Eur J Drug Metab Pharmacokinet DOI 10.1007/s13318-014-0239-0

ORIGINAL PAPER

Safety and pharmacokinetics of the CIME combination of drugs and their metabolites after a single oral dosing in healthy volunteers Natacha Lenuzza • Xavier Duval • Gre´gory Nicolas • Etienne The´venot • Sylvie Job • Orianne Videau Ce´line Narjoz • Marie-Anne Loriot • Philippe Beaune • Laurent Becquemont • France Mentre´ • Christian Funck-Brentano • Loubna Alavoine • Philippe Arnaud • Marcel Delaforge • Henri Be´nech

•

Received: 20 March 2014 / Accepted: 20 November 2014 Ó Springer International Publishing Switzerland 2014

Electronic supplementary material The online version of this article (doi:10.1007/s13318-014-0239-0) contains supplementary material, which is available to authorized users.

transport). Blood was collected over 3 days and on day 7. CIME probes and relevant metabolites were assayed by LC–MS/MS and PK parameters were calculated. Main results were: (1) good safety with reversible mild or moderate adverse effects, (2) an analytical method able to quantify simultaneously the 10 probes and the major metabolites, (3) calculation of PK parameters for all probes in general agreed with published values, and (4) identification of the low CYP2D6 metabolizer. This pilot study showed that the CIME combination was well tolerated and that its pharmacokinetics could be accurately measured in healthy volunteers. This combination can now confidently be checked for sensitivity and specificity and for lack of interaction to be validated as a phenotyping cocktail.

N. Lenuzza
E. The´venot
S. Job CEA, LIST, Data Analysis and Systems Intelligence Laboratory, Gif-sur-Yvette, France

L. Becquemont Clinical Research Unit EA2706 Paris sud-CHU Biceˆtre, Le Kremlin Biceˆtre, France

X. Duval
L. Alavoine Clinical Investigation Center (CIC-1425), CHU Bichat Claude Bernard, Paris, France

C. Funck-Brentano Department of Pharmacology and UMR ICAN 1166, Faculty of Medicine, Sorbonne University, UPMC Univ Paris 06, Paris, France

Abstract This phase I, pilot clinical study was designed to evaluate the safety and the pharmacokinetic (PK) profiles of the CIME (Metabolic Identity Card) combination of ten drugs, with a view to its use as a phenotyping cocktail. Ten healthy Caucasian subjects were orally dosed with the CIME combination (caffeine–CYP1A2, repaglinide– CYP2C8, tolbutamide–CYP2C9, omeprazole–CYP2C19, dextromethorphan–CYP2D6, midazolam–CYP3A, acetaminophen–UGT1A1, 6&9 and 2B15, digoxin–P-gp, rosuvastatin–OATP1B1&3 and memantine–active renal

X. Duval
F. Mentre´ INSERM, IAME, UMR1137, University Paris-Diderot, Sorbonne Paris Cite´, Paris, France G. Nicolas
O. Videau
H. Be´nech (&) CEA, DSV, iBiTecS, Pharmacology and Immunoanalysis Unit, Gif-sur-Yvette, France e-mail: [email protected] C. Narjoz
M.-A. Loriot
P. Beaune Department of Biochemistry, Pharmacogenetics and Molecular Oncology Unit, Assistance Publique des Hoˆpitaux de Paris, Hoˆpital Europe´en Georges Pompidou, Paris, France C. Narjoz
M.-A. Loriot
P. Beaune University Paris Descartes, INSERM UMRS 1147, Sorbonne Paris Cite´, Paris, France

C. Funck-Brentano Department of Pharmacology and CIC-1421, Assistance Publique des Hoˆpitaux de Paris, Pitie´-Salpeˆtrie`re Hospital, Paris, France P. Arnaud Pharmacy, CHU Bichat Claude Bernard, Paris, France M. Delaforge CEA, DSV, iBiTecS, UMR 8221, Bioenergetics, Structural Biology and Mechanisms Unit, Gif-sur-Yvette, France

Eur J Drug Metab Pharmacokinet

Keywords Safety

CIME
Probes
Phase I
Pharmacokinetics


1 Introduction The ‘‘cocktail strategy’’ initiated by Breimer and Schellens (Breimer and Schellens 1990) to determine metabolizer status (i.e., activity of enzymes responsible for drug metabolism and pharmacokinetics, DMPK) consists of the simultaneous assessment of several cytochromes P450 (CYP), phase II enzymes or drug transporter activities using a mixture of selective probes. To be considered as a validated cocktail, a combination of drugs must fulfill welldescribed criteria (Fuhr et al. 2007). Among others, probes must be validated for specificity and sensitivity and the proposed probes should not interact when administered together. Validated cocktails, including the Pittsburg (Stewart et al. 2011), the Inje (Ryu et al. 2007) and the Cooperstown or Cooperstown 5 ? 1 cocktail (Chainuvati et al. 2003), have been used to study the effects of some drug candidates on CYPs to anticipate future drug–drug interactions [e.g., dalcetrapib (Derks et al. 2009)], to assess differences between healthy subjects and patients [e.g., HIV-positive patients (Jetter et al. 2010)], and to study the effect of combined treatments (Wyen et al. 2008). Most of these cocktails assess the activity of several CYPs and a few of them target phase II enzymes such as N-acetyltransferase 2 (Chainuvati et al. 2003), xanthine oxidase (Chainuvati et al. 2003; Jones et al. 2010) or P-glycoprotein (P-gp)-mediated efflux transport (Wyen et al. 2008; Dumond et al. 2010; Jetter et al. 2010). Some CYPs, phase II enzymes, and transporters of great importance to DMPK are not assessed by validated cocktails. These include CYP2C8, uridine diphosphoglucuronosyl transferase (UGT), and organic anion-transporting polypeptide 1B (OATP1B1). CYP2C8 is known to interact with more than 5 % of 3,486 drugs (Rendic 2002) and affects the activity of several drugs including paclitaxel, amiodarone, chloroquine, amodiaquine, and repaglinide (Samer et al. 2013), as well as endogenous compounds such as arachidonic acid and retinoic acid. UGT isoforms are involved in the metabolism of many drugs such as buprenorphine, etoposide, retigabine, ezetimibe, irinotecan (UGT1A1), deferiprone (UGT1A6) and mycophenolic acid, raloxifene, propofol, and sorafenib (UGT1A9). They catalyze nearly 35 % of conjugation reactions and represents 10 % of drug metabolism (Evans and Relling 1999). OATP1B1 is an influx transporter highly expressed in the liver, which enables the transfer of drugs from the blood into the cytosol of the hepatocytes. It greatly contributes to the hepatobiliary elimination of xenobiotics and endogenous compounds (e.g., methotrexate, conjugated bilirubin).

Activities of CYP2C8, UGTs and OATP1B1 can be modulated by other drugs [e.g., efavirenz for UGT1A1 (Lee et al. 2012), imatinib for CYP2C8 (Samer et al. 2013)], leading to drug–drug interactions, as the lopinavir/ ritonavir combination lowers the formation of SN-38 glucuronide by 36 % through inhibition of UGT1A1 (Corona et al. 2008). A few years ago, we proposed the development of the CIME (for MEtabolic Identity Card, i.e., the determination of DMPK enzyme activities in an individual) combination of ten molecules, as a future cocktail. The plan was to use the CIME combination to quantify new enzymes/transporters (CYP2C8, UGTs and OATP1B) in addition to wellestablished probes for major CYPs. At present, there is no fully specific probe for the latter enzymes/transporters. However, we hypothesize that including probes with possible overlapping selectivity for several targets could offer relevant information. The best example is the widely used midazolam substrate of both CYP3A4 and 3A5. A lack of such information could be remedied by additional experiments, using redundant information provided by other components of the cocktail or choosing the most appropriate metabolite. The CIME combination was therefore designed to study the pooled activity of OATP1B1 & 1B3, the pooled activity of UGT 1A1, 1A6, 1A9 & 2B15, and the activity of P-glycoprotein and of CYP2C8, by the addition of rosuvastatin, acetaminophen (acetaminophen glucuronide), digoxin and repaglinide (M4-hydroxy-repaglinide), respectively, to a widely used more conventional cocktail composed of caffeine (CYP1A2), tolbutamide (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), midazolam (CYP3A) (Tomalik-Scharte et al. 2010; Wohlfarth et al. 2012; Doroshyenko et al. 2013). Finally, we added memantine to the CIME combination to study the renal excretion of drugs (active tubular secretion), since the plasma pharmacokinetics of memantine correlates with urine pH and memantine is not metabolized (Freudenthaler et al. 1998). After development and validation of a simultaneous LC–MS/MS bioanalytical assay for the substrates of the CIME combination and main relevant metabolites (Videau et al. 2010), the CIME combination was used as an index of blood–brain barrier permeation in an in vitro model (Lacombe et al. 2011), to demonstrate the drug-metabolizing capacity of a microfluidic biochip containing primary human hepatocyte cultures (Prot et al. 2011), and to phenotype several CYP activities in rat (Videau et al. 2012). Before any further validations of the CIME combination as a phenotyping cocktail, it is essential to ensure that this ten-drug combination generates no safety concerns and that full pharmacokinetic profiles can be generated for all the probes and metabolites involved in assay of CYP activities. Here, we conducted a prospective clinical study in healthy

Eur J Drug Metab Pharmacokinet

Caucasian volunteers with the main objectives of (1) evaluating the safety of the CIME combination given at low doses resulting in circulating levels sufficient for accurate bioanalytical determination, and (2) describing the pharmacokinetic parameters of the probes and their metabolites following a concomitant single oral administration.

2 Materials and methods 2.1 Study design This was a single-center, open-label pilot, phase I prospective clinical study conducted at the Bichat-Claude Bernard Hospital Clinical Investigation Center (Paris, France). The study protocol was approved by the French Medicines Agency and the Ile-de-France VI Committee for the Protection of Human Subjects participating in Biomedical Research. The legal sponsor was INSERM. The study was carried out in accordance with the Declaration of Helsinki, followed the International Conference on Harmonization Guidelines for Good Clinical Practice, and was registered at ClinicalTrials.gov (NCT01188525). Written informed consent was obtained from all volunteers before any study procedure and after adequate explanations. Ten healthy Caucasian subjects (6 males, 4 females) aged from 19 to 42 years and with body mass index from 19.9 to 29.7 kg/m2 were enrolled. They were in good health, based on medical history, physical examination, and standard laboratory tests including hematology, serum chemistry, urinary analysis and 12-lead electrocardiogram (ECG). Additional inclusion criteria were: negative urine test for cannabinoids, opioids and amphetamines; no history and no presence of drug or alcohol abuse; negative urinary pregnancy test and the use of a non-oral contraceptive method for women of childbearing potential. Medications were not permitted within 7 days prior to the drug administration and during the study, except for the single use of an analgesic for a mild event and in any case after the PK collections. Consumption of St John’s Wort-, grapefruit- or caffeine-containing products was prohibited within 24 h prior to administration of the CIME combination and during the study. Subjects included were studied in real-life conditions without a special wash-out of interacting substances. After an overnight fast, the CIME combination (acetaminophen 60 mg, repaglinide 0.25 mg, dextromethorphan 18 mg, digoxin 0.25 mg, memantine 5 mg, midazolam 4 mg, omeprazole 10 mg, rosuvastatin 5 mg, tolbutamide 10 mg, caffeine 73 mg) was administered orally with 200 mL of water at approximately 8:00 AM. Subjects fasted for 2 h after the administration and remained at the

clinical investigation center for 12 h in total following administration. They returned to the center on day 1, day 2, day 3 and day 7 post-administration for both safety followup and PK sampling purposes. 2.2 Genotype assessment Specific genotypes for CYPs with known polymorphisms were not considered as an inclusion or an exclusion criterion. However, genotyping of genomic DNA from blood samples was performed for each subject to assess their CYP2D6, CYP2C9, CYP2C19, ABCB1 and OATP1B1 metabolizer status. All volunteers provided written informed consent and approved the pharmacogenetic analysis. Genotyping was performed in the Hoˆpital Europe´en Georges Pompidou, Paris. Genomic DNA was extracted from peripheral blood leukocytes using the QiaAmp DNA mini Kit (Qiagen, Courtaboeuf, France) according to the recommendations of the manufacturer. The SNPs CYP2D6*3 (2549delA, rs35742686),*4 (1846G[A, rs3892097), and *6 (1707delT, rs5030655); CYP2C9*2 (455C[T, rs1799853), *3 (1100A[C, rs1057910); CYP2C19*2 (681G[A, rs4244285) and *17 (-806C[ T;rs12248560); ABCB1 (3435C[T, rs2032582 and 2677G[T/A, rs1045642) and SLCO1B1 (521T[C, rs4149056) were identified using Taq ManÒ Drug Metabolism Genotyping Assays (Applied Biosystems, Courtaboeuf, France). The CYP2D6 gene deletion (CYP2D6*5) and duplication (CYP2D6*1X or, *2XN) were analyzed by long PCR (the PCR protocol and primers are available on request). The prediction of CYP2D6, CYP2C9 and CYP2C19 phenotypes was based on the data from ‘‘The Human Cytochrome P450 (CYP) Allele Nomenclature Database’’ (www.cypalleles.ki.se/). 2.3 Safety assessment During the 12-h hospitalization and between each followup visit, volunteers were instructed to complete a diary card with description of all symptoms experienced since the last visit. The relationship of adverse events (AEs) to the CIME combination was determined by the principal investigator. Clinical examination and laboratory tests (hematology and serum chemistry) were performed at screening (baseline) and on day 7 post-administration (endpoint). Values outside the clinical range corresponding to healthy individuals and considered as clinically relevant by the principal investigator were reported as an AE. Vital signs, 12-lead electrocardiogram and physical examination were regularly performed within the 12-h hospitalization and at each follow-up visit (days 1, 2, 3 and 7). Blood glucose level was monitored at hours 4 and 12 postadministration. Real-time monitoring of digoxin (AxSYM

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process) was also performed on-site on all the 12-h blood samples collected following combination administration. 2.4 Pharmacokinetic assessment Blood samples were collected in heparinized tubes before administration and 0.25, 0.5, 0.75, 1.0, 1.5, 2, 3, 4, 5, 6, 8, 10, 12, 24, 48, 72, and 168 h afterwards. Blood was centrifuged and plasma was collected in two separate aliquots stored at -80 °C until analysis. Probes and metabolites were assayed by means of an LC–MS/MS method previously developed and validated (Videau et al. 2010) on a XEVO TQ MS from WATERS. Repaglinide and M4hydroxy-repaglinide (transitions: 453.2 [ 230.2 and 469.4 [ 246.1, respectively) were added to the previously developed assay (Videau et al. 2010) instead of amodiaquine, but were assayed simultaneously in the clinical samples. Lower limits of quantification (LLOQ) were 0.05 ng/mL for repaglinide, M4-hydroxy-repaglinide and digoxin and are reported elsewhere for the other compounds (Videau et al. 2010). For the last value below the LLOQ in the ascending phase of the PK profile and for the first value below the LLOQ in the descending phase, a value of one-half of the quantification limit was used; remaining data below the LLOQ were excluded. The PK parameters (maximum observed concentration, area under the plasma concentration–time curve from 0 to infinity, terminal elimination half-life and apparent clearance) were calculated by means of non-compartmental analysis using an in-house PK module developed in the R statistical software and crossvalidated with WINNONLINÒ (Pharsight, Mountain View, CA, USA) commercial software. Concentrations of substrates and metabolites and nominal sampling time were used to estimate PK parameters in each volunteer. 2.5 Statistical analyses PK parameters and safety data were summarized using descriptive statistics (geometric mean, range and coefficient of variation equal to 100 x standard deviation/ arithmetic mean). The non-parametric Wilcoxon matchedpairs signed-ranks test was used to compare safety clinical values at baseline and on day 7 post-administration. A P value less than 0.05 was considered statistically significant. This study was not designed as a comparative study and the sample size was not statistically calculated: as the pilot study was designed to assess the pharmacokinetics and safety, ten subjects were considered a relevant number. Based on the current study (average value at baseline and standard deviation of the difference between baseline and endpoint), 10 subjects were sufficient to detect a

30 % change with a power of 90 % (alpha-level 5 %) in all the clinical parameters, except for neutrophils, eosinophils, basophils (where 14 subjects were required) and creatinine phosphokinases (where 20 subjects were required). Analyses were done using the R statistical software.

3 Results 3.1 Pharmacokinetics A few concentrations were above the LLOQ for two minor metabolites (3-methoxymorphinan, 4-hydroxy-midazolam), so no PK parameters were estimated for these metabolites. No hydroxy-repaglinide concentrations were above the LLOQ for 2 out of 10 volunteers. For the 10 substrates and the 7 remaining metabolites, at least 6 consecutive concentrations above the LLOQ were available per volunteer. The excluded samples corresponded to early or terminal sampling times (concentration \ LLOQ or re-intake of caffeine). Individual plasma concentration– time courses are shown in Figs. 1 and 2. Calculated pharmacokinetic parameters for each substrate and quantifiable metabolite(s) are shown in Table 1. Seven volunteers had detectable plasma concentrations of caffeine and paraxanthine in the pre-dose sample despite the 24-h caffeine deprivation. A correction was applied to these volunteers, except for one with a too high paraxanthine residual concentration (supplementary material). No difference was observed in the substrate AUC? to metabolite AUC? ratio (MR) before and after correction (1.54 vs 1.52). The genes CYP2D6, CYP2C19, CYP2C9, SCLOB1, and ABCB1, which are known to modulate the pharmacokinetics of some CIME molecules, were genotyped. Several polymorphisms were observed for the CYP2D6 gene (*1/ *1, n = 5; *1/*3, n = 1; *1/*4, n = 2; *1/*6, n = 1; *4/ *5, n = 1). However, in view of the high number of polymorphisms (http://www.cypalleles.ki.se/cyp2d6.htm), we cannot exclude the presence of rare mutations in the subjects designated as having the wild-type genotype. Subject 4 with two deficient alleles for CYP2D6 (and therefore considered as a poor CYP2D6 metabolizer) presented high dextromethorphan concentrations, low dextrorphan concentrations and high substrate AUC? to metabolite AUC? ratio (MR) compared with the other volunteers (80.9 vs 0.05–1.49) (Figs. 1, 3). A subject with intermediate dextromethorphan concentrations and normal concentrations of dextrorphan was also identified, despite his wild-type genotype (MR = 1.49). In the remaining eight subjects, the MRs of subjects with no identified mutations were systematically lower than those with one

Eur J Drug Metab Pharmacokinet Table 1 Calculated PK parameters for each substrate and their quantifiable metabolite(s) Dose (mg)

Subject (samples)

Cmax (ng/ml)

Acetaminophen

60

n = 10 (166)

1,103 (20 %) (895–1,630)

4,682 (24 %) (2,998–6,461)

6.0 (31 %) (3.5–9.2)

12.8 (26 %) (9.3–20.0)

–

Acetaminophen glucuronide

–

n = 10 (160)

848 (15 %) (711–1,085)

6,661 (22 %) (5,082–9,901)

4.9 (41 %) (3.9–11.0)

–

0.70 (29 %) (0.42–1.10)

Caffeine (before correction)

73

n = 10 (165)

1,766 (13 %) (1,472–2,262)

16,031 (42 %) (10,235–35,744)

5.9 (44 %) (3.5–13.7)

4.6 (30 %) (2.0–7.1)

–

Paraxanthine (before correction)

–

n = 10 (165)

603 (31 %) (383–1,023)

10,418 (46 %) (7,518–25,046)

7.4 (44 %) (1.7–16.3)

–

1.54 (21 %) (0.98–2.11)

Dextromethorphan

18

(136) n=9

0.96 (118 %) (0.430–5.62)

7.40 (161 %) (2.18–80.7)

4.8 (79 %) (1.56–17.1)

2,431 (84 %) (223–8,261)

–

n=1

11.73

622

39.7

28.9

–

37.5 (27 %) (20.5–54.2) 7.69

4.8 (34 %) (3.7–9.0) 10.4

–

0.2 (129 %) (0.05–1.49) 80.9

Molecule

EM PM Dextrorphan

–

EM

AUC? (ng h/ml)

t1/2 (h)

CL/F (l/h)

AUC? AUC?

substrate/ metabolite

(160) n=9 n=1

6.86 (40 %) (3.8–12.2) 0.643

Digoxin

0.25

n = 10 (184)

0.50 (36 %) (0.27–0.85)

11.2 (47 %) (5.14–23.5)

46.8 (54 %) (17.0–107.6)

22.3 (52 %) (10.63–48.64)

–

Memantine

5

n = 10 (187)

7.0 (17 %) (4.9–8.4)

527 (21 %) (364–649)

56.8 (35 %) (24.7–99.1)

9.48 (24 %) (7.70–13.73)

–

Midazolam

4

n = 10 (148)

20.6 (25 %) (13.9–31.8)

60.0 (39 %) (31.9–110)

2.9 (65 %) (1.4–7.6)

66.7 (37 %) (36.5–126)

–

1-Hydroxymidazolam

–

n = 10 (166)

37.1 (52 %) (9.67–56.1)

79.1 (51 %) (35.7–165)

6.1 (39 %) (3.9–10.4)

–

0.76 (83 %) (0.34–2.48)

Omeprazole

10

n = 10 (106)

88.7 (41 %) (36.7–172)

157 (42 %) (84.7–336)

0.9 (89 %) (0.4–3.4)

63.9 (35 %) (29.7–118)

–

5-Hydroxyomeprazole

–

n = 10 (131)

84.3 (47 %) (40.9–160)

201 (28 %) (124–279)

1.6 (93 %) (0.9–6.9)

–

0.78 (38 %) (0.48–1.33)

Omeprazole sulfone

–

n = 10 (133)

26.4 (58 %) (11.3–71.0)

89.7 (43 %) (47.1–198)

1.9 (39 %) (1.3–3.7)

–

–

Repaglinide

0.25

n = 10 (112)

1.4 (46 %) (0.5–3.1)

2.12 (54 %) (1.03–5.36)

0.8 (53 %) (0.3–2.0)

118 (47 %) (46.7–243)

–

Hydroxyrepaglinide

–

n = 8 (35)

0.137 (22 %) (0.110–0.189)

0.180 (32 %) (0.097–0.311)

0.49 (27 %) (0.41–0.83)

–

11.4 (55 %) (5.3 – 27.1)

Rosuvastatin

5

n = 10 (169)

1.8 (30 %) (1.1–2.6)

20.8 (59 %) (12.8–56.8)

15.3 (58 %) (10.1–44.0)

241 (40 %) (88.1–390)

–

Tolbutamide

10

n = 10 (177)

1287 (27 %) (914–1976)

13977 (28 %) (8976–21017)

8.2 (18 %) (5.8–11.1)

0.72 (29 %) (0.48–1.11)

–

4-Hydroxytolbutamide

–

n = 10 (168)

6.7 (36 %) (3.7–11.3)

100 (24 %) (69.2–135)

11.1 (21 %) (8.2–14.5)

–

140 (40 %) (80.5–253)

PM

(–)

–

Tabulated values are geometric means, CV % and range

deficient allele (MR ranging from 0.05 to 0.15 for *1/*1 vs 0.22 to 0.42 for heterozygous). Several genotypes were also found for CYP2C9 (wild-type *1/*1, n = 5; *1/*2 heterozygote, n = 4 and *2/*2 homozygote, n = 1). It has been reported that the *1/*1, *1/*2 and *2/*2 allelic variants all exhibit extensive metabolic activity (Kirchheiner et al. 2002). Figure 2 shows this overlap among genotype groups especially due to one subject *1/*1 with a

lower metabolic activity. The polymorphisms observed for CYP2C19 (*1/*1, n = 3; *1/*17, n = 6; *2/*17, n = 1) correspond to an extensive metabolizer status. Polymorphisms of SLCOB1 coding for OATP1B1 were observed (c.521 TT, n = 5; c.521 CT, n = 3; c.521 CC, n = 2), with no effect on rosuvastatin AUC? or on repaglinide AUC? (data not shown). No effect of ABCB1 genotype was apparent on digoxin AUC? (data not shown).

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3.2 Safety Nine volunteers experienced mild or moderate adverse events (Table 2), notably somnolence, as expected, after midazolam administration. No serious adverse events were reported during the trial. A small significant decrease between baseline and endpoint values was observed in some clinical parameters, but these differences were not clinically relevant since all the corresponding values remained within the clinical range corresponding to healthy individuals (red blood cell count, P value = 0.018, values at endpoint: 3.9–5.1 9 1012/L1, change between baseline and endpoint: -0.46 to 0.2 9 1012/L1; hemoglobin, P value = 0.016, values at endpoint: 12–15.6 g/dL, change between baseline and endpoint: -1.4 to 0.4 g/dL; hematocrit, P value = 0.014, values at endpoint: 35.3–44.2 %, change between baseline and endpoint: -3.6 to 1.3 %; and sitting diastolic blood pressure, P value = 0.044, values at endpoint: 101–125 mmHg, change between baseline and endpoint: -23 to 6 mmHg). ECG records revealed no abnormalities in any treated volunteers and were within normal limits (QT/QTc interval \450 ms for all volunteers and at all time-points). No hypoglycemia was noted. The range of observed maximum digoxin concentration (Cmax) was 0.25–0.85 ng/mL. It remained in the therapeutic range (0.5–1 ng/mL) and well below the toxicity threshold (2.5 ng/mL) (Bauman et al. 2006) in all volunteers.

4 Discussion In the present study, we demonstrated that the CIME combination was well tolerated and that the selected low doses (ranging from 5 to 50 % of the commonly used therapeutic doses) lead to circulating levels sufficient for accurate bioanalytical determination. We were also able to estimate the main PK parameters for all the substrates and metabolites, except for 3-methoxymorphinan and 4-hydroxy-midazolam (metabolites of dextromethorphan and midazolam, respectively, through CYP3A4), which were present at concentrations too low for the analytical method and instrument. No obvious difference in the pharmacokinetics of the CIME probes and their metabolites was noted in this study compared with literature values, following administration separately or in a cocktail (see Table 3 for a non-exhaustive literature review) for caffeine (after correction, see Supplementary Materials), dextromethorphan (EM), digoxin, memantine, and rosuvastatin. Largest deviations were observed for the elimination of some metabolites. Published values of acetaminophen t1/2

[2.6 h (Critchley et al. 2005)] obtained at therapeutic dosages seem to be smaller than the value obtained in this study (6.0 h). Our data are, however, very close (6.0 vs 5.8 h) to the value reported after dosing of 0.1 mg acetaminophen using a microdose cocktail (Lappin et al. 2011). Other acetaminophen PK parameters and acetaminophen AUC to glucuronide metabolite AUC ratio were close to the literature values (see Tables 2, 3). Mean 1-hydroxy-midazolam Cmax and t1/2 also differed from literature values (37.1 ng/mL and 6.1 h vs 4.7–10.7 ng/mL and 1.6 h, respectively) (Bornemann et al. 1985; Uchida et al. 2006). It seems that the elimination of the 1-OH-midazolam was unexpectedly lower in our study than in the literature. The mean midazolam/1OH-midazolam AUC ratio was 0.76 vs literature values of 2–5. The PK values of omeprazole and its metabolites vary among published studies. For example, Cmax ranges from 22 (Kita et al. 2002) to 810 (Calabresi et al. 2004) ng/mL after a 20 mg oral dose, but from different formulations. Our results are nevertheless in agreement with those published in a cocktail study and obtained for both simultaneous and separate administration (t1/2 of 0.9 h for CIME vs 0.9, CL/F of 63.9 vs 50.5 L/h and normalized Cmax of 84.3 vs 76.5 ng/mL). Several polymorphisms are known to affect the activity of CYPs and transporters involved in the pharmacokinetics of the CIME molecules. CYP2D6*3, *4 and * 6 and the gene deletion *5 account for 95–99 % of the poor CYP2D6 metabolizers in the Caucasian population (Samer et al. 2013). Two allelic variants of CYP2C9 are frequently observed in Caucasians: *2 (allelic frequency of 8–14 %) and *3 (4–16 %) (Schwarz 2003), among them the *1/*1, *1/*2 and *2/*2 are classified as extensive, *1/*3 and *2/ *3 as intermediate and *3/*3 as slow metabolizers (Kirchheiner et al. 2002). Variant allele CYP2C19*2 (12–15 % in Caucasians) is associated with a loss of function and *17 (16–21 %) with a gain of function (Samer et al. 2013). Single-nucleotide polymorphism (SNP) c.521T[C in the gene encoding OATP1B1 is associated with reduced activity of OATP1B1 and increased plasma concentration of rosuvastatin and repaglinide in humans (Niemi et al. 2005; Pasanen et al. 2007). Some other polymorphisms have also been reported, but their impact in vivo remains controversial [e.g., the SNP 3435 C[T of ABCB1 coding for P-gp, associated with increased expression in duodenum, but conflicting effect on P-gp activity (Chowbay et al. 2005)]. Genotyping of individuals was performed in the study, but it was neither a primary objective nor an inclusion criterion. As a consequence, there were too few subjects in each genotype group to investigate statistically significant changes in the main PK parameters between genotypic groups. The CIME drug combination

Eur J Drug Metab Pharmacokinet

Fig. 1 Individual plasma concentration–time courses of acetaminophen and acetaminophen glucuronide (UGT1A1, 1A6, 1A9 and 2B15), caffeine and paraxanthine (CYP1A2), dextromethorphan and

dextrorphan (CYP2D6), digoxin (Pgp), midazolam and 1-hydroxymidazolam (CYP3A4). PM poor metabolizer, EM extensive metabolizer

nevertheless revealed the poor CYP2D6 metabolizer exhibiting the *4/*5 variants. The CIME combination was designed with the final aim of developing a new phenotypic cocktail targeting a large number of DMPK enzymes and proteins such as CYP2C8, UGT1A1/1A6/1A9/2B15, P-glycoprotein, OATP1B1 & 1B3, and/or active renal secretion besides more conventional targets (CYP1A2, 2D6, 3A, 2C9 and 2C19). At this stage of development, the CIME combination cannot be considered as a validated cocktail, since (1) lack of interaction between probes has not yet been formally

demonstrated and (2) the specificity of some of these probes (acetaminophen, rosuvastatin) is questionable. The CIME combination was designed to limit the risk of potential interaction between probes by: (a) selection of well-known substrates with no or few predictable interactions based on the Metabolism and Transport Drug Interaction Database (http://www.druginteractioninfo.org/) and the literature and (b) choice of low doses [previously discussed in (Videau et al. 2010)], but not microdoses minimizing pharmacokinetic linearity issues. The probe doses are generally below the therapeutic range, but are used only

Eur J Drug Metab Pharmacokinet

Fig. 2 Individual plasma concentration–time courses of memantine (tubular renal reabsorption), omeprazole, 5-hydroxy-omeprazole (CYP2C19) and omeprazole sulfone, repaglinide and hydroxyl-repaglinide (CYP2C8), and tolbutamide and 4-hydroxy-tolbutamide (CYP2C9)

for metabolic purposes and allow the production of metabolites for all the CYPs studied. Caffeine, dextromethorphan, midazolam, omeprazole and tolbutamide are included in published cocktails for which lack of interactions has been demonstrated (Frye et al. 1997; Bruce et al. 2001). It has been reported that omeprazole increases digoxin bioavailability beyond its toxicity threshold (Kiley et al. 2007), but (1) if probes are given simultaneously and in single doses, this interaction is very unlikely, and (2) the combination of 1 mg digoxin and 20 mg omeprazole did not lead to a clinically significant increase in digoxin Cmax or AUC in another study (Oosterhuis et al. 1991). In this

study, no interaction was found: geometric mean digoxin Cmax was 0.5 ng/mL (highest value 0.8 ng/mL), which remains below the toxic plasma threshold [2.5 ng/mL (Bauman et al. 2006)]. Together with the fact that no large deviation of PK parameters was observed compared with the literature, a complete validation study can now confidently be performed. With regards to specificity concerns, future development of the CIME combination will consist in verifying the sensitivity and specificity of the probes after the action of well-known modulators for the enzymes and transporters concerned. Indeed, specificity problems may arise from the

Eur J Drug Metab Pharmacokinet

Fig. 3 Individual phenotypic indexes for CYP2D6 and CYP2C9 as a function of CYP genotypes. NM non-mutated, HM carrier of one mutated allele, MM carrier of two mutated alleles Table 2 Adverse events following a single oral administration of the CIME ten-drug combination Adverse event

n

Occurrence time

Duration

Somnolence

8

40 min–6 h

20 min–3 h

Dizziness

3

40 min–12 h

5 min–2 h

Headache

2

1 h and 1 day

1 h; \1 day

Blood pressure drop

2

3 h; 8 h

\3 h; \1 day

Nausea

1

14 h

30 min

Atrial extrasystole

1

8 h 30

Disappeared at the day 1 follow-up

Diarrhea

1

3h

30 min

Abdominal pain

1

48 h

1 day

choice of new probes, since no fully specific probes are available to phenotype OATP1B1/3, CYP2C8 or UGT. When we started developing the CIME combination, we selected rosuvastatin as a probe for OATP1B. Rosuvastatin is proposed by the FDA guidance (Drug Interaction Studies—Study Design, Data Analysis, Implications for Dosing, and Labeling Recommendations, February 2012) as a probe for OATP1B1 because it is a substrate of this transporter (Fan et al. 2008), is weakly metabolized (76.8–90 % excreted unchanged) (Martin et al. 2003) and its pharmacokinetic profile is closely related to OATP1B1 genetic polymorphism (Pasanen et al. 2007; Choi et al. 2008). However, more recently it has been shown that rosuvastatin pharmacokinetics could also depend on BCRP and on OATP1B3 activity (Zhang et al. 2006; Choi et al. 2008). Pitavastatin would have been a relevant alternative

since recent work suggests that other transporters, such as BCRP, have a minimal impact on its pharmacokinetics and that pitavastatin is a better substrate than rosuvastatin for OATP1B1 (Prueksaritanont et al. 2014). We continue to believe that rosuvastatin is still a worthwhile choice since there are as yet no fully specific substrates for OATP1B, and most drugs interact with several transporters such as OATP1A1 and 1B3. This is the case for other statins, for methotrexate (van de Steeg et al. 2013), for conjugated bilirubin and for rifampicin (Iusuf et al. 2012). Thus, overlapping selectivity may be appropriate for simultaneous phenotyping of the global activities of these pathways. Similarly, several probes have been proposed for the determination of CYP2C8 activity such as amodiaquine, paclitaxel, rosiglitazone, and repaglinide. Amodiaquine

Eur J Drug Metab Pharmacokinet Table 3 Non-exhaustive summary of published studies of ‘CIME’ substrates administered alone Molecule

References

Dosea

n

Cmax (ng/ml)

AUC? (ng h/ml)

CL/F (l/h)

t1/2 (h)

AUC substrate/ AUCmetabolite (–)

Acetaminophen

(Critchley et al. 2005)

20 mg/kg

9

18,700

83,000

16.9b

2.6

–

c

5.8

–

(Lappin et al. 2011)

100 lg

Ace. glucuronide

(Critchley et al. 2005)

20 mg/kga

Caffeine

(Jodynis-Liebert et al. 2004)

300 mg

(Kamimori et al. 2002) (Perera et al. 2011) Paraxanthine Dextromethorphan Dextrorphan

Digoxin Memantine Midazolam

30

1.1

4.8

21.6

11,200

90,600

–

4.5

0.92

20

–

–

6.58b

4.3

–

100 mg

12

1,840

14,700

8.12b

–

–

100 mg

30

1,500

15,500

6.65b

5.5

–

4–9 –

– 1.45 0.75

9

b

(Perera et al. 2012) (Perera et al. 2011)

review 100 mga

– 30

– 500

– 9,700

3.15–8.69 –

(Turpault et al. 2009)

100 mga

30

1,230

18,600

–

–

(Borges et al. 200)

30 mg

11 (EM)

–

19.0

1,289

–

–

(Silvasti et al. 1987)

60 mg

10

5.3

35.2

1,704d

3.2–3.6

–

(Borges et al. 2005)

30 mga

11 (EM)

–

–

–

–

0.01

(Jetter et al. 2010)

30 mga

11 (EM)

–

–

–

–

0.351

(Wyen et al. 2008)

30 mga

24 (EM)

–

–

–

–

0.45

(Larsen et al. 2001)

1 mg

3.73

63.9

16.4

36.9

–

7.9

59.2

–

(Rao et al. 2005)

20 mg

29.3

2,170

(Liu et al. 2008)

5 mg

6.2

486

67

(Bornemann et al. 1985)

7.5 mg

12

34

92

103

2.6

–

(Lam et al. 2003)

10 mg

40

64–85

172–257

46.3–78.4

3.2–7.8

–

(Uchida et al. 2006)

8 mg

10

28.3

167

60.5b

2.9

–

1-Hydroxy-mid.

(Bornemann et al. 1985)

7.5 mg

12

20

48

–

1.6

2

Omeprazole

(Uchida et al. 2006) (Calabresi et al. 2004)

8 mga 20 mg

10 8

9.34 810

41.6 –

– 17.45

– 1.89

5.02 –

5-Hydroxy-ome.

Repaglinide Rosuvastatin Tolbutamide

4-Hydroxy-tol. a

a

(Kita et al. 2002)

20 mg

4

22

402

–

–

–

(Turpault et al. 2009)

20 mg

30

187

396

50.5d

0.9

–

(Calabresi et al. 2004)

20 mga

8

280

–

–

2.79

2.52

(Kita et al. 2002)

20 mga

4

153

362

–

–

1.10

(Shirasaka et al. 2013)

20 mga

9

–

–

–

–

1.20

(Kalliokoski et al. 2008)

0.25 mg

12

3.7

4.7

53.2d

1.5

–

(Blickle 2006)

Review

–

–

–

63.3e

–

–

(Zhang et al. 2006)

20 mg

7

9.9

62.2

385

20.8

–

(Martin et al. 2003)

40 mg

10

18.8

176

227

20.3d

–

(Uchida et al. 2006)

125 mg

10

16,300

179,000

0.78b

7.7

(Gross et al. 1999)

125 mg

10

63,000

798,000

0.637

9.1

–

(Jetter et al. 2004)

125 mg

26

12,200

161,000

0.78

8.3

–

(Uchida et al. 2006)

125 mga

10

294

4,110

–

–

44.7

(Jetter et al. 2004)

125 mga

26

–

2,040

–

–

79

For metabolites (which were not administered to volunteers), given doses are the dose of the corresponding parent probe

b

Conversion from L/h/kg into L/h for a mean weight of 70 kg

c

Conversion from CLiv estimation into CL/F using F = 88 % (Lappin et al. 2011)

d

Estimated using the formula CL/F = dose/AUC

e

Conversion from CLiv estimation into CL/F using F = 60 % (Blickle 2006)

was selected for the first version of the CIME combination (Videau et al. 2010; Prot et al. 2011). However, the ethics committee was surprised by this use since several cases of severe toxicity have been reported with amodiaquine

(Guevart and Aguemon 2009). We, therefore, decided to replace this probe. Paclitaxel was ruled out because of its narrow therapeutic index, which may lead to serious safety concerns. Rosiglitazone could have been a relevant choice

Eur J Drug Metab Pharmacokinet

since it is not a substrate of OATP1B1 (Kalliokoski et al. 2008), unlike repaglinide (Niemi et al. 2005), of CYP3A4 (Sall et al. 2012) or of both (Varma et al. 2013). Fortunately, the metabolic ratio of repaglinide to its M4 hydroxy-metabolite, whose formation is predominantly mediated by CYP2C8, is more specific for the assessment of CYP2C8 activity (Sall et al. 2012). Moreover, repaglinide is proposed in the latest FDA and EMA guidance for drug–drug interactions as being a sensitive substrate for OATP1B1. The specificity of the metabolic ratio should be checked in the future using an efficient modulator of CYP2C8 activity (Samer et al. 2013). With regards to UGT, this ‘super family’ includes several isoforms with distinct, but overlapping, substrate and inhibitor selectivity (Miners et al. 2004, 2006, 2010; Court 2005). We selected acetaminophen [since its main metabolic pathway is glucuronidation by UGT1A1/1A6/1A9 (Court et al. 2001) and also UGT2B15 (Navarro et al. 2011)], instead of a more specific substrate of only one UGT isoform because acetaminophen is widely available, inexpensive and well tolerated, and also because these three UGT1A isoforms are involved in the metabolism of many clinically relevant drugs. In the case of lack of change in the acetaminophen/acetaminophen glucuronide phenotyping index, the investigator will have relevant information on the UGT1A pool, as previously studied using acetaminophen as a probe (Volak et al. 2013). In the case that there is a change, additional investigations could be performed using more specific probes such as endogenous bilirubin (UGT1A1) or propofol (UGT1A9) as already reported in neonates (Allegaert et al. 2009). Finally, memantine was selected for the assessment of active tubular secretion, as the renal clearance of memantine at acidic pH exceeds the expected glomerular filtration rate (Freudenthaler et al. 1998). However, (1) lack of published modulators for evaluation of the sensitivity and specificity of this probe, (2) low inter-individual variability observed in this study, and (3) recent findings on the influence of the glomerular filtration rate and gender as well as NR1I2 (c.1663T[C, rs1523130) polymorphism on memantine clearance (Noetzli et al. 2013) preclude meaningful use of this probe in the future. Memantine will therefore not be included in upgraded versions of the CIME combination. The number of blood samples needed for this pilot study could limit use of the CIME combination in clinical practice. However, in the future, we expect to reduce the number of samples by developing a maximum a posteriori Bayesian estimator based on accurate compartmental population models, a flexible approach that is widely used in therapeutic monitoring (Saint-Marcoux et al. 2011). By combining non-linear mixed effect pharmacokinetic modeling of the CIME drug time–concentration profile with

optimal design approaches (e.g., using an individual Fisher Information Matrix) (Combes et al. 2013), a reduced sampling scheme common to several drugs of the CIME combination is currently under investigation. This reduced sampling scheme will be extended to all the drugs and will be consolidated when more clinical data become available in humans (refined population models including covariates and external validation of the sampling scheme).

5 Conclusion In conclusion, this pilot study in the development of the CIME combination in humans shows that the CIME combination of ten probes is safe and allows the production of metabolites by the targeted DMPK enzymes at expected concentrations. Future studies in humans can now confidently be performed to assess further the value of the CIME combination as a phenotyping cocktail. Our future aim is to design an optimized cocktail, including at least caffeine (CYP1A2), tolbutamide (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), midazolam (CYP3A4), and digoxin (P-gp). Repaglinide could be a worthwhile choice for CYP2C8 if the corresponding hydroxyl metabolite is quantified. Acetaminophen could also be used to assess both UGT1A1/6/9 & 2B15 activity. Additional transporter substrates such as rosuvastatin or other statins should be selected, taking into account the most recent literature. Memantine will not be included in future versions of the CIME combination. Conflict of interest

The authors declare no conflict of interest.

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