

(FDA, 2013k)

Fluticasone and vilanterol

Y

N

Y

Pulmonary/Critical Care

05/10

(FDA, 2013d)

Radium Ra 223 dichloridea

N

N

Yb

Hematology/Oncology

05/15

(FDA, 2013{)

Dabrafenib

Y

N

N

Hematology/Oncology

05/29

(FDA, 2013w)

b

Hematology/Oncology

05/29

(FDA, 2013p)

Trametinib

Y

N

Y

Afatinib

Y

N

Y (HI)

Hematology/Oncology

07/12

(FDA, 2013i)

Dolutegravir

Y

Y

Y

Infectious Disease

08/12

(FDA, 2013y)

Vortioxetine

Y

N

Y

Psychiatry

09/30

(FDA, 2013e)

Conjugated estrogens and bazedoxifene

Y

N

Y

Obstetrics/Gynecology

10/03

(FDA, 2013g)

Riociguat

Y

N

Y

Cardiology

10/08

(FDA, 2013a)

Macitentan

Y

N

Y

Cardiology

10/18

(FDA, 2013s)

Flutemetamol F-18a

N

N

N

Diagnostics

10/25

(FDA, 2013z)

Obinutuzumaba

N

N

Yb

Hematology/Oncology

11/01

(FDA, 2013h)

Eslicarbazepine acetate

Y

N

Y

Neurology/Neurosurgery

11/08

(FDA, 2013c)

Ibrutinib

Y

N

Y

Hematology/Oncology

11/13

(FDA, 2013j)

Luliconazole

Y

N

N

Infectious Disease

11/14

(FDA, 2013n)

Simeprevir

Y

N

Y

Gastroenterology

11/22

(FDA, 2013r)

Sofosbuvir

Y

N

Y

Gastroenterology

12/06

(FDA, 2013v)

Umeclidinium and vilanterol

Y

Y

Y

Pulmonary/Critical Care

12/08

(FDA, 2013b)

Y – Studies included in the NDA Reviews, N – Studies not included in the NDA Reviews a

Not evaluated in this review

b

Population PK data presented, not included in this review

27

DMD Fast Forward. Published on September 30, 2014 as DOI: 10.1124/dmd.114.060392 This article has not been copyedited and formatted. The final version may differ from this version.

DMD #60392 TABLE 2. Enzymes and transporters involved in the NDA/BLA elimination pathways Main Elimination Route

Enzymes Involved a

DM1: metabolism; no mass balance study for T-DM1

T: proteolytic enzymes; DM1: CYP3A4, CYP3A5

Afatinib

minimal metabolism, fecal (85% mostly as parent)

FMO, CYPs

Alogliptin

minimal metabolism, renal (76% mainly as parent), fecal (13%)

CYP2D6, CYP3A4

metabolism, fecal (60.4% mainly as parent), renal (32.5 mainly as metabolites)

Drug Name Ado-trastuzumab emtansine (T-DM1)

Canagliflozin

E: metabolism, renal (as parents and Conjugated estrogens and metabolites); B: metabolism, fecal (85% bazedoxifene mainly as parent)

Dabrafenib

Dimethyl fumarate

Dolutegravir

Eslicarbazepine acetate Fluemetamol F-18

Fluticasone and vilanterol Gadoterate meglumine

Ibrutinib Luliconazole

Macitentan

Mipomersen Obinutuzumab

metabolism, fecal (71%), renal (23%) metabolism, exhalation of CO2 (60%), renal (15.5%)

Transporters Involved a

Reference

P-gp b

(FDA, 2013l)

P-gp, BCRP c

(FDA, 2013i)

none b

(FDA, 2013q)

UGT2B4, UGT1A9, CYP3A4, CYP2D6

P-gp, MRP2

(FDA, 2013k)

E: CYP3A4; B: UGT1A1, UGT1A10, UGT1A8

not tested d

(FDA, 2013g)

P-gp b

(FDA, 2013w)

esterases, tricarboxylic acid cycle none b (non-CYP)

(FDA, 2013x)

CYP2C8, CYP3A4, CYP2C9, CYP2C19

metabolism, fecal (53% as parent), renal (31% mainly as metabolites)

UGT1A1, UGT1A3, UGT1A9

P-gp, BCRP c

(FDA, 2013y)

metabolism, renal (90% as parent and metabolites)

non-CYP hydrolytic enzymes, UGT1A9, UGT2B4, UGT2B17

not tested

(FDA, 2013c)

fecal (52%), renal (37%)

not available

not tested

(FDA, 2013z)

F: metabolism, fecal (90%); V: metabolism, renal (70%), fecal (30%)

CYP3A4

P-gp b

(FDA, 2013d)

renal (86.6% as parent)

none

not tested

(FDA, 2013f)

metabolism, fecal (80.6% mostly as metabolites)

CYP3A4, CYP2D6

none b

(FDA, 2013j)

metabolism (topical use)

CYP2D6, CYP3A4

not tested

(FDA, 2013n)

metabolism, renal (50% as inactive metabolites), fecal (24%)

CYP3A4 (99%), CYP2C19

none

(FDA, 2013s)

metabolism in tissues, renal (

Drug disposition and drug-drug interaction data in 2013 FDA new drug applications: a systematic review.

The aim of the present work was to perform a systematic review of drug metabolism, transport, pharmacokinetics, and DDI data available in the NDAs app...
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