LITERATURE REVIEW:

MDR1 AS INTESTINAL EFFLUX PROTEIN: INFLUENCE ON DRUG ABSORPTION

AND DRUG-DRUG INTERACTIONS

EXPERIMENTAL WORK:

INTERACTIONS OF ALISKIREN WITH MDR1 INHIBITORS IN VITRO AND

PHARMACOKINETIC MODELING OF THE INFLUENCE OF MDR1 ON INTESTINAL

ABSORPTION

Tiina Koskenkorva

University of Helsinki

Faculty of Pharmacy

Division of Biopharmaceutics and Pharmacokinetics

February 2012

HELSINGIN YLIOPISTO HELSINGFORS UNIVERSITET UNIVERSITY OF HELSINKI

Tiedekunta Fakultet Faculty

Faculty of Pharmacy Osasto Sektion Department

Biopharmaceutics and Pharmacokinetics TekijäFörfattareAuthor

Tiina Koskenkorva Työn nimi Arbetets titelTitle

Literature review: MDR1 as intestinal efflux protein – influence on drug absorption and drug

drug interactions

Experimental work: Interactions of aliskiren with MDR1 inhibitors in vitro and

pharmacokinetic modeling of the influence of MDR1 on intestinal absorption Oppiaine LäroämneSubject

Pharmacokinetics Työn laji Arbetets artLevel

Master’s thesis Aika DatumMonth and year

February 2012 Sivumäärä SidoantalNumber of pages 34 and 35 (+ appendix I)

Tiivistelmä ReferatAbstract

Elucidation of transporter- and/or metabolic enzyme-mediated drug interactions is important

part of early drug development. However the knowledge about clinical consequences of

transporter-mediated drug-drug interactions is still limited and more investigation is needed

to improve our understanding. MDR1 transporter, widely distributed on the pharmacokinetic

barriers in the body (e.g. intestine) and has been shown no limit the bioavailability of drugs.

Substrates of MDR1 are exposed to limited intestinal drug absorption and intestinal drug-

drug interactions due to inhibition of the transporter. In predicting the clinical significance of

an interaction, the principal obstacle has been the limited ability to appropriately scale the

preclinical data into in vivo situation. In vitro-in vivo correlations on the extent of MDR1’s

influence on absorption and standardized predicting methods for drug-drug interactions using

the inhibitory constants (IC50 and Ki) would greatly increase the value of in vitro studies.

Current in vitro and in silico methods for prediction of the influence of MDR1 on intestinal

absorption and related drug-drug interactions are discussed in the literature review. In

addition, the latest regulatory draft guidances (FDA, EMA) are reviewed.

Aliskiren has been shown to be a sensitive MDR1 substrate in vivo and high affinity substrate

for the transporter in vitro. The objective of the experimental work was to study the MDR1-

mediated transport of aliskiren and the related drug-drug interactions in vitro and in silico.

Vesicular transport assay was used to obtain kinetic parameters for aliskiren (Km and Vmax)

and inhibitor potencies (IC50) for ketoconazole, verapamil, itraconazole and its metabolite

hydroxyitraconazole. Ki was further calculated for itraconazole and hydroxyitraconazole.

Aliskiren showed high affinity to MDR1 transporter with a Km value 5 µM, consistent to

what was reported previously in different assay systems. The interactions between aliskiren

and the inhibitors in vitro correlated to the observed interactions in vivo in humans. In

addition, hydroxyitraconazole was shown to be a potent inhibitor of MDR1-mediated

transport of aliskiren in vitro. This suggests that hydroxyitraconazole may contribute to the

pronounced interaction observed between aliskiren and itraconazole in a clinical interaction

study.

A compartmental absorption and transit (CAT) model with added enterocyte compartments

and MDR1 efflux was used to describe the influence of MDR1 on intestinal absorption of

aliskiren in humans. The integration of kinetic parameters (Km) from in vitro studies requires

further optimization on how to describe the intracellular drug concentrations in the model.

Aliskiren is however suitable MDR1 probe substrate to be used in in vitro and in vivo trials in

humans and therefore gives a good basis for developing vitro-in vivo predictive models.

AvainsanatNyckelordKeywords

MDR1, transporter, drug-drug interaction, intestinal absorption, pharmacokinetic modeling SäilytyspaikkaFörvaringställeWhere deposited

Division of Biopharmaceutics and Pharmacokinetics Muita tietojaÖvriga uppgifter Additional information

Supervisors: Kati-Sisko Vellonen, Mikko Niemi and Arto Urtti

HELSINGIN YLIOPISTO HELSINGFORS UNIVERSITETUNIVERSITY OF HELSINKI

Tiedekunta Fakultet Faculty

Farmasian tiedekunta Osasto Sektion Department

Biofarmasia ja farmakokinetiikka TekijäFörfattareAuthor

Tiina Koskenkorva Työn nimi Arbetets titelTitle

Kirjallisuuskatsaus: MDR1 effluksiproteiini ohutsuolessa – merkitys lääkeaineiden

imeytymisessä ja lääke-lääke interaktioissa

Erikoistyö: Aliskireenin interaktio MDR1 inhibiittoreiden kanssa in vitro ja

farmakokineettinen mallinnus MDR1 kuljetusproteiinin merkityksestä lääkeaineiden

imeytymisessä

Oppiaine LäroämneSubject

Farmakokinetiikka Työn laji Arbetets artLevel

Pro gradu Aika DatumMonth and year

Helmikuu 2012 Sivumäärä SidoantalNumber of pages 34 ja 35 (+ liite I)

Tiivistelmä ReferatAbstract Kuljetusproteiini- ja metaboliaentsyymivälitteisten lääke-lääke interaktioiden ennustaminen

on tärkeä osa lääkkeen kehityskaarta. Kuitenkin tietämys kuljetusproteiinivälitteisten

interaktioiden kliinisistä seurauksista on vielä rajallista ja lisää tutkimusta tarvitaan niiden

ymmärtämiseksi. MDR1 effluksiproteiini ilmentyy mm. suolen seinämässä ja sen on osoitettu

rajoittavan lääkeaineiden imeytymistä. Lääkeaineet, jotka ovat MDR1 kuljetusproteiinin

substraatteja altistuvat sekä rajalliselle imeytymiselle ohutsuolesta, että kuljetusproteiinin

inhibitiosta aiheutuville lääke-lääke interaktioille. Yhteisvaikutusten kliinisen merkityksen

arvioimisen tärkein haaste on ollut in vitro datan skaalaus in vivo tilanteeseen. In vitro – in

vivo korrelaatiot MDR1:n kvantitatiivisesta vaikutuksesta lääkeaineiden imetymiseen sekä

standardisoidut interaktioiden ennustusmenetelmät inhibitioparametrejä (IC50, Ki) hyödyntäen

lisäisivät in vitro kokeiden arvoa suuresti. Kirjallisuuskatsauksessa tarkastellaan yleisimpiä in

vitro ja in silico menetelmiä MDR1:n vaikutuksen tutkimisessa ja ennustamisessa. Lisäksi

esitetään viranomaisten (FDA, EMA) viimeisimmät ohjeistukset MDR1-välitteisten

interaktoiden tutkimisesta.

Aliskireeni on osoittautunut herkäksi MDR1:n inhibitiolle kliinisissä interaktiokokeissa ja

sillä on hyvä affiniteetti kuljetusproteiiniin in vitro. Kokeellisen työn tavoitteena oli tutkia

MDR1-välitteistä aliskireenin kuljetusta ja siihen liittyviä imeytymisvaiheen interaktoita in

vitro ja in silico menetelmillä. Aliskireenille määritettiin kuljetuksen kineettiset parametrit

(Km ja Vmax) vesicular transport (VT) kokeella ja ketokonatsolille, verapamiilille,

itrakonatsolille sekä sen metaboliitille hydroksi-itrakonatsolille määritettiin inhibitio

parametri (IC50). Itrakonatsolille ja hydroksi-itakonatsolille laskettiin myös Ki. Aliskireenin

kuljetus Sf9-MDR1 membraaneissa oli konsentraatiosta riippuvaa Km arvolla 5 µM, osoittaen

hyvää affiniteettiä MDR1 kuljetusproteiiniin myös VT-kokeessa. Yhteisvaikutukset

aliskireenin ja inhibiiittorien välillä in vitro korreloivat hyvin vastaavien kliinisten

interaktiostutkimusten kanssa. Lisäksi kokeessa osoitettiin hydroksi-itrakonatsolin olevan

voimakas MDR1 inhibiittori in vitro, mikä viittaa siihen, että hydroksi-itrakonatsoli saattaa

olla myötävaikuttamassa aliskireenin ja itrakonatsolin voimakkaaseen in vivo interaktioon.

Farmakokineettistä CAT (compartmental absorption and transit) tilamallia käytettiin

kuvaamaan MDR1 kuljetusproteiinin vaikutusta aliskireenin imeytymiseen ohutsuolesta.

Aliskireenin in vitro Km arvon integroiminen malliin vaatii kuitenkin lisää optimointia

solunsisäisen lääkekonsentraation kuvaamiseen mallissa niin, että se vastaisi in vivo tilannetta

ihmisen ohutsuolessa. Aliskireeni kuitenkin soveltuu hyvin käytettäväksi MDR1 substraattina

sekä in vitro, että in vivo kliinisissä interaktiotutkimuksissa, joten sitä voidaan hyödyntää

ennustavien in vitro – in vivo mallien kehitämisessä. AvainsanatNyckelordKeywords

MDR1, kuljetusproteiini, lääke-lääke interaktio, imeytyminen, farmakokineettinen mallitus SäilytyspaikkaFörvaringställeWhere deposited

Biofarmasian ja farmakokinetiikan osasto Muita tietojaÖvriga uppgifter Additional information

Ohjaajat: Kati-Sisko Vellonen, Mikko Niemi ja Arto Urtti

LITERATURE REVIEW: MDR1 AS INTESTINAL EFFLUX PROTEIN - INFLUENCE

ON DRUG ABSORPTION AND DRUG-DRUG INTERACTIONS

Tiina Koskenkorva

University of Helsinki

Faculty of Pharmacy

Division of Biopharmaceutics and Pharmacokinetics

February 2012

TABLE OF CONTENTS

1 INTRODUCTION .................................................................................................... 1

2 ROLE OF MDR1 IN PHARMACOKINETICS ....................................................... 2

2.1 Physiological function and tissue distribution ................................................... 2 2.2 Structure and mechanism ................................................................................... 3 2.3 Interindividual variation in MDR1 expression .................................................. 3

3 INFLUENCE OF MDR1 ON ORAL DRUG ABSORPTION ................................. 4

3.1 Factors affecting intestinal drug absorption ....................................................... 4 3.1.1 Physiological and physicochemical factors ................................................ 4

3.1.2 MDR1 and CYP3A4 interplay .................................................................... 4 3.1.3 Saturation of intestinal MDR1 and CYP3A4 ............................................. 5

3.2 Preclinical methods for studying MDR1-mediated efflux in intestinal

absorption ................................................................................................................... 5 3.2.1 In vitro methods .......................................................................................... 5 3.2.2 In vitro parameters ...................................................................................... 6 3.2.3 In vivo methods ........................................................................................... 7

3.2.4 In vivo parameters ....................................................................................... 7 3.3 In vitro in vivo correlations ................................................................................ 8

3.4 Predicting MDR1’s influence on drug absorption in humans .......................... 10 3.4.1 Physiologically based pharmacokinetic modeling .................................... 10 3.4.2 Utility of models in the prediction of absorption in humans .................... 13

4 MDR1-INHIBITION .............................................................................................. 15

4.1 Mechanism of inhibition .................................................................................. 15 4.2 In vitro methods for studying MDR1 inhibition .............................................. 16

4.2.1 ATPase assay ............................................................................................ 17 4.2.2 Vesicular transport assay .......................................................................... 18

4.2.3 Uptake assay ............................................................................................. 19 4.2.4 Utility of in vitro assays in studying MDR1-mediated interactions ......... 20

4.3 In vitro inhibition parameters ........................................................................... 22 4.4 In vivo methods for studying MDR1-interactions ............................................ 24 4.5 Prediction of intestinal MDR1-mediated drug-drug interactions..................... 25

5 CONCLUSIONS .................................................................................................... 28

6 REFERENCES ....................................................................................................... 29

1

1 INTRODUCTION

One of the major reasons for failure of a leading compound in drug development

process is poor pharmacokinetic qualities. MDR1 transporter is in a significant position

to influence the absorption, distribution and/or elimination (ADME) of a drug due to its

wide distribution on the apical membranes of the body. In order to have a therapeutic

effect, the drug has to reach the systemic blood circulation. The extent of absorption

from the intestine depends on the dissolution, passive permeability and susceptibility of

a drug to MDR1 efflux and/or CYP3A4 metabolism in the intestine.

Clinically significant drug-drug interactions have risen to be a concerning issue for drug

safety. Therefore it is of great importance to predict a drug’s potential to either cause

interactions or be susceptible to them. Oral administration of a drug causes a high level

of exposure in the intestine and concentrations higher than the resulting plasma

concentrations. For this reason, the possibility for transporter saturation is more

significant in the intestine. In addition, already low doses of an MDR1 inhibitor may

cause drug-drug interactions in the intestine rather than in other sites. As MDR1-

mediated efflux can limit the absorption of substrate drugs, inhibitors of MDR1 may

enhance the absorption markedly. Absorption may also vary due to inter-individual

variation in the expression of MDR1. Thus, being a substrate for MDR1 the drug is

exposed to limited absorption, MDR1-mediated drug-drug interactions and high inter-

individuality in pharmacokinetics.

High throughput in vitro assays are frequently applied for screening of substrates for

MDR1. However quantifying the extent to which intestinal absorption is affected by

MDR1or the extent of a drug-drug interaction in vivo in humans is particularly

challenging. The principal obstacle has been the limited ability to appropriately scale

the preclinical data into the in vivo situation. The extent to which in vitro data can

predict in vivo situation needs more investigation and significant in vitro-in vivo

correlations would greatly increase the value of in vitro studies (del Amo et al., 2009).

This requires reliable, reproducible and suitable preclinical in vitro and in vivo animal

data from standardized experiments. In silico physiologically based pharmacokinetic

2

modeling has been utilized to demonstrate MDR1’s contribution on absorption in

humans using in vitro data. Nevertheless standardized methods for predicting intestinal

drug-drug interactions have not yet been established (Tachibana et al., 2010)

2 ROLE OF MDR1 IN PHARMACOKINETICS

2.1 Physiological function and tissue distribution

MDR1 (multidrug resistance 1 protein), also known as P-glycoprotein, was originally

identified over-expressed in tumor cells showing resistance to cancer treatment (Juliano

and Ling 1976). MDR1 belongs to the ABC (ATP-binding cassette) transporter

superfamily and is encoded by gene ABCB1. The ABC superfamily of transporters uses

adenosine triphosphate (ATP) as an energy source to the transfer of substrates out of the

cell against the concentration gradient (Schinkel and Jonker 2003). MDR1 is the most

studied efflux transporter, found located mainly on the apical membranes of the body.

MDR1 is widely distributed, including brush border membrane of intestinal enterocytes,

capillary endothelial cells in the blood-brain barrier, canalicular membrane of

hepatocytes, renal proximal tubular cells and placenta (Cordon-Cardo et al. 1990). Due

to the wide distribution in barrier tissues of the body, MDR1 is suggested to have a

protective role limiting the bioavailability and exposure of substrate drugs.

MDR1-mediated efflux has been shown to limit oral absorption of drugs and cause

variable and nonlinear pharmacokinetics (e.g. talinolol (Wetterich et al., 1996)). The

transport of a drug across the intestinal epithelial depends on its passive permeability

and the active transporter-mediated efflux. MDR1 is suggested to have a significant

importance in distribution of drugs. Distribution into the brain across the blood-brain

barrier has been studied extensively in vivo in mdr1-gene deficient mice and significant

in vitro-in vivo correlations of the extent of MDR1’s influence have been shown

(Hakkarainen et al. 2010). MDR1’s location in hepatocytes and renal tubular cells may

limit the systemic exposure of substrate drugs due to the efflux of drug and metabolites

into the bile and/or into urine via kidneys.

3

2.2 Structure and mechanism

The 170 kDa MDR1 protein consists of 1280 amino acids. It has two homologous

halves each containing 6 membrane spanning α-helices (trans-membrane domain; TMD)

and a nucleotide binding domain (NBD) located in the cytoplasm. MDR1 protein is

post-translationally modified by phosphorylation and N-glycosylation. Distinctive

phosphorylation of MDR1 by kinases has been shown to have an influence on MDR1

activity (Idriss et al., 2000).

MDR1 recognizes a great variety of structurally unrelated compounds that are generally

of hydrophobic and amphipathic nature, thus partition into the lipid layer. The two

models most supported as the mechanism of transport are (1) flippase model, where the

binding site is in the cytosolic (inner) leaflet of the membrane bilayer and drugs are

translocated to the extracellular (outer) leaflet (Higgins and Gottesman 1992) and (2)

the hydrophobic vacuum cleaner model, in which drugs are transported from the

cytosolic leaflet out of the cell into the aqueous phase (Raviv et al., 1990).

2.3 Interindividual variation in MDR1 expression

Involvement of intestinal MDR1 has showed to be a cause of significant interpatient

variation in the oral bioavailability of substrate drugs (e.g. cyclosporine (Lown et al.,

1997)). Interindividual variability in the expression or function of MDR1 might explain

the variation in response to drug therapy, at least to some extent, but the genetic

contribution is still unclear. It has been suggested that ABCB1 gene polymorphisms

contribute to the variability in MDR1 function. The effect of MDR1 genotypes has been

studied the most on pharmacokinetics of digoxin, a common substrate for MDR1, with

modest and conflicting results (Hoffmeyer et al., 2000; Chowbay et al. 2005). Many

other factors, such as exposure to MDR1 inducing chemicals, age, intestinal

inflammation and circadian rhythm have been suggested to affect the intestinal MDR1

expression level (del Amo et al., 2009).

4

There has been extensive research in order to identify correlations between MDR1

genotypes or haplotypes and mRNA or MDR1 protein expression, activity and related

drug response. However majority of studies have failed to demonstrate a significant

associations and the results have been inconsistent (Leschziner et al. 2007). Attempts

have been made to correlate MDR1 mRNA and protein expression levels as well, but no

correlation has been found (Berggren et al., 2007; Canaparo et al., 2007). Considerable

interindividual variability was observed in mRNA levels in the human intestine,

however even higher interindividual variability was seen in MDR1 protein levels

(Berggren et al., 2007). It has been suggested that lack of correlation might be due to

either functional polymorphisms of the MDR1 gene or post-translational mechanisms.

This emphasizes the importance of determining the MDR1 protein levels instead of the

mRNA levels, when studying the relationship between MDR1 gene and the clinical

outcome.

3 INFLUENCE OF MDR1 ON ORAL DRUG ABSORPTION

3.1 Factors affecting intestinal drug absorption

3.1.1 Physiological and physicochemical factors

Absorption from the intestine is influenced by physicochemical properties of the drug

(e.g. solubility, dissolution and permeability) and the physiological factors of the

gastrointestinal tract. In addition to intestinal transporters and enzymes, physiological

variables are gastric emptying, small intestine transit time, gastrointestinal pH, intestinal

blood flow, effects of food, fluids and disease state (e.g. inflammation in the intestine).

3.1.2 MDR1 and CYP3A4 interplay

When studying the extent of drug absorption, besides MDR1 efflux the limiting effect

of gut metabolism has to be considered. CYP3A4 is the most abundantly expressed

CYP enzyme in the intestine (Paine et al., 2006). Due to the overlap of substrate

5

specificities between MDR1 and CYP3A4, the effect of each has to be evaluated.

Moreover an interplay has been proposed. Cummings et al. (2002) suggested that if a

drug is substantially effluxed by MDR1, it can increase the fraction of drug metabolized,

since the effluxed drug is reabsorbed, having more time to be metabolized in the

enterocytes. Because clinically relevant selective inhibitors of either MDR1 or

CYP3A4 have not been identified to date, estimation of their effect on intestinal

absorption of drugs separately is challenging.

3.1.3 Saturation of intestinal MDR1 and CYP3A4

Another consideration is the possible saturation of CYP enzymes and transporters in the

intestine. For example talinolol has showed saturable kinetics after increasing doses in

humans (Wetterich et al., 1996). If a drug is identified being a substrate for MDR1,

further in vitro experiments should be performed using increasing concentrations of the

drug to evaluate the saturability. If the transporter is saturated at the therapeutic doses,

its drug bioavailability would increase after the saturation point. However the prediction

of clinically relevant concentrations, or the local concentration of drug in the intestine

and correlating the activity of MDR1 in a cell line or mouse intestine to the human

intestine, is difficult. Due to saturation, it is possible for a clinical dose of MDR1

substrate to show high fraction absorbed and intestinal availability (FaFg), but in a

microdose clinical study to show low FaFg. This saturation can be assessed by

comparing the FaFg values of a clinical dose and a microdose, when possible (Tachibana

et al., 2010). In silico physiologically based pharmacokinetic modeling can be utilized

to guide the preclinical studies and predict concentrations in vivo in humans.

3.2 Preclinical methods for studying MDR1-mediated efflux in intestinal absorption

3.2.1 In vitro methods

The in vitro assays for studying MDR1-mediated transport can be classified into (1)

uptake (2) transport and (3) ATPase assay (Zhang et al., 2003). All assays are suitable

for screening MDR1 substrates, and in many cases are aimed to identify or classify

6

inhibitors of MDR1 as well. Experimental method that has been applied most frequently

in studying MDR1’s influence in intestinal absorption is the transport assay. Transport

assay is the most informative in screening potential transporter-mediated absorption

issues and the most definite assay to determine the localization of transporters (Zhang et

al., 2003). The transport assay is also recommended in the FDA draft guidance of drug

interaction studies (2006) and EMA draft guideline for investigation of drug interactions

(2010). Cell lines used in the transport assay have to express MDR1 and form a

confluent, polarized cell monolayer with tight extracellular junctions. Immortalized

human colorectal carcinoma derived cell line (Caco-2), where MDR1 is naturally

expressed, has been widely used to measure the bi-directional differences in

permeability. Also, MDR1-transfected Madine-Darby canine kidney cell line (MDCKII)

and MDR1-transfected pig-kidney cell line (LLC-PK1) have shown usability due to

their short culture time and availability of wild type cell lines to use as controls (Zhang

et al., 2003). Uptake and ATPase assays are described later when the in vitro methods

for studying MDR1 inhibition are discussed.

3.2.2 In vitro parameters

In transport assay, the flux rate of the drug through the cell monolayer (apparent

permeability (Papp)), is measured in both apical to basal (A-B) and basal to apical (B-A)

directions. Most commonly used parameter is the ratio between the B-A and A-B flux

rates (RB-A/A-B), also called the efflux ratio (ER). Efflux ratio > 2 indicates increased

transport of the drug to the secretory direction (B-A). To confirm that the efflux activity

is due to MDR1, a follow-up experiment with a potent and specific MDR1-inhibitor is

advisable. FDA draft guidance (2006) recommends follow-up experiment for drugs with

efflux ratio > 2. However, some researchers perform follow-up experiments with

MDR1-inhibitor for drugs efflux ratios 1.5 - 2 to further investigate MDR1’s

involvement (Polli et al., 2001; Hubatsch et al., 2007). The efflux of a drug investigated

should be studied over a range of concentrations (e.g. 1, 10 and 100 µM).

7

3.2.3 In vivo methods

Mdr1 knockout mice have been most widely used in in vivo studies and have greatly

improved the understanding of MDR1’s physiological function and influence on

pharmacokinetics. In situ mice and rat intestine perfusion models have been used in

studying the intestinal absorption of MDR1 substrates. Determination of MDR1 effect

only on intestinal absorption is more challenging to study in living animals, since first-

pass metabolism in the liver and MDR1’s effect on elimination of the drug have to

considered. Obviously, in situ models however suffer from the limitation of being an

isolated organ instead in the living body.

In mice, MDR1 is encoded by mdr1a and mdr1b and mdr2. The genes that confer the

multidrug-resistance phenotype are mdr1a and mdr1b. It has been reported that an 82 %

homology exists with human MDR1 and mouse mdr1a, and 75 % homology with

mdr1b (Gros et al. 1988). The single (mdr1a gene or mdr1b gene) and double (mdr1a

and mdr1b) knockout strains in mice have shown to be viable, fertile and have no

apparent physiological abnormalities (Schinkel et al., 1994; Schinkel et al., 1997). Mice

naturally lacking the expression of mdr1a gene product were detected in a

subpopulation of a CF-1 mouse strain (Lankas et al., 1997). The advantage is that the

expression of other mdr1 family gene products is not altered. In mdr1a knockout mouse

strain, the expression of mdr1b has been shown to increase, but the only murine MDR1

isoform present in the intestine is mdr1a suggesting that the model can be well utilized

in studying MDR1’s influence on oral absorption (Schinkel et al., 1994). Nevertheless it

must be kept in mind that disruption of genes may have compensatory effects and

species differences exist between animal and human mdr1 gene and MDR1 transporter.

In addition, extrapolation of MDR1-mediated drug interaction in rodents to humans

must be conducted with caution.

3.2.4 In vivo parameters

Very good in vivo parameters to describe quantitatively the influence of MDR1 on

intestinal absorption do not exist. Most common practice has been to compare oral

8

pharmacokinetic parameters between MDR1 knockout and wild type mice. For example

drug concentration in plasma after oral administration at a certain time point and oral

AUC (del Amo et al., 2009). Often, both the oral and i.v. AUC values for knockout and

wildtype mice have not been calculated in pharmacokinetic studies. This information

would enable the calculations of ratio of oral bioavailability (F). To evaluate the role of

MDR1 in the intestinal absorption specifically, the knowledge of the drug’s first pass

elimination is needed. It has to considered that also the distribution and elimination

parameters may change in MDR1 knowkout animals.

3.3 In vitro in vivo correlations

Troutman and Thakker (2003b) introduced the parameters absorptive quotient (AQ) and

the secretory quotient (SQ). They showed in their previous study (Troutman and

Thakker 2003a) that MDR1 has an asymmetric effect on the transport of compounds

across Caco-2 cell monolayer. Substrates can use different absorptive and secretory

transport pathways. For substrates that use primarily the transcellular pathway, the

apparent Km values have differed in absorptive and secretory directions. The parameters

AQ and SQ would describe directly the attenuation of the absorptive quotient and the

enhancement of the secretory quotient due to MDR1-mediated efflux. Troutman and

Thakker proposed that because efflux ratio does not always provide a good estimate of

the attenuation of intestinal absorption of drugs due to MDR1, the effect of MDR1 on

absorptive transport alone should be used to assess the effect on intestinal absorption.

Absorptive flux is measured under normal cell culture conditions and after complete

inhibition of MDR1 by selective, non-competitive inhibitor (see AQ calculation Table

1 ).

Collett et al. (2004) showed that a permeability assay in Caco-2 monolayers allows a

reasonable prediction of the probable in vivo effect of MDR1 on plasma drug levels

after oral administration. The ratio of A-B permeability measured in the presence and

absence of a selective MDR1 inhibitor (RGF) (Table 1) in Caco-2 monolayers showed a

significant correlation (r2 = 0.8, p < 0.01) with the ratio of plasma drug levels in the

absence and presence of MDR1 in mice (RKO/WT in vivo), data obtained from literature. A

ratio of drug plasma concentrations at a single time point (at 4 h) was used. A strong

9

correlation with RGF was observed also after correction of in vivo ratio with IV data. In

this study, the more commonly used parameter RB-A/A-B showed no correlation with in

vivo data (r2 = 0.33, p = 0.11). Researchers suggested that RGF would be more reliable in

predicting in vivo effect of MDR1 from in vitro results. This result was however

criticized by del Amo et al. (2008) because the plasma drug concentration ratio (without

IV correction) may be influenced also by distribution or elimination and that the IV

corrected correlation was established for 6 drugs instead of 9. They also stated that

because drug concentration-time curves might differ in MDR1 knockout and wildtype

mice, one should be careful in comparing only one time point.

Still, RA-B/B-A is the most frequently used in vitro parameter to compare to in vivo mice

studies of oral absorption (del Amo et al., 2009). Amo et al. reviewed in vitro-in vivo

correlations and reported that in most cases, when RA-B/B-A was reported ≥2, the ratio

between mdr-deficient and wildtype mice of different in vivo parameters (drug

concentration in plasma, AUC oral or oral bioavailability) was higher than 1.

Importantly, they showed that there is a lack of standard in vivo parameters to describe

quantitatively the function of MDR1 in absorption. But, as Troutmar and Thakker stated

(2003a), the parameter RA-B/B-A is affected by both absorptive and secretory flux rates.

Due to this and the varying passive permeability of drug compounds, it seems that

determining the ratio of apparent permeability in absorptive direction in absence and

presence of MDR1-inhibitor (RGF) (or the ratio between A-B flux rates obtained in the

parental and in MDR1-transfected cell line) or the absorptive quotient (AQ) are more

appropriate to use in in vitro-in vivo correlations. The total transfer or drugs across the

cell monolayer is the sum of passive diffusion of the drug and the MDR1-mediated

efflux. For drugs with high passive permeability, it is likely that active transport by

MDR1 is a smaller factor in the overall absorption.

Adachi et al. (2003) performed in situ intestinal perfusion experiments for 12

compounds in mdr1a/1b knockout and in normal mice. The results were compared to

results from their previous permeability assays, determined by comparing the

permeability in MDR1-expressing and parental LLC-PK1 monolayers (Adachi et al.,

2001). The parameter obtained was the permeability-surface area (PS) product. PS

10

product is the product of the apparent membrane permeability coefficient and the

surface area. PS product ratio was further calculated by dividing the PS products in

mdr1a/1b knockout mice by those in normal mice (Table 1). In vitro PS product ratio

(PS A-B) was calculated by dividing the PS product (A-B) of parental LLC-PK1

monolayer by MDR1-expressing monolayer (Table 1). A significant correlation (r =

0.855, P < 0.01) was observed between the parameters. Adachi et al. suggested that

drugs with high PS product ratios may be markedly affected by interindividual

differences in the expression of MDR1 and by coadministered substrates or inhibitors.

Proposed parameters for in vitro – in vivo correlations.

Parameter Definition Reference

In vitro RGF

Ratio between A-B flux

rates in the presence

(Ppass A-B) and absence

(Papp A-B) of MDR1

inhibitor

Collet et al., 2004

Absorptive quotient

(AQ)

Ratio between (Ppass A-B -

Papp A-B) and Ppass A-B

Troutman and Thakker

2003a

PS product ratio (PSA-B) Ratio between PS

product A-B of

parenteral monolayer

and MDR1-expressing

monolayer

Adachi et al., 2003

In situ PS product ratio Ratio between PS

products of mdr1a/1b

knockout mice and

normal mice

Adachi et al., 2003

In vivo F, AQin vivo p.o. and i.v. AUC values

for both knockout and

wildtype rodents are

needed

del Amo et al, 2008;

Troutman and Thakker

2003a

3.4 Predicting MDR1’s influence on drug absorption in humans

3.4.1 Physiologically based pharmacokinetic modeling

In physiologically based pharmacokinetic (PBPK) modeling, the pharmacokinetic

processes (ADME) of a drug are mathematically demonstrated by using physiological

and anatomical descriptions and physicochemical properties of the drug. In silico PBPK

modeling can be used as a tool to guide in vitro and in vivo studies and potentially to

reduce preclinical animal studies. Interspecies differences of transporters have to be

Table 1.

11

acknowledged when extrapolating animal results to human, but by developing of

quantitative predictive models this step could potentially be passed. Incorporation of

MDR1 efflux and CY3A4 metabolism in the model highly improves the significance of

predictions. In modeling based on in vitro data, important issues are the relevant

concentration and site of the substrate and what correlation factors are needed to adapt

the in vitro data (e.g. MDR1 expression and Km parameter).

Yu et al. (1996) introduced the compartmental absorption and transit (CAT) model. In

the model small intestine is divided into seven compartments, where the absorption

occurs. Transit of drug through small intestine takes 199 min and follows 1st order

kinetics (Yu et al., 1996).

In advanced compartmental absorption and transit (ACAT) model (Figure 1) each

compartment is modeled with accurate physiological information regarding volumes,

transit time, length and radius (Agoram et al., 2001). Physiochemical concepts, such as

solubility and permeability are more easily incorporated in the model than the

expression and activity of transporters and metabolism. Commercial Gastroplus®

software implements the ACAT model in the simulations.

Figure 1. Structure of the ACAT model (Tubic et al., 2006).

12

The advanced dissolution, absorption and metabolism (ADAM) model is a module

within the Simcyp® Population-Based Simulator (Jamei et al., 2009). It is a version of

the segregated flow model (Cong et al., 2001), which takes tissue layers and

distributions in blood supply into account in describing the intestinal absorption.

ADAM model is however compartmental and based on CAT model. The nine segments

of the gastrointestinal tract differ in terms of size, abundance of transporters and

enzymes, transit time, pH and bile salt concentration. ADAM model assumes enterocyte

a well-stirred compartment, where MDR1 and CYP enzymes compete for the binding of

a substrate. The interindividual variations can be demonstrated by Simcyp® software.

Figure 2. Structure of the ADAM model (Darwich et al. 2010).The ADAM model is

compartmental with segregated blood flows to each section.

13

Figure 3. Structure of the ADAM model (Darwich et al. 2010). In the seven

compartments of the small intestine the drug can dissolve, re-precipitate, be exposed to

chemical degradation, be absorbed and exposed to transporters and/or metabolizing

enzymes.

3.4.2 Utility of models in the prediction of absorption in humans

Kwon et al. (2004) simulated (1) whether the effect of MDR1 in oral absorption would

be significant at clinically relevant concentrations and (2) the role of MDR1 in oral

absorption modeled by a dynamic CAT model linked to a pharmacokinetic model. In

the latter simulation, the ratio of transporter mediated transport to passive transport

(RMDR1) was used to evaluate if MDR1 would reduce the oral bioavailability of drugs

with high solubility. Both simulations suggested that for high-solubility drugs MDR1

altered the bioavailability only at low, well below clinically relevant concentrations.

Tubic et al. (2006) demonstrated involvement of MDR1 in nonlinear absorption of

MDR1-substrate talinolol using the ACAT model. The results predicted from the model

were then compared to a phase I dose escalation study of talinolol, oral doses increasing

from 25 to 400 mg. Talinolol is a selective β-1 antagonist, usually administrated 100 mg

once a day. Talinolol has shown dose-dependent nonlinear absorption, but is

metabolized only < 1%, allowing the examination of drug efflux without the effect of

metabolism in the intestine. However, to demonstrate the clinically observed nonlinear

dose dependence, the experimental Km and Vmax values had to be optimized. The

optimized Km value (0.69 µM) was lower than the experimental Km (412 µM). The

14

researchers suggested that this may result from the fact that the ACAT model uses the

simulated concentration of the cytoplasm of the enterocyte for the interaction with

MDR1, while the concentration of talinolol within the actual binding site (apical leaflet

of membrane bilayer (Shapiro and Ling 1997) would be expected to be higher because

of the hydrophobicity of the molecule. Thus, to obtain a good correlation between in

silico simulations and in vivo data, experimental kinetic parameters Km and Vmax could

not be used.

Badhan et al. (2009) applied the CAT model in simulating the influence of MDR1

efflux, CYP3A4 metabolism and passive permeability on drug available for absorption

within the enterocytes. Preclinical in vitro data was used to model the fraction of drug

escaping the enterocyte (Fg ), the parameter used to quantify the results. Compounds

with varying intestinal metabolic and MDR1 efflux clearances were used to develop the

model. In vitro apparent permeability (PappA-B) was converted to human effective

permeability (Peff), which was further converted to absorption rate constant (Ka). In vitro

MDR1 efflux ratios ranging 1-10 were tested to simulate the intestinal efflux.

Comparison was made to in vivo Fg, which was derived from reported oral

bioavailability (F = Fa × Fg × Fh), where Fh was estimated from in vivo hepatic clearance

(CLh), liver blood flow and hepatic extraction ratio, Fa was assumed. The model

successfully predicted Fg for the range of drugs tested (within 20 % of observed in vivo

Fg) and demonstrated that incorporation of in vitro efflux ratios may be useful in the

prediction of Fg involving MDR1 substrates. The presence of MDR1 increased the level

of CYP3A4 metabolism. Fg was highly sensitive to changes in intrinsic metabolism, but

less sensitive to changes in intestinal drug permeability.

Darwich et al. (2010) applied the ADAM model to simulate the interplay of transport

and metabolism in oral drug absorption. Studied variables were the intrinsic clearances

(CLint) and Km values for MDR1 and CYP3A4. Darwich et al., investigated the effects

of MDR1 and gut metabolism on Fa and Fg of Biopharmaceutics Classification System

(BCS) I – IV compounds. An increase in the intrinsic clearance of CYP3A4 (CLint-

CYP3A4) resulted in a marked decrease in Fg. However, an increase in the intrinsic

clearance of MDR1 (CLint-MDR1) lead to a marked reduction in Fa. Also a minor decrease

15

in Fg was noticed, and the researchers suggested that it may be a cause of decreased

enterocytic concentration due to MDR1-mediated efflux and de-saturation of CYP3A4

enzymes. However the significance of actual interplay of MDR1 and metabolism needs

further studies, but the model shows feasibility to investigate the relative roles of

transporters and metabolism in absorption of drugs.

4 MDR1-INHIBITION

4.1 Mechanism of inhibition

MDR1 recognizes substrates at the cytoplasmic leaflet of the lipid bilayer (Shapiro and

Ling 1997). The transporter has at least two binding sites (Dey et al., 1997; Shapiro and

Ling 1997) that are distinct, but yet dependent (Wang et al., 2000). The binding of a

substrate at one site of MDR1 is suggested to prevent or lower the affinity for binding at

the other site. At least, it seems to be evident, that a tight linkage or allosteric effects

between the nucleotide binding sites and the transport binding sites exists (Wang et al.,

2000). Due to these findings, interaction between MDR1 substrates does not always

follow simple kinetics. The complexity of the molecular mechanisms of MDR1

inhibition contributes to the challenge of predicting potential for MDR1-mediated drug-

drug interactions, qualitatively or quantitatively.

The pattern of MDR1 inhibition can be classified into at least three types of mechanism:

(1) competitive, (2) non-competitive and (3) co-operative interaction (Litman et al,

1997). In the case of competitive inhibition, two substrates act on the same binding site

of MDR1 and only one substrate is able to bind at a time. For example the interaction

between verapamil and cyclosporine is of competitive type (Litman et al, 1997). Km for

verapamil’s ability to stimulate the ATPase activity (ATP hydrolysis) increases with the

increasing concentrations of cyclosporine, suggesting weaker affinity. Cyclosporine acts

as a competitive inhibitor of verapamil transport, but there is evidence that cyclosporine

can interact with both binding sites of MDR1 (Ayesh et al., 1996). Non-competitive

inhibition implies that the two substrates are able to bind simultaneously to MDR1 at

16

distinct binding sites. The simplest example is the interaction between verapamil and

sodium orthovanadate (Na3VO4). Sodium orthovanadate interacts with the ATP binding

domain of MDR1 instead of the substrate binding sites, inhibiting the ATPase activity

concentration dependently (Urbatch et al, 1995). The Km of verapamil does not change

with the sodium orthovanadate concentrations, even though transport is inhibited

(Litman et al, 1997). When the substrates of MDR1 bind in distinct sites in a non-

competitive manner and allosteric effects are involved in the interaction, the inhibition

mechanism can be classified as co-operative interaction.

4.2 In vitro methods for studying MDR1 inhibition

In vitro assays for studying inhibition ABC transporter inhibition consist of membrane

based (ATPase and vesicular transport) and cell based (uptake and transport) assays.

Advantages of membrane based assays are that the effect of a drug compound on a

specific transporter can be better examined, while in cell based assays the expression of

multiple transporters, even in engineered cell lines, has to be considered (Xia et al.,

2007). However the transporter under investigation can be blocked by a selective

inhibitor, which reveals the effect of the specific transporter on the transport. The

expression level of the transporter can vary depending on culture conditions and cell

passages. This has to be taken into account in membrane based assay as well. Another

advantage of membrane based assays is that when prepared in large amount, membrane

vesicles can be stored in the freezer, as cells need to be maintained under culture

condition before use. Membrane based assays are quite easy to conduct, so they are

generally less labor and time consuming. But because of the intact cell culture, cell

based assays can provide more definite information about drug and transporter

interactions. Both membrane and cell based assays can be adapted to high throughput

mode. Vesicular transport assay and cell based assays can be used to determine kinetic

parameters for substrates and inhibitors and are considered functional assays.

17

4.2.1 ATPase assay

ABC transporters require ATP hydrolysis as an energy source for the transport of

substrates out of the cell. ATP hydrolysis yields inorganic phosphate (Pi), which can be

detected by colorimetric reaction (Sarkadi 1992) (Figure 4). The amount of Pi liberated

is proportional to the activity of that transporter. ATPase assay is performed by using

membrane vesicles purified from Spodoptera frugiperda (Sf9) insect or mammalian

cells, which express high levels of the specific human transporter. A proportion of the

membrane vesicles are turned inside-out, so that the transporter is located on the outer

surface of the membrane. In the presence of ATP, the efflux transporter pumps the

substrate into the membrane vesicle and Pi is generated. ABC transporters show a

baseline ATPase activity that varies for different transporters and membrane

preparations. Substrates of the transporter stimulate the baseline ATPase activity and

inhibitors or slowly transported substrates inhibit the baseline ATPase activity.

Inhibitors also decrease the ATPase acitivity measured in the presence of a stimulating

substrate (inhibition mode). Sodium orthovanadate is a specific inhibitor of the ABC

transporters due to the interaction with the ATP binding domain of transporters.

Because there is also some endogenous ATP coming from the membrane, the ATPase

activity of the transporter is calculated as the difference between the amount of Pi

released in the presence and absence of sodium orthovanadate .

ATPase assay can be used as a screening tool to identify substrates for ABC

transporters. However, it is not a functional assay and it cannot be used to differentiate

substrates and inhibitors (FDA draft guidance, 2006). Other limitations of the ATPase

assay are high intra- and interassay variability and possibility to yield false negatives.

Substrate has to be tested in wide enough range of concentrations, because the

stimulation or inhibition can occur at either low or high concentrations. In order to do

this, the test concentrations cannot be limited by solubility.

18

4.2.2 Vesicular transport assay

Also vesicular transport assay is performed by using purified membrane vesicles. In

vesicular transport assay, the amount of a substrate transported into the membrane

vesicles is studied (Figure 5). After incubation with ATP, membrane suspension

including the substrate and inhibitor is sucked through a filter that retains the membrane

vesicles. By breaking the vesicles, the substrates transported into the vesicle can be

collected and measured. An interaction between substrate and inhibitor is detected as a

change in the initial rate of substrate transport. Compounds may also move across the

membrane by passive diffusion. Thus, the MDR1-mediated movement is calculated as

the difference in the uptake of substrate in the presence or absence of ATP.

Vesicular transport assay is a functional assay and can be used to distinguish substrates

and inhibitors (Szeremy et al., 2011). It is also an effective model to determine kinetic

parameters. However, for drug compounds with high passive permeability, the assay

can yield false negatives. Active transport may remain unnoticed, since passive

diffusion and active transport both may transfer drug into the inside-out vesicles. But

Figure 4. ATPase assay. ATP hydrolysis yields inorganic phosphate (Pi), which can be

detected by colorimetric reaction (SOLVO Biotechnology).

19

because the significance of active efflux is likely to be smaller for drugs that have high

passive permeability, vesicular transport assay is considered valuable in studying

MDR1 inhibition.

4.2.3 Uptake assay

In this assay the amount of a compound, commonly the acetoxymethyl ester or calcein

(calcein-AM), accumulated within the cell is measured. Calcein-AM is a very lipid

soluble, able to rapidly permeate across a cell membrane. From the lipid bilayer,

calcein-AM can be effluxed back to the medium by MDR1. Once inside the cell,

calcein-AM is irreversibly hydrolyzed to hydrophilic, intensively fluorescent calcein.

Inhibition of MDR1 causes an increase of calcein-AM and calcein levels inside the cell

(Figure 6).

Figure 5. Vesicular transport assay. The amount of a substrate transported into the

inside-out membrane vesicles is studied (SOLVO Biotechnology).

20

4.2.4 Utility of in vitro assays in studying MDR1-mediated interactions

Szerémy et al. (2011) compared three assays (uptake, ATPase and vesicular transport

assay) to study MDR1-mediated interactions using a common probe substrate calcein-

AM. The vesicular transport assay proved to be most sensitive to detect interactions

with MDR1, even though calcein-AM is a highly permeable probe. The uptake assay

showed the least sensibility, as for low permeability inhibitors no interaction was

observed. This is likely due to inhibitors with low permeability not able to well

permeate to binding site of MDR1 at the cytoplasmic leaflet. In the case of ATPase

assay, Szeremy et al. suggested that more interactions would be detected, if both

activation and inhibition modes are used instead activation mode alone. In the inhibition

mode of the ATPase assay, inhibitors of the transporter inhibit the ATPase activity

measured in the presence of s stimulating substrate. Also importantly, depending on the

probe substrate, a drug may potentiate or inhibit MDR1-mediated transport due to

allosteric interactions (Taub et al., 2005). In the study of Szeremy et al., Sf9-MDR1

membrane vesicles were used for the ATPase assay and cells of human origin

overexpressing MDR1 were used for the vesicular transport assay and different

preparation methods were used.

Figure 6. Uptake assay. Inhibition of MDR1 causes calcein-AM and calcein

accumulation within the cell (modified from SOLVO Biotechnology).

21

Polli et al. (2001) compared three assays (MDCKII-MDR1 transport, uptake and

ATPase) in identifying MDR1 substrates in drug discovery process. The transport assay

showed tendency to fail with high permeability substrates, as the uptake (inhibition of

calcein AM efflux) and ATPase assay tended to fail with low permeability substrates.

Thus, compounds that cannot permeate well into the cell membrane, or the reconstituted

lipid bilayer of a membrane vesicle in a concentration critical for the ATPase activation,

may have a limited effect. Therefore the transport assay was chosen as a primary screen

for MDR1 substrates. However, in the ATPase study membrane vesicles purified from

insect cells (Sf9-MDR1) were used. Possibly the application of membrane vesicles

purified from mammalian cells might improve the assay sensitivity. Keogh and Kunta

(2006) validated a method using digoxin as a probe in a MDCKII-MDR1 transport

assay. They suggested that the method is suitable for routine use to assess the in vitro

inhibitory potency (IC50) of new drug candidates on MDR1-mediated digoxin transport.

Comparison of IC50 values against clinical interaction profiles for the probe inhibitors

indicated the in vitro assay would be predictive of MDR1-mediated clinical digoxin-

drug interactions mediated.

22

Assay type Tissues Parameters Applicability Limitations

Cell based

Transport Caco-2

MDCKII-

MDR1

LLP-PK1-

MDR1

RB-A/A-B

RMDR1/parental

Km, Vmax

IC50, Ki

Evaluation of MDR1-

transport

and inhibition.

Directly measure efflux

across cell barrier.

Localization of

transporters.

Tends to fail to identify

high permeability

substrates.

Uptake Tumor cells

(e.g.

vinblastine

resistant Caco-

2, MDCKII-

MDR1)

Accumulation of

substrate in the presence

and absence of MDR1

activity.

Inhibition of efflux of

fluorescent probe (e.g.

calcein-AM, rhodamine-

123).

Primarily used for

inhibition assay.

Tends to fail to identify

low permeability

substrates and inhibitors.

Accumulation assay

cannot be used to

differentiate substrate

and inhibitors.

Membrane

based

Vesicular

transport

Membrane

vesicles (e.g.

Sf9-MDR1,

MDCKII-

MDR1)

Km, Vmax

IC50, Ki

Evaluation of MDR1-

transport and inhibition.

Effective model for

kinetic studies.

Tends to fail to identify

high permeability

substrates.

ATPase Membrane

vesicles (e.g.

Sf9-MDR1,

MDCKII-

MDR1)

ATPase stimulation Interaction with MDR1-

transporter

Activation mode

Inhibition mode

Not a functional assay.

Cannot be used to

differentiate substrates

and inhibitors.

High intra- and

interassay variability

False negatives.

4.3 In vitro inhibition parameters

Ki and IC50 are commonly used to report the inhibitory capacity of drug compounds and

to compare their relative inhibitory potency. The inhibition constant, Ki, designates the

equilibrium constant of the dissociation of the transporter-inhibitor complex. IC50

determines the concentration of inhibitor needed to cause 50 % reduction in transport

rate of another compound. In other words, smaller values for Ki indicate tighter binding

and lower IC50 values suggest stronger inhibition.

In general, IC50 is more commonly used to assess interactions. IC50 is determined at one

concentration of a substrate over a scale of inhibitor concentrations. In order to calculate

Ki, the rates of transport have to be determined by varying independently the

Table 2. Utility of in vitro assays in studying MDR1-mediated interactions (adapted

from FDA draft guideline, 2006)

23

concentrations of substrate and the concentration of inhibitor (Burlingham and

Widlanski 2003). This is more labor- and time-consuming. IC50 value is dependent on

the substrate and its concentration, whereas Ki is constant, depending only on the

specific transporter and inhibitor. Because Ki does not depend on the substrate, it is

more readily compared between different assays (experimental conditions) and

laboratories to characterize inhibitors.

If the mechanism of inhibition and the concentration of the substrate is known, an IC50

value can be theoretically converted into Ki value using the equation of Cheng and

Prusoff (1973) (Equation 2). According to this relationship the inhibitory potencies are

related as a function of the concentration (S) and the Km value of the substrate. In the

case of competitive inhibition, IC50 value approaches Ki when the assays are performed

at substrate concentrations well below the Km value. Thus the IC50 value is always

higher than Ki.

Cer et al. (2009) developed a web-server tool for estimating Ki from experimentally

determined IC50 values for inhibitors of enzyme activity and ligand binding. For enzyme

kinetics, the tool uses classic Michael-Menten kinetics, which can be applied for

transporter interactions as well. Required user-defined input values include the

concentration and Km of the substrate and IC50 value.

Mathematically most accurate way to determine IC50 value is by nonlinear regression.

As an alternative way, Burlingham and Widlanski (2003) introduced a new analysis of

the Dixon plot (Figure 8). Dixon plot is graphical method for determining Ki by

assaying only two substrate concentrations against a range of inhibitors in the case of

competitive inhibition (Dixon 1953) (Figure 7). Burlingham and Widlanski suggested

that this linear method could be utilized to determine IC50 values as well, even if the

mode of inhibition is unknown.

Equation 2

24

IC50 values can be used to assess the relative inhibitory potencies of candidate

compounds and classify them as weak or potent inhibitors. However, their utility is

limited to predict the extent of drug-drug interactions. For quantitative predictions, in

vitro kinetic parameters, Km and Ki are needed.

4.4 In vivo methods for studying MDR1-interactions

Mdr1 knockout mice have shown the significance of MDR1 transporter in

pharmacokinetics of certain drugs. These results are utilized to develop in vitro - in vivo

correlations to estimate the importance of MDR1 in the pharmacokinetics of substrate

Figure 7. The Dixon plot for a competitive inhibitor. Ki can be determined from the

intersection of data obtained at two substrate concentrations (Burlingham and Widlanski

2003).

.

Figure 8. New analysis of the Dixon plot. The Dixon plot can be illustrated as a series of

IC50 determinations (Burlingham and Widlanski 2003). IC50 approaches Ki, when the

assay is performed at low concentration of substrate.

25

drugs. Using this information, the effect of an MDR1 inhibitor on a certain substrate

could be estimated. Besides the substrate’s affinity to MDR1, the inhibitor’s inhibitory

capacity contributes to the interaction. Inhibitory capacities are estimated in in vitro

experiments, as in vivo parameters with varying concentrations of inhibitor would be

extremely laborious and expensive to produce. However, the information from in situ

and in vivo mice studies can be well exploited in interaction studies to predict the drugs

susceptibility to an MDR1-mediated interaction. To perform an actual interaction study

with predictive value in mice, concentrations of substrate and inhibitor would have to be

in vivo relevant in human and then extrapolated to mice.

4.5 Prediction of intestinal MDR1-mediated drug-drug interactions

The latest FDA draft guidance (2006) for drug interaction studies presents the criteria

for determining whether an investigational drug is a substrate (Figure 9) and/or an

inhibitor (Figure 10) of MDR1 and whether an in vivo interaction study is needed. To

evaluate if a drug is a substrate for MDR1, a bi-directional transport assay is

recommended. If the net flux ratio is over 2, the result is considered positive and further

studies with a known MDR1 inhibitor are should be performed. If the addition of a

MDR1 inhibitor reduces the net flux ratio significantly (more than 50 % reduction), the

drug is considered a likely MDR1 substrate. When an investigational drug is a MDR1

substrate in vitro, available in vivo data should carefully evaluated to determine whether

an in vivo drug interaction is needed. For example, the bioavailability of drugs that are

classified as class I drugs according to the Biopharmaceutics Classificiation System

(BCS), being highly soluble and highly permeable, may not be significantly affected by

co-administration of a MDR1 inhibitor (Zhang et al, 2008).

26

To determine whether an investigational drug is an inhibitor of MDR1, a bi-directional

transport assay using a probe substrate is recommended. The criteria states that the

concentration of the probe should be below its apparent Km value. First, a high

concentration (e.g. 100 µM or as high as the drug’s solubility allows) of the

investigational drug can be used to see if the efflux of the probe is affected. If the efflux

of the probe is inhibited by the investigational drug, the inhibition should be further

studied over a range of concentrations to determine the inhibitory potency, IC50 or Ki.

The next step is to calculate the ratio between the concentration of the drug (I) and the

inhibitor potency (IC50 or Ki). If the ratio is over 0.1, the investigational drug is

considered a MDR1 inhibitor and an in vivo drug interaction study with a MDR1

substrate (generally digoxin) is recommended.

Figure 9. Decision tree to determine whether a drug is a substrate for MDR1 and

requires an in vivo drug interaction study (FDA draft guidance 2006; Giacomini 2010).

27

The FDA and EMEA draft guidances highly emphasizes the importance of a validated

or sufficient cell system. To evaluate if an investigation drug is a MDR1 substrate,

known probe substrate(s) should be used as a positive control(s). An acceptable cell

system should produce net flux ratios of the probe(s) similar to what has been reported

in the literature (a minimum net flux ratio of 2 is recommended). The same criteria

apply to inhibition studies, and additionally two or three known potent MDR1 inhibitors

should be included as positive controls.

The difficulty in predicting intestinal drug-drug interactions is the estimation of the drug

concentration in the intestine. In the draft guidance (2006) (I) represented the mean

steady-state Cmax value for total drug (unbound and bound) following administration of

the highest proposed clinical dose. This criteria further evolved leading to the proposal

of alternative criteria: drugs that having a (I)1/IC50 ratio over 0.1 or (I)2/IC50 ratio over

10 should be evaluated in an in vivo drug interaction study. (I)1 stands for the total

plasma Cmax (unbound and bound) and (I)2 is obtained by dividing the dose by 250 ml,

which is the typical amount of water taken with administration of a drug The

concentration of drug in the intestine is taken into account also in the EMA draft

guidance (2010) for permeability studies for investigational drugs. EMA states that

permeability should be studied for at least four different physiologically relevant

Figure 10. Decision tree to determine whether a drug is an inhibitor of MDR1and when

an in vivo drug interaction study is recommended (Giacomini 2010)FDA draft guidance

2006; (Zhang et al. 2008).

28

concentrations, which could be 0.1–50-fold the dose divided by 250 ml for intestinal

transport. In comparison, when investigating systemic MDR1 transport the

corresponding concentration range recommended is 0.1–50-fold the unbound Cmax.

Importantly, because the methodology used for determination of the IC50 value greatly

affects the ratio, there is a great need for standardization (Zhang et al., 2008).

5 CONCLUSIONS

It is of great importance that predictive information of potential MDR1-mediated

absorption limitations and related drug-drug interactions is produced in early drug

development. However, there’s lack of suitable in vitro and in vivo data (e.g.

comparable parameters) for in vitro-in vivo correlations, predictive of the extent of

MDR1 on drug absorption. In studying MDR1-mediated interactions, many in vitro

assays are frequently applied, but there is a need for validated international in vitro

protocols. For example, the IC50 values for inhibitors have marked differences between

studies and laboratories.

If a drug-drug interaction can be accurately explained in vitro, the in vivo influence in

humans can be better predicted. In silico pharmacokinetic modeling has been widely

utilized in predicting the influence of MDR1 on drug absorption. In the future,

physiologically based pharmacokinetic modeling of drug-drug interactions with

implemented kinetic parameters (Km, IC50, Ki) would greatly increase the value of both

in vitro studies and in silico models. However, understanding of the mechanisms and

assumptions involved is vital for interpreting drug interaction data and evaluating the

risk of clinically significant interactions.

29

6 REFERENCES

Adachi, Y., Suzuki, H. & Sugiyama, Y. 2001, "Comparative studies on in vitro methods

for evaluating in vivo function of MDR1 P-glycoprotein", Pharmaceutical research,

vol. 18, no. 12, pp. 1660-1668.

Adachi, Y., Suzuki, H. & Sugiyama, Y. 2003, "Quantitative evaluation of the function

of small intestinal P-glycoprotein: Comparative studies between in situ and in vitro",

Pharmaceutical research, vol. 20, no. 8, pp. 1163-1169.

Agoram, B., Woltosz, W.S. & Bolger, M.B. 2001, "Predicting the impact of

physiological and biochemical processes on oral drug bioavailability", Advanced

Drug Delivery Reviews, vol. 50 (Suppl 1), pp. S41-S67.

Ayesh, S., Shao, Y-M. & Stein, W.D. 1996, "Co-operative, competitive and non-

competitive interactions between modulators of P-glycoprotein", Biochimica Et

Biophysica Acta-Molecular Basis Of Disease , vol. 1316, no. 1, pp. 8-18.

Badhan, R., Penny, J., Galetin, A. & Houston, J.B. 2009, "Methodology for

development of a physiological model incorporating CYP3A and P-glycoprotein for

the prediction of intestinal drug absorption", Journal of pharmaceutical sciences,

vol. 98, no. 6, pp. 2180-2197.

Berggren, S., Gall, C., Wollnitz, N., Ekelund, M., Karlbom, U., Hoogstraate, J., Schrenk,

D. & Lennernäs H. 2007, "Gene and protein expression of P-glycoprotein, MRP1,

MRP2, and CYP3A4 in the small and large human intestine", Molecular

Pharmaceutics, vol. 4, no. 2, pp. 252-257.

Burlingham, B. & Widlanski, T. 2003, "An intuitive look at the relationship of Ki and

IC50: A more general use for the dixon plot", Journal of chemical education, vol.

80, no. 2, pp. 214-218.

Canaparo, R., Finnström, N., Serpe, L., Nordmark, A., Muntoni, E., Eandi, M., Rane A.

& Paolo Zara, G. 2007, "Expression of CYP3A isoforms and P-glycoprotein in

human stomach, jejunum and ileum", Clinical & Experimental Pharmacology &

Physiology, vol. 34, no. 11, pp. 1138-44.

Cer, R.Z., Mudunuri, U., Stephens, R. & Lebeda F.J. 2009, "IC50-to-Ki: a web-based

tool for converting IC50 to Ki values for inhibitors of enzyme activity and ligand

binding", Nucleic acids research., vol. 37 July 1, pp. W441-W445.

Cheng, Y.C. & Prusoff, W.H. 1973, "Relationship between the inhibition constant (K1)

and the concentration of inhibitor which causes 50 per cent inhibition (I50) of an

enzymatic reaction", Biochemical pharmacology, vol. 22, no. 23, pp. 3099-3108.

30

Chowbay, B., Li, H., David, M., Cheung, Y.B. & Lee, E.J.D. 2005, "Meta-analysis of

the influence of MDR1 C3435T polymorphism on digoxin pharmacokinetics and

MDR1 gene expression", British journal of clinical pharmacology, vol. 60, no. 2,

pp. 159-171.

Collett, A., Tanianis-Hughes, J., Hallifax, D. & Warhurst G. 2004, "Predicting P-

glycoprotein effects on oral absorption: Correlation of transport in Caco-2 with

drug pharmacokinetics in wild-type and mdr1a(-/-) mice in vivo", Pharmaceutical

research, vol. 21, no. 5, pp. 819-826.

Cong, D., Doherty, M. & Pang K.S. 2001, "A new, physiologically-based, segregated-

flow model to explain route-dependent intestinal metabolism", Faseb Journal , vol.

15, no. 4, pp. A548-A548.

Cordon-Cardo, C., O'Brien, J., Boccia, J., Casals, D., Bertino, J.R. & Melamed, M.R.

1990, "Expression of the multidrug resistance gene product (P-Glycoprotein) in

human normal and tumor tissues", Journal of Histochemistry and Cytochemistry,

vol. 38, no. 9, pp. 1277-1287.

Cummins , C.L., Jacobsen, W. & Benet, L.Z. 2002, "Unmasking the Dynamic Interplay

between Intestinal P-glycoprotein and CYP3A4", Journal of Pharmacology and

Experimental Therapeutics, vol. 300, no. 3, pp. 1036-1045.

Darwich, A.S., Neuhoff, S., Jamei, M. & Rostami-Hodjegan, A. 2010, "Interplay of

Metabolism and Transport in Determining Oral Drug Absorption and Gut Wall

Metabolism: A Simulation Assessment Using the "Advanced Dissolution,

Absorption, Metabolism (ADAM)" Model", Current Drug Metabolism, vol. 11, no.

9, pp. 716-729.

del Amo, E.M., Heikkinen A.T. & Mönkkönen J. 2009, "In vitro-in vivo correlation in

P-glycoprotein mediated transport in intestinal absorption", European journal of

pharmaceutical sciences : official journal of the European Federation for

Pharmaceutical Sciences, vol. 36, no. 2-3, pp. 200-211.

Dey, S. & Ramachandra, M., Pastan , I., Gottesman, M.M. & Suresh V.A. 1997,

"Evidence for two nonidentical drug-interaction sites in the human P-glycoprotein",

Proceedings of the National Academy of Sciences of the United States of America,

vol. 94, no. 20, pp. 10594.

Dixon, M. 1953, "The determination of enzyme inhibitor constants", Biochemical

Journal, vol. 55, no. 1, pp. 170-1.

European Medicines Agency (EMA): Draft guideline on the Investigation of Drug

Interactions, 2010.

Food and Drug Administration (FDA): Draft guidance for Industry. Drug Interaction

Studies - Study Design, Data Analysis, and Implications for Dosing and Labeling,

2006.

31

Giacomini, K.M., Huang, S.-M., Tweedie, D.J., Benet, L.Z., Brouwer, K.L.R., Chu, X.,

Dahlin, A., Evers, R., Fischer, V., Hillgren, K.M., Hoffmaster, K.A., Ishikawa, T.,

Keppler, D., Kim, R.B., Lee, C.A., Niemi, M., Polli, J.W., Sugiyama, Y., Swaan,

P.W., Ware, J.A., Wright, S.H., Yee, S.W., Zamek-Gliszczynski M.J. & Zhang L.

2010, "Membrane transporters in drug development", Nature reviews.Drug

discovery, vol. 9, no. 3, pp. 215-236.

Gros, P., Raymond, M., Bell, J. & Housman, D. 1988, "Cloning and characterization of

a second member of the mouse mdr gene family", Molecular and cellular biology,

vol. 8, no. 7, pp. 2770-2778.

Hakkarainen, J.J., Jalkanen, A.J., Kääriainen, T.M., Keski-Rahkonen, P., Venalainen, T.,

Hokkanen, J., Monkkonen, J., Suhonen, M. & Forsberg, M.M. 2010, "Comparison

of in vitro cell models in predicting in vivo brain entry of drugs", International

journal of pharmaceutics, vol. 402, no. 1, pp. 27-36.

Higgins, C.F. & Gottesman, M.M. 1992, "Is the multidrug transporter a flippase?",

Trends in biochemical sciences, vol. 17, no. 1, pp. 18-21.

Hoffmeyer, S., Burk, O., von Richter, O., Arnold, H.P., Brockmöller, J., Johne, A.,

Cascorbi, I., Gerloff, T. & Roots, I., Eichelbaum, M. & Brinkmann, U. 2000,

"Functional polymorphisms of the human multidrug-resistance gene: Multiple

sequence variations and correlation of one allele with P-glycoprotein expression

and activity in vivo", Proceedings of the National Academy of Sciences of the

United States of America, vol. 97, no. 7, pp. 3473.

Hubatsch, I., Ragnarsson E.G.E. & Artusson P., 2007, "Determination of drug

permeability and prediction of drug absorption in Caco-2 monolayers", Nature

Protocols, vol. 2, no. 9, pp. 2111-2119.

Idriss, H.T., Hannun, Y.A., Boulpaep, E. & Basavappa S. 2000, "Regulation of volume-

activated chloride channels by P-glycoprotein: phosphorylation has the final say!",

Journal of Physiology-London, vol. 524, no. 3, pp. 629-636.

Jamei, M., Turner, D., Yang, J., Neuhoff, S., Polak, S., Rostami-Hodjegan, A. & Tucker,

G. 2009, "Population-Based Mechanistic Prediction of Oral Drug Absorption",

Aaps Journal, vol. 11, no. 2, pp. 225-237.

Juliano, R.L. & Ling, V. 1976, "A surface glycoprotein modulating drug permeability in

Chinese hamster ovary cell mutants", Biochimica et biophysica acta, vol. 445, no. 1,

pp. 152-162.

Keogh, J.P. & Kunta, J.R. 2006, "Development, validation and utility of an in vitro

technique for assessment of potential clinical drug-drug interactions involving P-

glycoprotein", European Journal of Pharmaceutical Sciences (Netherlands), vol.27,

(5), pp.543-554, 2006, , pp. 543-554.

32

Lankas, G. R., Cartwright, M.E. & Umbenhauer, D. 1997, "P-glycoprotein deficiency in

a subpopulation of CF-1 mice enhances avermectin-induced neurotoxicity",

Toxicology and applied pharmacology, vol. 143, no. 2, pp. 357-365.

Leschziner, G.D., Andrew, T., Pirmohamed, M. & Johnson, M.R. 2007, "ABCB1

genotype and PGP expression, function and therapeutic drug response: a critical

review and recommendations for future research", Pharmacogenomics Journal, vol.

7, no. 3, pp. 154-179.

Litman, T., Zeuthen, T., Skovsgaard, T. & Stein, W.D. 1997, "Competitive, non-

competitive and cooperative interactions between substrates of P-glycoprotein as

measured by its ATPase activity", Biochimica Et Biophysica Acta-Molecular Basis

Of Disease, vol. 1361, no. 2, pp. 169-176.

Lown, K.S., Mayo, R.R., Leichtman, A.B., Hsiao, H.-L., Turgeon, K., Schmiedlin-Ren,

P., Brown, M.B., Guo, W., Rossi, S.J., Benet, L.Z. & Watkins, P.B. 1997, "Role of

intestinal P-glycoprotein (mdr1) in interpatient variation in the oral bioavailability

of cyclosporine", Clinical Pharmacology & Therapeutics, vol. 62, no. 3, pp. 248-60.

Polli, J.W., Wring, S.A., Humphreys, J.E., Huang, L. Morgan, J.B., Webster, L.O. &

Serabjit-Singh, C.S. 2001, "Rational use of in vitro P-glycoprotein assays in drug

discovery", Journal Of Pharmacology And Experimental Therapeutics, vol. 299, no.

2, pp. 620-628.

Raviv, Y., Pollard, H.B., Bruggemann, E.P., Pastany, I. & Gottesman, M.M. 1990,

"Photosensitized Labeling of a Functional Multidrug Transporter in Living Drug-

resistant Tumor-Cells", Journal of Biological Chemistry, vol. 265, no. 7, pp. 3975-

3980.

Sarkadi, B. 1992, "Expression of the human multidrug resistance CDNA in insect cells

generates a high-activity drug-stimulated membrane ATPase", Journal of

Biological Chemistry, vol. 267, no. 7, pp. 4854-4858.

Schinkel, A.H., Smit, J.J., van Tellingen, O., Beijnen, J.H., Wagenaar, E., van Deemter,

L., Mol, C.A., van der Valk, M.A., Robanus-Maandag, E.C. & de Riele, H.P. 1994,

"Disruption of the mouse mdr1a P-glycoprotein gene leads to a deficiency in the

blood-brain barrier and to increased sensitivity to drugs", Cell, vol. 77, pp. 491-502.

Schinkel, A.H., Mayer, U., Wagenaar, E., Mol., C.A., van Deemter, L., Smit, J.J., van

der Walk, M.A., Voordouw, A.C., Spits H., van Tellingen, O., Zijlmans, J.M.,

Fibbe, W.E. & Borst, P. 1997, "Normal variability altered pharmacokinetics in mice

lacking mdr1-type (drug-transporting) P-glycoproteins", Proceedings of the

National Academy of Sciences, vol. 94, pp. 4028-4033.

Schinkel, A.H. & Jonker, J.W. 2003, "Mammalian drug efflux transporters of the ATP

binding cassette (ABC) family: an overview", Advanced Drug Delivery Reviews,

vol. 55, no. 1, pp. 3.

33

Shapiro, A.B. & Ling, V. 1997, "Extraction of Hoechst 33342 from the cytoplasmic

leaflet of the plasma membrane by P-glycoprotein", European Journal of

Biochemistry, vol. 250, no. 1, pp. 122-129.

Szeremy, P., Pal, A., Mehn, D., Toth, B., Fulop, F, Krajcsi, P. & Heredi-Szabo, K. 2011,

"Comparison of 3 Assay Systems Using a Common Probe Substrate, Calcein AM,

for Studying P-gp Using a Selected Set of Compounds", Journal of Biomolecular

Screening, vol. 16, no. 1, pp. 112-119.

Tachibana, T., Kato, M., Takano, J. & Sugiyama, Y. 2010, "Predicting drug-drug

interactions involving the inhibition of intestinal CYP3A4 and P-glycoprotein",

Current Drug Metabolism, vol. 11, no. 9, pp. 762-777.

Taub, M.E., Podila, L., Ely, D. & Almeida, I. 2005, "Functional assessment of multiple

P-glycoprotein (P-gp) probe substrates: influence of cell line and modulator

concentration on P-gp activity", Drug Metab Dispos, vol. 33, no. 11, pp. 1679.

Troutman, M.D. & Thakker D.R. 2003a, "Efflux ratio cannot assess P-glycoprotein-

mediated attenuation of absorptive transport: Asymmetric effect of P-glycoprotein

on absorptive and secretory transport across Caco-2 cell monolayers",

Pharmaceutical research, vol. 20, no. 8, pp. 1200-1209.

Troutman, M.D. & Thakker D.R. 2003b, "Novel Experimental Parameters to Quantify

the Modulation of Absorptive and Secretory Transport of Compounds by P-

Glycoprotein in Cell Culture Models of Intestinal Epithelium", Pharmaceutical

Research, 2003, Vol.20(8), p.1210-1224, vol. 20, no. 8, pp. 1210-1224.

Tubic, M., Wagner, D., Spahn-Langguth, H., Bolger, M.B. & Langguth, P. 2006, "In

silico modeling of non-linear drug absorption for the P-gp substrate talinolol and of

consequences for the resulting pharmacodynamic effect", Pharmaceutical research,

vol. 23, no. 8, pp. 1712-1720.

Urbatsch, I.L., Sankaran, B., Weber, J. & Senior A.E. 1995, "P-glycoprotein is Stably

Inhibited by Vanadate-Induced Trapping of Nucleotide at a Single Catalytic Site" ,

Journal of Biological Chemistry, vol. 270, no. 33, pp. 19383-19390.

Wang, E.J., Casciano, C.N., Clement, R.P. & Johnson, W.W. 2000, "Two transport

binding sites of P-glycoprotein are unequal yet contingent: initial rate kinetic

analysis by ATP hydrolysis demonstrates intersite dependence", Biochim Biophys

Acta, vol. 1481, no. 1, pp. 63.

Wetterich, U., Spahn-Langguth, H., Mutschler, E., Terhaag, B., Rösch, W. & Langguth,

P. 1996, "Evidence for intestinal secretion as an additional clearance pathway of

talinolol enantiomers: concentration- and dose-dependent absorption in vitro and in

vivo", Pharmaceutical research, vol. 13, no. 4, pp. 514-22.

34

Xia, C.Q., Milton, M.N. & Gan, L.-S., 2007, "Evaluation of Drug-Transporter

Interactions Using In Vitro and In Vivo Models", Current Drug Metabolism, vol. 8,

no. 4, pp. 341-363.

Yu, L.X., Crison, J.R. & Amidon, G.L. 1996, "Compartmental transit and dispersion

model analysis of small intestinal transit flow in humans", International journal of

pharmaceutics, vol. 140, no. 1, pp. 111-118.

Zhang, Y., Bachmeier, C. & Miller, D.W. 2003, "In vitro and in vivo models for

assessing drug efflux transporter activity", Advanced Drug Delivery Reviews, vol.

55, no. 1, pp. 31.

Zhang, L., Zhang, Y., Strong, J.M., Reynolds, K.S. & Huang, S. 2008, "A regulatory

viewpoint on transporter-based drug interactions", Xenobiotica, vol. 38, no. 7, pp.

709-724.

EXPERIMENTAL WORK: INTERACTIONS OF ALISKIREN WITH MDR1 INHIBITORS

IN VITRO AND PHARMACOKINETIC MODELING OF THE INFLUENCE OF MDR1 ON

INTESTINAL ABSORPTION

Tiina Koskenkorva

University of Helsinki

Faculty of Pharmacy

Division of Biopharmaceutics and Pharmacokinetics

February 2012

TABLE OF CONTENTS

1 INTRODUCTION .................................................................................................... 1

2 AIMS OF THE STUDY ........................................................................................... 4

3 MATERIALS AND METHODS .............................................................................. 4

3.1 Drug compounds ................................................................................................ 4 3.2 MDCKII-MDR1 cell culture .............................................................................. 5 3.3 Sf9-MDR1 and Sf9-β-galactosidase cells .......................................................... 5 3.4 Preparation of membrane vesicles ..................................................................... 6 3.5 Determination of the protein concentration of membrane vesicles ................... 6

3.6 ATPase assay ..................................................................................................... 6 3.7 Vesicular transport assay .................................................................................... 7

3.7.1 Determination of test circumstances ........................................................... 7

3.7.2 Determination of Km and Vmax for aliskiren ............................................... 8 3.7.3 Determination of IC50 and Ki for inhibitors ................................................ 8

3.8 Measuring of aliskiren ........................................................................................ 9 3.9 Sigma plot .......................................................................................................... 9

3.10 Pharmacokinetic modeling ............................................................................... 10

4 RESULTS ............................................................................................................... 11

4.1 ATPase assay ................................................................................................... 11 4.2 Vesicular transport assay .................................................................................. 13

4.2.1 Feasibility of MDCKII-MDR1 membrane vesicles .................................. 13

4.2.2 Determination of test circumstances ......................................................... 14 4.2.3 Determination of Km and Vmax for aliskiren ............................................. 15 4.2.4 Determination of IC50 and Ki for inhibitors .............................................. 16

4.2.5 Pharmacokinetic modeling ....................................................................... 19

5 DISCUSSION ......................................................................................................... 21

5.1 Correlations of in vitro parameters to in vivo literature data ........................... 21

5.1.1 Aliskiren .................................................................................................... 21 5.1.2 Inhibitors ................................................................................................... 22 5.1.3 Limitations of in vitro assays applied ....................................................... 25

5.2 Pharmacokinetic modeling ............................................................................... 26 5.2.1 Discussion ................................................................................................. 26

5.2.2 Considerations .......................................................................................... 28 5.3 Comparison of aliskiren and digoxin as MDR1 probes ................................... 30

6 CONCLUSIONS .................................................................................................... 31

7 REFERENCES ....................................................................................................... 32

APPENDIX 1

ABBREVIATIONS FOR THE MODEL

GE Gastric emptying for solid drugs

Kge Gastric emptying rate constant for dissolved drug

Kt Transit rate constant (for solid and dissolved drug)

Kd Dissolution rate constant

Ka Absorption rate constant

Peff Effective permeability

Kel Elimination rate constant

t ½ Half-life

V lumen Volume of liquid in lumen

A enterocyte Surface area of enterocyte

V enterocyte Volume of enterocyte

Vd Volume of distribution

Km Substrate concentration, at which reaction rate is half of

maximum

Vmax Maximum transport rate

logD6.0 Partition coefficient at pH 6.0

PSA Polar surface area

1

1 INTRODUCTION

Drug-drug interactions are a common problem during drug treatment and a cause of

great number of hospital admissions within the EU (EMA 2010). Therefore, elucidation

of transporter- and/or metabolic enzyme-mediated drug interactions is important part of

early drug development. However, the knowledge about clinical consequences of

transporter-mediated drug-drug interactions is still limited and more investigation is

needed to improve our understanding (EMA 2010).

MDR1 is the most extensively studied efflux transporter, widely expressed in many

pharmacokinetic barriers in the body. Many inhibitors of MDR1 transporter are also

inhibitors of CYP3A4 enzyme and it has been suggested that they act synergistically in

the intestine to limit the bioavailability of orally administered drugs (Benet et al., 1996).

However, the overlapping substrate specificity is commonly a confusing factor, when

studying MDR1 inhibition. It complicates the extrapolation of in vitro data into in vivo

situation and makes it more difficult to estimate the influence of each interaction

separately. Thus, when studying MDR1 inhibition, the possible effect of CYP3A4

inhibition has to be regarded, when interpreting the results. To fully understand to role

of each, selective in vivo relevant inhibitors of each are needed. Because of the wide

tissue distribution of MDR1, inhibition of the transporter may result in interactions due

to a change in intestinal, renal, biliary or central nervous system efflux.

There is an increased need to validate in vitro assays to produce information that is

predictable against in vivo data. With the aid of in vitro techniques, substantial volumes

of data can be produced effectively. If the observed clinically significant interactions

can be accurately explained in vitro, better in silico models could be developed to

predict the in vivo outcome in humans using the in vitro data. Possibly less laborious

and costly preclinical animal data would be needed. Predictive models would be useful

tools to guide clinical interaction studies and to estimate the clinical significance of a

drug interaction in different situations and with different inhibitors. An important issue

is the use of clinically relevant probes and inhibitors with clinically relevant

concentrations in the in vitro assays. A MDR1-selective substrate that is suitable in in

2

vitro studies and in vivo trials in humans, would give a good basis for developing in

vitro–in vivo predictive models.

Aliskiren is the first orally active renin inhibitor, approved 2007 by the FDA for the

treatment of primary hypertension. The renin–angiotensin-aldosterone system plays an

important part in the physiological regulation of blood pressure. Excessive renin system

activity may lead to hypertension and associated target organ damage (Weir and Dzau

1999). Renin is the first, rate-limiting enzyme of the renin-angiotensin-aldosterone

cascade, responsible for the conversion of angiotensinogen into angiotensin I. Aliskiren

inhibits renin activity, with a great potency (IC50 = 0.06 nM (Wood et al. 2003)).

Aliskiren is known as Tekturna® in the US and as Rasilez® in other markets, available

in 150 mg and 300 mg tablets.

Pharmacokinetics of aliskiren has been shown to be very sensitive to MDR1 inhibition

in humans (Tapaninen et al. 2010a). Tapaninen et al. (2010) showed that MDR1- and

CYP3A4-inhibitor itraconazole increased the mean Cmax of aliskiren 5.8-fold and its

mean AUC0-∞ 6.5-fold in humans. However, itraconazole did not have a significant

effect on the half-life of aliskiren. Tapaninen et al. suggested that this indicates an

interaction during the first-pass phase in the small intestine. Because aliskiren

undergoes only minor CYP -metabolism (aproximately 1.4 % of dose as oxidized

metabolites (Waldmeier et al., 2007)) and has low hepatic extraction ratio (0.10 (Azizi

et al., 2006)), inhibition of CYP3A4 in the liver during the first-pass phase cannot

explain the interaction entirely.

Aliskiren has been classified as a class III compound according to the Biopharmaceutics

Classification System (BCS), having high solubility and low permeability (Table 1).

Being an MDR1 substrate, aliskiren has a poor bioavailability of 2.6 % (Table 2). The

absorbed dose of aliskiren was excreted mainly unchanged via the hepato-biliary route

(91.9 % (Waldmeier et al., 2007)). Only 0.6 % of dose was recovered in the urine (0-

168 h) (Drugs@FDA), which suggests that renal interactions are unlikely. In vitro

studies show, that aliskiren is not an inhibitor of MDR1 or CYP enzyme activity.

Oxidation is catalyzed mainly by CYP3A4/5 enzymes. Aliskiren binds moderately to

3

plasma proteins (in vitro 49-52 %,), which contributes to a lower risk of interactions.

Aliskiren displays linear pharmacokinetics based on AUC (0-96h) and Cmax in the dose

range of 75 mg to 600 mg (Vaidyanathan et al. 2006). Aliskiren has moderate affinity

for the human organic anion transporter (OATP2B1) (Km 72 µM) (Vaidyanathan et al.

2008), which the hepatic uptake is thought to be mediated by.

Physicochemical parameters for aliskiren Value Unit

Aqueous solubility (pH 7.4)

Molecular mass

Molecular mass as hemifumarate salt

logP (pH 7.4)

pKa (as a free base)

logD6.01

PSA1

>350

551.8

609.8

2.45

9.49

-0.28

146.1

mg/ml

g/mol

g/mol

1 Calculated by ACDLabs

PK parameters for aliskiren Value

Dose (mg)

Tmax (h)

Cmax (µM)

AUC (µM×h)

Apparent terminal t½ (p.o.) (h)1

Apparent terminal t½ (i.v.) (h)2

Absorption (% of dose)

Bioavailability (%)

CL (l/h)2

Vss (l)2,3

300 mg

3

0.46

2.008

48.7

23.7

≥ 3

2.6 %

9

135

1 calculated between 48 and 144 hours after administration

2 calculated after i.v. administration

3(Azizi et al., 2006)

In addition to being very sensitive to MDR1 inhibition in vivo (Tapaninen et al. 2010),

aliskiren has a high affinity for the transporter in vitro (Km 2.1 µM in ATPase assay

(Vaidyanathan et al. 2008)). Because aliskiren undergoes only minor metabolism, the

influence of MDR1-mediated interaction alone can be better assessed. Aliskiren as a

probe gives a good starting point for MDR1-mediated in vitro interaction studies.

The interactions between aliskiren and MDR1 inhibitors itraconazole, ketoconazole and

verapamil have not been studied in vitro. Tapaninen et al. (2010) suggested that the

Table 1. Physicochemical parameters for aliskiren (Drugs@FDA)

Table 2. Pharmacokinetic parameters for aliskiren (Drugs@DFA).

4

interaction between aliskiren and itraconazole in vivo was likely mostly due to

itraconazole inhibiting MDR1 transport in the intestine, hence improving aliskiren

absorption. Hydroxyitraconazole is itraconazole’s active metabolite. As an inhibitor of

CYP3A enzyme (Von Moltke et al. 1998), hydroxyitraconazole may contribute to

CYP3A-mediated interactions of itraconazole, whereas hydroxyitraconazole’s potential

to inhibit MDR1 has not been investigated in vitro. In addition to itraconazole,

ketoconazole and verapamil are well documented MDR1- and CYP3A4 inhibitors with

differing inhibition profiles. It is of great interest to study if the MDR1-mediated

interaction in vitro would be predictive of the extent of MDR1-mediated interaction in

vivo.

2 AIMS OF THE STUDY

The objective of this experimental part was to study the MDR1-mediated transport of

aliskiren and the related drug-drug interactions in vitro and in silico. Aims of the study

were to (1) obtain Km and Vmax values for aliskiren by using the vesicular transport

assay, (2) obtain IC50 values for ketoconazole, verapamil, itraconazole and

hydroxyitraconazole and to calculate Ki values for itraconazole and hydroxyitraconazole,

(3) assess the feasibility of MDCKII-MDR1 membrane vesicles in vesicular transport

assay, (4) use a compartmental absorption and transit (CAT) model to simulate the

intestinal absorption of aliskiren and related drug-drug interactions in vivo in humans by

using the in vitro results.

3 MATERIALS AND METHODS

3.1 Drug compounds

Aliskiren hemifumarate and ketoconazole were supplied by Toronto Research

Chemicals Inc. (North York, Canada) and verapamil by Sigma-Aldrich (Germany).

Itraconazole and hydroxyitraconazole were obtained from Jansen Research Foundation

5

(Titusville, New Jersey). Stock solutions were prepared in dimethyl sulfoxide (DMSO):

aliskiren 5 mM, ketoconazole 25 mM, verapamil 100 mM, itraconazole 0.8 mM and

hydoxyitraconazole 0.8 mM. In all experiments, stock solution or serial dilutions were

added to the assay mix to produce a final DMSO concentration of 2 % of the total

reaction volume (v/v).

3.2 MDCKII-MDR1 cell culture

Madin-Darby canine kidney II (MDCKII) renal epithelial cells expressing human

MDR1 were originally received from Netherland Cancer Institute. The growth medium

used was D-MEM (Gibco/BRL 61965-026), supplemented with 10% Fetal bovine

Serum and 1 % Penicillin-Streptomycin solution (5000 U/ml – 5 mg/ml, Gibco).

MDCKII-MDR1 cells were split twice a week after a confluent monolayer was formed.

Cells were first washed briefly with DPBS, incubated with 0.25 % trypsin/EDTA for 3-

5 minutes at 37 °C and then split 1:10.

MDCKII-MDR1 cell mass was collected for the preparation of membrane vesicles. At

the time of collection, cells had been split over 4 times and been grown for less than

three months. Cells were kept on ice and detached from the tissue culture flask to cold

PBS with a cell scraper. After 5 min centrifugation (+ 4 °C, 1000 g) the supernatant was

removed. Cell mass was frozen in liquid nitrogen and stored in the freezer -75 °C until

use.

3.3 Sf9-MDR1 and Sf9-β-galactosidase cells

Sf9 (Spodoptera frugiperda) insect cells expressing human MDR1 or β-galactosidase

(control) were used to prepare membrane vesicles. Sf9 cells had been infected with a

recombinant baculovirus containing the cloned MDR1 gene. Sf9 cells expressing β-gal

were produced in similar manner, but the foreign gene in the baculovirus is a gene

coding β-gal instead of MDR1.

6

3.4 Preparation of membrane vesicles

Inside-out membrane vesicles were prepared mainly as described in (Chu 2004).

Preparation of membrane vesicles was done on ice and using ice-cold buffers. Cells

were washed twice with harvest buffer containing 50 mM Tris-HCl (pH 7.0) and 300

mM mannitol and centrifuged (Centurion) + 4 °C, 800 g, 5 min. Cells were lysed and

homogenized in membrane buffer containing 50 mM Tris-HCl (pH 7.0), 50 mM

mannitol and 2 mM EGTA, using Dounce homogenizator (Pestle B), for 40 strokes.

Cell lysates were centrifuged + 4 °C, 800 g, 10 min to separate the nuclei. The

supernatant was further ultracentrifuged (Beckman Coultier, Optima LE-80K; rotor 50.2

Ti, 91E733) + 4 °C, 100 000 g, 1 h 15 min to separate the cell membranes. The pellet

containing the membranes, was resuspended in membrane buffer by pushing through a

27G needle for 20 times to form inside-out membrane vesicles. Membrane vesicles

were frozen in liquid nitrogen and stored in the freezer- 75°C until use. Same

preparation method was used for both mammalian (MDCKII-MDR1) and insect cells

(Sf9-MDR1).

3.5 Determination of the protein concentration of membrane vesicles

The protein concentration of membrane vesicles was determined by the Bio-Rad Protein

Assay (Standard Procedure for Microtiter Plates). Standards were diluted in membrane

buffer from 5 mg/ml bovine serum albumin stock solution, for the range of 0.05 to 1

mg/ml. Absorbance was measured at 595 nm by Varioskan (Flash, Thermo Scientific).

3.6 ATPase assay

ATPase assay was used to measure the effect of aliskiren on the ATPase activity of

human MDR1 expressed in Sf9 insect cell membrane vesicles. In the assay, transport

activity of MDR1 is determined by the amount of inorganic phosphate (Pi) that is

liberated according to the hydrolysis of ATP to ADP (Sarkadi 1992). Thus, the amount

of Pi liberated is proportional to the activity of that transporter, which substrates of the

transporters stimulate. Liberated Pi is detected by colorimetric reaction.

7

A 0.5 mg/ml membrane suspension was made in an assay mix and distributed onto the

96 well plate on ice. Serial dilutions of aliskiren and verapamil (control drug), were

added to the well plate in 1 µl DMSO. 60 mM NA3VO4 was added to the designated

wells. The plate was preincubated at 37 °C for 5 min and the ATPase reaction was

started by the addition of 25 mM Mg-ATP. After 20 min incubation at 37 °C, the

reaction was stopped by adding sodium dodecyl sulfate (SDS 5%). The plate was

incubated with the freshly prepared colorimetric detection reagent (35 mM ammonium

molybdate in 15 mM zinc acetate and 10 % ascorbic acid) at 37 °C for 25 min.

Absorbance was measured at 655 nm by Varioskan and amount of free phosphate (Pi)

liberated (nmol/well) was calculated using the phosphate standard curve. Na-

orthovanadate (Na3VO4) is a specific inhibitor for the ABC transporters (Urbatch et al.,

1995). Na3VO4–sensitive ATPase activity was calculated as the amount of Pi liberated

per milligram membrane protein per minute (nmol/mg/min), substracting the values

obtained in the presence of Na3VO4 from the values obtained in the absence of Na3VO4.

3.7 Vesicular transport assay

In the case of inside-out membrane vesicles, efflux proteins transport the substrates

from the buffer into the membrane vesicles in the presence of ATP. The quantity of the

transported substrate can then be measured. In this assay, the amount of aliskiren (nmol)

transported into the Sf9-MDR1 membrane vesicles was measured. ATP-dependent

transport of aliskiren (nmol/mg/min) was further calculated.

3.7.1 Determination of test circumstances

Determination of linearity of transport as function of time and optimization of protein

amount (µg) in reaction were carried out. Aliskiren was assayed in the concentration

range of 1, 10 and 100 µM with incubation times 1, 3, 10, 15 and 30 min. Protein

amount of 50 µg was used. Aliskiren concentration 10 µM was further assayed with

protein amounts 20 and 50 µg for incubation times 1, 3, 15 min and with protein

amounts 20, 50 and 100 µg for the 10 min incubation time. 1 min incubation time

8

showed the highest rate of ATP-dependent transport (nmol/mg/min) in both assays and

was therefore used as reaction time for the further experiments. No saturation of

transport was observed between different protein amounts in the reaction. Protein

amount of 50 µg was selected, because the experience was that it shows less variation

than the smaller protein amount of 20 µg.

3.7.2 Determination of Km and Vmax for aliskiren

Aliskiren concentrations 0.5, 1, 2, 4, 8, 10, 16 and 32 µM were used for the

determination of Km and Vmax values. A mix of membrane suspension and aliskiren

dilution in DMSO was made to assay mix and distributed to the desired wells.

Verapamil (100 µM) in 0.75 µl DMSO was used as a control. The plate was pre-

incubated at 37 °C for 15 min and reaction started by addition of preincubated Mg-ATP

or assay mix. The plate was incubated at 37 °C for 1 min and reaction stopped by

adding ice-cold washing mix. The samples were transferred to a 96 well filter plate

(MultiScreen, Millipore, Ireland) and rinsed 5 times with washing mix. After the filters

had dried, 100 µl 0.1 M ammoniumhydroxide was added to each well and incubated in

room temperature for 10 minutes. The samples were then transferred through the filter

to a 96 well plate by suction.

3.7.3 Determination of IC50 and Ki for inhibitors

Aliskiren concentration of 2 µM was used for the determination of IC50 values for

inhibitors. For ketoconazole and verapamil, concentrations of 0.1, 1, 2, 4, 8, 16, 32 and

100 µM were used. For itraconazole, the concentrations were 0.1, 0.25, 0.5, 1, 2, 4, 6

µM and for hydroxyitraconazole 0.1, 0.25, 0.5, 1, 2, 4, 6 and 8 µM. The solubility of

itraconazole and hydroxyitraconazole in 800 µM stock solution in DMSO and in assay

mix in the concentrations used, was ensured with nephelometer (Nepheloskan Ascent,

Labsystems, Finland). To determine the Ki for itraconazole and hydroxyitraconazole,

aliskiren concentrations of 1, 2 and 8 µM were used against the range of inhibitor

concentrations.

9

In ketoconazole and verapamil vesicular transport assays, the volume of inhibitor added

to the wells, was increased to improve pipeting accuracy. Inhibitor dilution in DMSO

was mixed with assay mix and 5.75 µl of the inhibitor solution was added instead of

0.75µl. To start the reaction, 20 µl of ATP-Mg or assay mix was added instead of 25 µl,

so that the volume of reaction and DMSO concentration of 2 % remained the same.

Accordingly, ATP-Mg dilution was made stronger, so that the amount of ATP in the

reaction was sufficient.

3.8 Measuring of aliskiren

Aliskiren samples were measured using UPLC-MS/MS technique. ULPC (Acquity,

Waters, USA) column used was UPLC HSS T3 with dimension 2.1 x 100 mm and

particle size 1.8 µm (Waters, USA). Flow rate was 0.3 ml/min and injection volume 10

µl. Mobile phase A was 0.1 % formic acid and mobile phase B acetonitrile. Mass

spectrometry used was TandemQuadrupole, model G6410A (Agilent, USA).

Propranolol was used as an internal standard.

3.9 Sigma plot

Km and Vmax values for aliskiren and IC50 values for inhibitors were calculated from the

in vitro results by SigmaPlot (Systat Software Inc, USA) using nonlinear regression

analysis. One site saturation equation was used to obtain Km and Vmax and one site

competition equation for IC50 values. Weighing did not improve the fittings, thus none

was used. For itraconazole and its metabolite, Ki was calculated (Equation 1) using three

IC50 values obtained by using three different aliskiren concentrations (1, 2 and 8 µM).

Equation 1

10

3.10 Pharmacokinetic modeling

Model was constructed using Stella ™ modeling software (isee systems version 9.0.1,

USA). Compartmental absorption and transit (CAT) model (Yu et al., 1996) was used

as a basis, to which an enterocyte compartment and MDR1-mediated efflux was added

(Figure 1). Passive permeation on the apical and basolaterial membrane of the

enterocyte was represented with the following equation (Equation 2): The model

parameters are presented (Table 3).

Equation 2

Figure 1. Pharmacokinetic model for simulating intestinal absorption of MDR1

substrates and the effect of MDR1 inhibition (modified from (Kortejärvi et al., 2007)

and material from V-P Ranta).

11

Model parameters.

Model parameter Value Unit Reference

GE 4250 µg/min Kortejärvi et al., 2007

Kge 0.0583 min-1

Kortejärvi et al., 2007

Kt 0.035 min-1

Yu et al., 1996

Kd 0.0317 min-1

Yu et al., 1996

Ka 6.01 x 10-3

min-1

Linnankoski et al.,2006

Peff

0.00451 cm/min

Kel 4.87 x 10-4

min-1

t ½ 23.7 h-1

V lumen 35.7 ml

A enterocyte 2857 cm2

V enterocyte 2.86 cm3 (ml)

Vd 135000 ml Azizi et al., 2006

Hepatic extraction

ratio

0.10 Azizi et al., 2006

Km 2.79 µg/ml

Vmax1 1.6 x 10

-4 µg/cm

2/min Vaidyanathan et al., 2008

Vmax2 0.0861 µg/cm

2/min Tang et al., 2002

logD6.0 -0.28 Calculated by ACDLabs

PSA 146 Calculated by ACDLabs

4 RESULTS

4.1 ATPase assay

Aliskiren increased liberated inorganic phosphate (Pi) (nmol/mg/min) in Sf9-MDR1

membranes, suggesting enhanced activity of MDR1 transporter (Figure 2). However,

the results showed great variation (n = 6). At the highest, aliskiren increased liberated Pi

52 % (at 5 µM concentration), which is proportional to the enhanced activity of the

Table 3.

12

transporter. Verapamil was used as a positive control, known to stimulate the baseline

ATPase activity of MDR1 transporter. Verapamil increased liberated Pi 85 % at the

highest (at 10 µM concentration), indicating stronger activation of the transporter than

aliskiren (Figure 3).

0

20

40

60

80

100

120

140

160

180

200

0 1 5 10 100

Lib

era

ted

Pi (

nm

ol/

mg/

min

)

Aliskiren concentration (µM)

0

20

40

60

80

100

120

140

160

180

200

220

0 10 20 60

Lib

era

ted

Pi (

nm

ol/

mg/

min

)

Verapamil concentration (µM)

Figure 2. Na3VO4-sensitive ATPase activity of Sf9-MDR1 membranes in the presence

of aliskiren. Aliskiren increased liberated Pi (nmol/mg/min) (mean ± SD), suggesting

enhanced activity of MDR1 transporter (n = 6).

Figure 3. Na3VO4-sensitive ATPase activity of Sf9-MDR1 membranes in the presence

of verapamil. Verapamil was used as a positive control, known to increase liberated Pi

(nmol/mg/min) (mean ± SD) in MDR1 membranes (n = 6).

13

4.2 Vesicular transport assay

4.2.1 Feasibility of MDCKII-MDR1 membrane vesicles

ATP–dependent transport of aliskiren was concentration dependent (Figure 4, Figure 5).

Shape of the figure (3 concentrations used: 1, 10 and 100 µM) is very similar in both

MDCKII and Sf9 membranes, only MDCKII membranes gave lower values for the

ATP-dependent transport (nmol/mg/min). Vesicular transport study with MDCKII-

MDR1 membranes was performed only once, thus requires additional experiments.

Furthermore, incubation time of 15 min was used, which was later reduced to 1 min

because of saturation after.

0,000

0,005

0,010

0,015

0,020

0,025

0,030

0,035

0,040

0 20 40 60 80 100 120

ATP

-de

pe

nd

en

t tr

ansp

ort

(n

mo

l/m

g/m

in)

Aliskiren concentration (µM)

Figure 4. ATP-dependent transport of aliskiren in Sf9-MDR1 membranes (n = 1).

Incubation time of 15 min was used.

14

4.2.2 Determination of test circumstances

The rate of ATP-dependent transport of aliskiren was highest with incubation time of 1

min, and showed saturability after (Figure 6, Figure 7). Protein amounts 20, 50, 100 µg

in the reaction showed no difference in the rate of ATP-dependent transport (Figure 7),

suggesting that the transport is not saturated due to limited amount of transporter in the

reaction. In the latter study, comparing the circumstances of incubation time 1 min and

protein amount 50 µg, the rate of ATP-dependent transport was higher.

0,000

0,002

0,004

0,006

0,008

0,010

0,012

0 20 40 60 80 100 120

ATP

-de

pe

nd

en

t tr

ansp

ort

(n

mo

l/m

g/m

in)

Aliskiren concentration (µM)

Figure 5. ATP-dependent transport of aliskiren in MDCKII-MDR1 membranes (n = 1).

Incubation time of 15 min was used.

15

4.2.3 Determination of Km and Vmax for aliskiren

ATP-dependent transport of aliskiren showed saturable kinetics with Km of 5.05 µM and

Vmax of 0.89 (nmol/mg/min) (Figure 8, Table 4).

0,00

0,02

0,04

0,06

0,08

0,10

0,12

0,14

AT

P-d

epen

den

t tr

an

spo

rt

(nm

ol/

mg

/min

)

Incubation time (min)

1 min

3 min

10 min

15 min

30 min

0,00

0,10

0,20

0,30

0,40

0,50

0,60

AT

P-d

epen

den

t tr

an

spo

rt

(nm

ol/

mg

/min

)

1 min prot. 20 microg

1 min prot. 50 microg

3 min prot. 50 microg

10 min prot. 20 microg

10 min prot. 50 microg

10 min prot. 100 microg

15 min prot. 50 microg

Figure 6. Incubation time 1 min showed the highest rate of ATP-dependent transport of

aliskiren (nmol/mg/min). Aliskiren concentration 10 µM and protein amount 50 µg

were used.

Figure 7. No saturation of ATP-dependent transport of aliskiren was observed with

varying protein amounts 20, 50 and 100 µg in the reaction. Aliskiren concentration 10

µM and incubation times 1, 3, 10 and 15 min were used.

16

Km and Vmax values for aliskiren calculated with SigmaPlot (n = 3).

Coefficient Value SD Unit

Km 5.1 3.5 µM

Vmax 0.89 0.13 nmol/mg/min

4.2.4 Determination of IC50 and Ki for inhibitors

Itraconazole (Figure 11) and hydroxyitraconazole (Figure 12) inhibited MDR1-

mediated transport of aliskiren (2 µM) in Sf9-MDR1 membranes with an IC50 of 1.7

and 1.0 µM, respectively (Table 5). Ketoconazole (Figure 9) and verapamil (Figure 10)

were less potent MDR1 inhibitors with IC50 values of 15.7 and 18.2 µM (Table 5). Ki

calculated for itraconazole was 0.82 and for hydroxyitraconazole 0.61 (Table 5). ATP-

dependent transport of different concentrations (1, 2 and 8 µM) of aliskiren in the

presence of itraconazole, predicted by SigmaPlot, is presented (Table 13).

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

0 10 20 30 40

ATP

-de

pe

nd

en

t tr

ansp

ort

(n

mo

l/m

g/m

in)

Aliskiren concentration (µM)

Figure 8. ATP-dependent transport of aliskiren (mean ± SD) in Sf9-MDR1 membranes

(n = 3).

Table 4.

17

Figure 10. ATP-dependent transport of 2 µM aliskiren (mean ± SD) in Sf9-MDR1

membranes in the presence of verapamil. Verapamil concentrations of 0.1, 1, 2, 4, 8, 16,

32 and 100 µM were used to determine the IC50 value (n=3).

0,0

0,2

0,4

0,6

0,8

1,0

1,2

0,1 1 10 100

ATP

-de

pe

nd

en

t tr

ansp

ort

(n

mo

l/m

g/m

in)

Ketoconazole concentration (µM)

0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

0,1 1 10 100

ATP

-de

pe

nd

en

t tr

ansp

ort

(n

mo

l/m

g/m

in)

Verapamil concentration (µM)

Figure 9. ATP-dependent transport of 2 µM aliskiren (mean ± SD) in Sf9-MDR1

membranes in the presence of ketoconazole. Ketoconazole concentrations of 0.1, 1, 2, 4,

8, 16, 32 and 100 µM were used to determine the IC50 value (n = 3).

18

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1,0

0,1 1 10

ATP

-de

pe

nd

en

t tr

ansp

ort

(n

mo

l/m

g/m

in)

Itraconazole concentration (µM)

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1,0

0,1 1 10

ATP

-de

pe

nd

en

t tr

ansp

ort

(n

mo

l/m

g/m

in)

Hydroxyitraconazole concentration (µM)

Figure 11. ATP-dependent transport of 2 µM aliskiren (mean ± SD) in Sf9-MDR1

membranes in the presence of itraconazole. Itraconazole concentrations of 0.1, 0.25, 0.5,

1, 2, 4 and 6 µM were used to determine the IC50 and Ki values (n = 3).

Figure 12. ATP-dependent transport of 2 µM aliskiren (mean ± SD) in Sf9-MDR1

membranes in the presence of hydroxyitraconazole. Hydroxyitraconazole

concentrations of 0.1, 0.25, 0.5, 1, 2, 4 and 8 µM were used to determine the IC50 and Ki

values (n = 3).

19

IC50 (µM) STD Ki STD

Ketoconazole 15.7 4.8

Verapamil 18.2 4.9

Itraconazole 1.7 0.2 0.82 0.46

Hydroxyitraconazole 1.0 0.3 0.61 0.32

4.2.5 Pharmacokinetic modeling

In the model, in order to correctly simulate reported plasma Cmax 254 ng/ml for aliskiren

(Drugs@FDA) using the experimental Km value (2.89 µg/ml), in vivo relevant value for

Vmax could not be used (Table 6). Instead, Vmax had to be increased roughly 100-fold

(50000 µg/min), suggesting that the drug concentration in enterocytes did not reflect the

in vitro or in vivo situation.

0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

1,6

1,8

0,1 1 10

AT

P-d

epen

den

t tr

an

spo

rt

(nm

ol/

mg

/min

)

Itraconazole concentration (µM)

Aliskiren 1 microM

Aliskiren 2 microM

Aliskiren 8 microM

Figure 13. ATP-dependent transport of three concentrations of aliskiren (1, 2 and 8 µM)

in Sf9-MDR1 membranes in the presence of itraconazole, predicted by SigmaPlot.

Table 5. IC50 values for the inhibitors calculated by SigmaPlot (aliskiren concentration

of 2 µM). Ki values were calculated from IC50 values obtained by using three different

aliskiren concentrations (1, 2 and 8 µM).

20

To increase the drug concentration in enterocytes, thus to enhance the active efflux by

MDR1 in the model, the passive permeability of aliskiren in the basolateral membrane

was decreased. The basolateral surface area (basol. A) was decreased to 1/10 and 1/100.

In the same circumstances (same values for Km and Vmax), the reduction of basolateral

surface area resulted in smaller plasma Cmax (Table 6), suggesting a better description

for the passive permeability of drug in the basolateral membrane.

Table 6. Simulated mean plasma Cmax values for aliskiren.

Predicted Cmax (ng/ml) Ba (%) Basol. A Km (µg/ml) Vmax (µg/min)

20 mg i.v. 140

300 mg p.o. 240 11 1 2.79 50000

300 mg p.o. 1810 11 1 2.79 500

300 mg p.o. 120 6 1/10 2.79 50000

300 mg p.o. 20 1 1/100 2.79 50000

300 mg p.o. without MDR1 1880 84 1

1880 84 1/10

1240 55 1/100

Experimental in vivo

300 mg p.o.1

240 3

150 mg p.o. after

itraconazole treatment

2 766

1Drugs@FDA

2Tapaninen et al. 2010a

21

5 DISCUSSION

5.1 Correlations of in vitro parameters to in vivo literature data

5.1.1 Aliskiren

Aliskiren showed concentration-dependent transport and high affinity for MDR1 with a

Km value 5.1 µM (± 3.5). Km calculated for aliskiren was quite close to the earlier data

of 2.1 µM (± 0.5) obtained from an ATPase assay using Sf9-MDR1 membranes and 3

µM obtained in a Caco-2 transport assay (Vaidyanathan et al. 2008). ATPase assay is

generally not recommended for kinetic studies, because it is not a functional assay

measuring the actual transport of a substrate. However, the results obtained from the

three different assay systems are consistent. Calculation of the Km for aliskiren served as

a validation of the method. The use of another known probe substrate (e.g. digoxin) to

compare to literature would have improved the credibility of the study more.

The mean plasma Cmax of aliskiren after a 300 mg dose was 0.46 µM (Drugs@DFA),

which is below the in vitro Km value of aliskiren. This suggests that systemic saturation

of MDR1 transport is unlikely, but due to great inter-individual variability in

pharmacokinetics of aliskiren, this option cannot be ruled out entirely. In the intestine,

the concentration of the drug is evidently higher. EMA draft guidance (2010)

recommends that in studying intestinal transport, the drug could be studied over the

concentration range 0.1 – 50-fold the dose divided by 250 ml, which is the typical

amount of water a drug is swallowed with. For aliskiren, theoretically 300 mg / 250 ml

would result in an intestinal concentration of 2.17 mM, 1000-fold the Km value.

However, the concentration of drug in the binding site of MDR1 ((the cytosolic leaflet

of lipid bilayer (Shapiro and Ling 1997)) is the concentration that determines the active

efflux transport by MDR1. In vivo, aliskiren has been shown to display linear

pharmacokinetics (AUC (0-96h) and Cmax) in a dose range of 75 mg to 600 mg

(Vaidyanathan et al. 2006).

22

The maximum rate of transport (Vmax) depends on the expression of MDR1, which is

not likely as high in vivo in the human intestine as in Sf9-MDR1 cell line. Perhaps the

Vmax value could be utilized to compare the expression of MDR1 in different cell lines.

Also, similar Vmax value throughout the experiments gives confirmation, that the

expression of MDR1 is same, when different passages of cell lines or different batches

of membrane vesicles are used.

5.1.2 Inhibitors

IC50 value for inhibitor depends on the substrate, substrate concentration, assay system

and cell line used. Thus, comparing the inhibitory potencies of different inhibitors

obtained in different studies and laboratories is challenging (Table 7). However, the

IC50 values obtained for ketoconazole and verapamil in this in vitro study suggest

weaker inhibition of the MDR1-mediated transport than what has been reported

previously (Table 7). The IC50 values do seem to correlate quite well to the in vivo

clinical interaction studies with aliskiren (Table 8).

Table 7.IC50 values obtained in this in vitro study and previously reported in the

literature.

Experimental Literature

Cell line Sf9-MDR1 Sf9-MDR11

Caco-22 NIH-3T3-

G1853

MDCKII-

MDR14

Ketoconazole

Verapamil

Itraconazole

Hydroxyitraconazole

Cyclosporine A

15.7

18.2

1.7

1

2.2

5.2

1.2

2.1

1.3

5.6

1.7

1.4

3.7

5.9

1.3

1Obtained in vesicular transport study with calcein AM as substrate (Szeremy et al., 2011).

2Obtained in transport study with digoxin as substrate (FDA 2006).

3Obtained in uptake study with fluorescent daunorubicin as substrate (NIH-3T3-G186 cell line contains

human MDR1) (Wang et al., 2001). 4Obtained in transport study with digoxin as substrate (Keogh and Kunta 2006)

23

Table 8. Comparison of MDR1-mediated interactions with aliskiren in vitro to in vivo

clinical interaction studies. For IC50 determination aliskiren concentration of 2 µM was

used.

In vitro In vivo

IC50 (µM) Ki AUC Cmax

Ketoconazole 15.7 2-fold1

2-fold1

Verapamil 18.2 1.8-fold2

1.8-fold2

Itraconazole 1.7 0.82 6.5-fold3

5.8-fold3

Hydroxyitraconazole 1.0 0.61

1 Vaidyanathan et al., 2008

2 Rebello et al., 2010

3 Tapaninen et al., 2010

Quinney et al. (2008) showed in an in vivo rat study, that the active metabolite of

itraconazole, hydroxyitraconazole, is formed during the intestinal first pass metabolism

by CYP3A4. The result was consistent with earlier studies. In addition, compared to

itraconazole the systemic concentrations of hydroxyitraconazole were higher and

declined more slowly. In our study, hydroxyitraconazole was shown to be a potent

MDR1 inhibitor in vitro with similar inhibitor potency to itraconazole (or even more

potent). This suggests that the metabolite has potentially a highly significant

contribution to the MDR1-mediated interactions with itraconazole.

Itraconazole and ketoconazole have both been regarded as potent inhibitors of MDR1

(Table 7) and CYP3A4 in vitro (IC50 values 0.12 and 0.012 µM respectively (Wang et

al., 1999)). Thus, ketoconazole is even 10 times more potent CYP3A4 inhibitor in vitro

than itraconazole. Hydroxyitraconazole inhibited CYP3A4 with an IC50 value of 0.23

µM (Wang et al., 1999). In vivo in humans, itraconazole and ketoconazole both

increased midazolam (substrate for CYP3A4 but not MDR1) AUC0-∞ 10-fold and 15-

fold respectively (Olkkola et al., 1994), which correlates to ketoconazole being more

potent CYP3A4 inhibitor.

However the in vivo interaction between ketoconazole and aliskiren was not as

significant as the interaction between itraconazole and aliskiren. Ketoconazole increased

aliskiren Cmax and AUC approximately 1.8-fold in humans (Vaidyanathan et al. 2008).

24

Interaction was not associated with safety or tolerability issues and no dose adjustments

were recommended with co-administration. This suggests that ketoconazole might not

be as potent inhibitor of MDR1 as itraconazole, which the results from our in vitro

interaction studies support (Table 8). Interaction between itraconazole and aliskiren is

probably of clinical importance and simultaneous use should be avoided (Tapaninen et

al., 2010a). A 6-fold increase in aliskiren exposure might increase the risk of

hypotension and adverse effects, especially in continuous treatment in patient

population. Also, possible inter-individual variation in the extent of interaction has to be

considered, as aliskiren has showed notable interindividual variability even in the group

of healthy subjects.

Verapamil has been regarded as only a moderate inhibitor of MDR1 (Table 7) and a

weak inhibitor of CYP3A4 in vitro (IC50 value 23 µM (Wang et al., 1999)). In vivo in

humans, verapamil increased aliskiren Cmax and AUC approximately 2-fold (Rebello et

al., 2010). Such level of aliskiren exposure was safe and well tolerated in healthy

participants and no dose adjustments were needed. In vivo interactions of ketoconazole

and verapamil with aliskiren seem to be of similar class, as were the IC50 values

obtained in our study. The results suggest that ketoconazole and verapamil both are

moderate inhibitors of MDR1. In vivo verapamil increased midazolam AUC0-∞ 3-fold

(Backman et al., 1994), a lot less than potent the CYP3A4 inhibitors ketoconazole and

itraconazole. This correlates to the in vitro evaluation of verapamil being a weak

CYP3A4 inhibitor. In further studies, it would be interesting to obtain Ki values for also

ketoconazole and verapamil.

Another interesting MDR1 inhibitor to study in vitro in further studies is cyclosporine.

Cyclosporine is also a potent inhibitor of MDR1 (Table 7) and a weak inhibitor of

CYP3A4 (IC50 <50 µM, (FDA draft guidance 2006)). Coadministrated with aliskiren,

cyclosporine increased aliskiren Cmax 2.5-fold and AUC 4-5-fold (Rebello et al., 2011).

It would be interesting to compare IC50 and Ki values for cyclosporine to itraconazole’s,

as the extent of the in vivo interaction was not quite as pronounced as with itraconazole.

But, it has to be considered that the clinical trial arrangements in studying these

interactions differed. In the itraconazole interaction study, aliskiren (150 mg) was given

25

on a day 3 of a 5-day treatment with itraconazole, whereas in the cyclosporine

interaction study aliskiren (75 mg) was given simultaneously with cyclosporine.

Perhaps the interaction appears more pronounced, when the inhibitor is given first and

the binding sites of MDR1 are already occupied. Another explanation for the stronger in

vivo interaction with itraconazole could be the contribution of its metabolite.

Itraconazole and its metabolite are both also potent CYP3A4 inhibitors, which may

enhance the intestinal availability of aliskiren.

5.1.3 Limitations of in vitro assays applied

We used the ATPase assay to confirm the interaction between aliskiren and MDR1

transporter. ATPase assay can be used as a screening tool to identify substrates of

MDR1, but it is not designed to distinguish substrates from inhibitors. As was observed

in our studies, ATPase assay showed high intra- and inter-assay variability. To avoid

false negatives, substrates have to be assayed in wide enough range of concentrations,

because different concentrations can stimulate the ATPase activity a different amount.

In order to do this, the substrate has to be soluble enough. Another complication was the

assay yielding a high value (liberated Pi) for the pure solvent (DMSO), as also DMSO

stimulates the ATPase activity.

In vesicular transport assay, the transporter is located on the outer membrane of the

inside-out membrane vesicle, being more available for the substrate. For drugs with

poor permeability (e.g. aliskiren) this enhances the access to the transporter. On the

other hand, for drugs with high permeability the effect of active transport can go

unnoticed as the passive permeability and active transport occur to the same direction in

this assay. Therefore the vesicular transport assay does not suite as well for identifying

high permeability MDR1-substrates. However, because the MDR1 efflux is more

relevant for low permeability drugs, this limitation does not pose a problem. Verapamil

(100 µM) was used as a method control. Verapamil inhibited the transport of 2 µM

aliskiren so that the amount of aliskiren (nmol) recovered inside the membrane vesicles

was the same as was passively diffused, without ATP involved. Vesicular transport

26

assay should be an effective model for kinetic studies and was shown a sensitive

method to detect MDR1-mediated drug-drug interactions (Serezemy et al., 2010).

The results obtained are preliminary. More repeated experiments and standardization of

the test circumstances are needed to improve presicion and repeatability. Sources of

variation could have been the use of different batches of membrane vesicles and/or

differences in the protein measurement. Aliskiren was measured by UPLC/MS-MS and

propranolol was used as an internal standard. Propranolol is not an ideal internal

standard for aliskiren, but gave accurate enough results for our experiments. An

important limitation in our study, and in vitro studies in general, was the poor water

solubility of itraconazole and its metabolite. For itraconazole and hydroxyitraconazole

only concentrations up to 6 and 8 µM respectively could be used in the assays. Poor

solubility of drugs can prevent comprehensive in vitro interaction studies.

Use of MDCKII-MDR1 membrane vesicles in the experiments turned out to be

laborious and costly. A large amount of cells was needed to be grown in order to purify

enough membrane vesicles for only one experiment. The same membrane vesicle

preparation method was used for both MDCKII and Sf9 cells. The preparation method

used was originally for Sf9-MRP2 cells. Thus, more investigation is needed to see if the

method can be optimized for MDR1 expressing cells and mammalian cells. It would

give us more insight, if the amount of inside-out membrane vesicles (%) was

determined. The expression level of MDR1 and the composition of the cell membrane

can differ in insect and mammalian cells. Addition of cholesterol to Sf9 membranes has

been attempted to mimic the mammalian membrane and to improve the in vivo

relevance of the assays.

5.2 Pharmacokinetic modeling

5.2.1 Discussion

Due to time limitations, only a simple pharmacokinetic model was tested to see the

possibility for further development. The intestinal absorption of aliskiren was simulated

27

with and without the effect of active efflux by MDR1 and the resulting plasma

concentrations (Cmax) were compared to reported aliskiren plasma concentrations in vivo.

The resulting aliskiren plasma concentrations from simulations without MDR1 efflux

were compared to in vivo situation with a potent MDR1 inhibitor.

Aliskiren has poor oral bioavailability of approximately 3 % (Drugs@FDA). After a

single dose of 300 mg, aliskiren average Cmax of 254 ng/ml was reported. However great

inter-individual variability has been observed (e.g. 215 ± 122 ng/ml (n=19);

(Vaidyanathan et al. 2006)). After 20 mg i.v. dose, the simulated Cmax was 140 ng/ml

(dose/Vd) (Table 6). With the assumed Vd in the model, bioavailability of 3 % after 300

mg dose would result in Cmax of only 70 ng/ml, suggesting that the Vd used in the model

may be incorrect. Aliskiren does display multicompartmental kinetics (Vaidyanathan et

al., 2008), which has not been taken into account in the model. Comparison could not be

made to AUC values from literature, as the simulated values were higher.

The model failed to demonstrate the plasma Cmax observed in vivo by using the

experimental Km value and in vivo relevant value for Vmax. The problem in the model

seemed to be too rapid permeation through the enterocyte resulting in low intracellular

aliskiren concentration. Permeation was described with the equation: 2 x Peff x A x (Cd –

Cr) on both apical and basolateral membranes. In the basolateral permeation,

concentration of aliskiren in blood (Cr) was assumed 0, because of sink conditions.

To describe MDR1 activity in the human intestine in vivo, Vmax values obtained for

vinblastine and aliskiren in Caco-2 transport assays (0.0861 and 0.00016 µg/cm2/min

respectively) were used as rough estimates. Simcyp® pharmacokinetic modeling

software uses a scaling factor 2.04 for scaling Caco-2 cell line to human intestine

(jejunum), based on the ratio of total MDR1 to total protein in vitro and in vivo. Using

the higher value for Vmax (0.0861 nmol/cm2/min) and an estimate for enterocyte

compartment membrane surface area (A) 2857 cm2, value 246 µg/min for Vmax is

calculated. Scaling of this to human intestine (jejunum) according to the Simcyp®

scaling factor 2.04, an estimated Vmax value 502 µg/min is obtained.

28

In order to correctly simulate aliskiren plasma concentrations using the experimental Km

value (2.89 µg/ml), the estimated in vivo value for Vmax (502 µg/min) could not be used.

Instead, Vmax had to be increased roughly 100-fold (50000 µg/min) (Table 6).

Simulations with Vmax 500 µg/min resulted in the same plasma concentrations as was

simulated without active efflux (Cmax 1800 ng/ml), suggesting that no active efflux

occurs. This indicates that the drug concentration in enterocytes in the model is too low

for effective efflux and does not reflect the in vitro or in vivo situation.

In theory, the absorption area is larger in the apical membrane of the enterocyte due to

the intestinal microvilli. This approach was tested in order to slow down the basolateral

permeability of aliskiren in the model. The surface area (A) of the basolateral

membrane of the enterocyte compartment was reduced to 1/10 and 1/100. In the model

with MDR1 efflux, 1/10 basolateral surface area resulted in reduction of Cmax by half

(120 ng/ml) when the increased drug concentration in the enterocyte accelerated the

efflux (Table 6). In the model without active efflux, 1/10 basolateral surface area did

not have an effect on Cmax, only1/100 surface area reduced Cmax to 1240 ng/ml.

After a single dose of 150 mg aliskiren administrated during a treatment with potent

MDR1 inhibitor itraconazole, aliskiren average Cmax 766 ± 377 ng/ml was reported

(Tapaninen et al. 2010a). This suggests a great increase in the oral bioavailability of

aliskiren, at least partly due to inhibition of active efflux by MDR1 in the intestine. In

the model, this situation was simulated without MDR1 efflux. 300 mg dose resulted in

Cmax 1880 ng/ml (Table 6), which may reflect to the in vivo situation with a potent

MDR1 inhibitor, considering that in vivo Cmax 766 ng/ml was reached after a 150 mg

dose. In the future, implementation of kinetic in vitro inhibition parameters (IC50, Ki) to

predict the extent of a drug-drug interaction would be of great value.

5.2.2 Considerations

In the model, the drug is assumed evenly distributed in the enterocyte. In vivo, MDR1 is

located in the membrane (cytoplasmic leaflet of the lipid bilayer (Shapiro and Ling

1997)). A lipophilic substrate is likely more distributed in the membrane, as a

29

hydrophilic substrate is more distributed in the intracellular aqueous phase, where the

volume is also larger. This suggests that for effective efflux, hydrophilic substrates need

to have higher affinity to the transporter (Km) due to lower concentration in the binding

site. For lipophilic substrates, a weaker affinity can result in transport as effective.

Expression of the MDR1 transporter has been shown to increase along the GI tract

having the highest expression in the colon (Mouly et al., 2003; Thorn et al., 2005). In a

more advanced model, a correlation factor could be used for the different compartments

of the gastrointestinal tract. Because aliskiren is poorly metabolized, the effect of

intestinal CYP3A4 is postulated to be a smaller contributor to the poor bioavailability

and thus, was not included in the model. It has been suggested however, that substrates

notably effluxed by MDR1 are more exposed to metabolism due to reabsorption into the

enterocytes after efflux (Cummings et al., 2001). In further studies, it would be

interesting to see if the contribution of intestinal CYP3A4 could be estimated by

pharmacokinetic modeling. Opposite to MDR1, CYP3A4 expression is highest in the

duodenum in vivo (Thorn et al., 2005).

Pharmacokinetics of aliskiren have showed great inter-individual variability

(Waldmeier et al., 2007; Tapaninen et al. 2010a). This may be, at least partly,

contributed by inter-individual variation in the expression of intestinal MDR1. However,

it is not been clarified what are factors influencing MDR1 expression and to what extent.

Genetic variability in the ABCB1 gene has been suggested, but the common haplotypes

c.1236C-c.2677G-c.3435C (CGC) and c.1236T-c.2677T-c3435T (TTT) showed no

effect on the pharmacodynamics or pharmacokinetics of aliskiren (Tapaninen et al.

2010b). The researchers suggested that the large variability may be explained by

variability in the gastronintestinal physiology and other factors affecting the activity of

MDR1 or CYP3A4, or other transporters of enzymes involved. In addition, aliskiren

showed similar pharmacokinetics and pharmacodynamics in healthy Japanese and

Caucasian subjects, although the pharmacokinetic parameters of both groups showed

notable variation (Vaidyanathan et al. 2006). If these individualities could be explained

and predicted, pharmacokinetic modeling could be a prospective tool in estimating an

individual drug dose in clinical practice. In addition,

30

5.3 Comparison of aliskiren and digoxin as MDR1 probes

Digoxin is widely used and generally most recommended probe substrate in studying

MDR1-mediated drug-drug interactions (Keogh and Kunta 2006; Rautio et al., 2006).

Interactions with digoxin are clinically relevant due to its narrow therapeutic index, that

may lead to drug induced toxicity. Clinical relevance enables the study of in vitro-in

vivo correlations and establishment of predictive models. Neither aliskiren nor digoxin

is exposed to significant CYP metabolism. The difference is that digoxin is eliminated

mainly via kidney by excretion of unchanged digoxin into urine, as aliskiren’s

elimination occurs mainly via hepato-biliary route to feces. MDR1 is responsible for the

active secretion of digoxin in the renal tubular cells (de Lannoy and Silverman, 1992),

thus inhibitors of MDR1 potentially affect the elimination of digoxin as well.

The interaction between aliskiren and itraconazole in vivo in humans seems to be more

pronounced than the interaction of digoxin and itraconazole. The serum concentrations

of digoxin increased about 2-fold, when a therapeutic dose of intraconazole was given

simultaneously with digoxin for 10 days (Partanen et al., 1996). However, inhibitor was

given simultaneously instead of giving it first. Itraconazole decreased the renal

clearance of digoxin most likely due to inhibition of MDR1-mediated active secretion in

the kidney, which only partly explains the increase in serum concentrations of digoxin

(Jalava et al., 1997). Inhibition of MDR1 in small intestine increasing the bioavailability

of digoxin likely contributes to the increased serum concentration.

Aliskiren does not have a narrow therapeutic index similar to digoxin, but on the other

hand it makes aliskiren more safe probe to study MDR1-mediated interactions in

humans. Aliskiren is classified as a class III compound according to the

Biopharmaceutics Classification System (Drugs@FDA), having high solubility and low

permeability. Digoxin is highly permeable and poorly soluble, classified as class II

compound in the BCS system. Inhibition data obtained with digoxin may be applied to

other MDR1 substrates similar to digoxin. On the other hand, inhibition data obtained

with aliskiren could be applied to MDR1 substrates similar to aliskiren (wide

therapeutic index, poor permeability). It has been suggested however, that due to

31

multiple binding sites of MDR1, different probes binding to different sites of MDR1

would be needed for the characterization of interactions. For further studies, it would be

interesting to compare the in vitro interactions of digoxin and aliskiren as probes with

well characterized inhibitors (e.g. itraconazole, ketoconazole and verapamil).

FDA has presented criteria for preferred in vitro MDR1 probe substrates and inhibitors

in draft guidance for drug interaction studies (2006) (Table 9). However, a substrate or

inhibitor that meets all the criteria has not been identified, instead a list of acceptable

substrates, inhibitors and concentrations used is suggested.

Criteria for preferred in vitro MDR1 probe substrates:

1. Selective for the MDR1 transporter

2. Exhibits low to moderate passive permeability (2 – 30 x 10-6

cm/s)

3. No significant metabolism1

4. Commercially available1

5. May be used as an in vivo MDR1 probe substrate1

1 Optional

6 CONCLUSIONS

The objective of the experimental part was to study the MDR1-mediated transport of

aliskiren and the related drug-drug interactions in vitro and in silico. MDR1-mediated

transport of aliskiren in vesicular transport assay showed high affinity to the transporter,

similar to what was reported previously in different assay systems. Aliskiren has been

shown to be sensitive to MDR1 inhibition in vivo by potent MDR1 inhibitor

itraconazole and the interaction in vitro was consistent. In addition, hydroxyitraconazole,

itraconazole’s active metabolite formed in the intestine, was shown to be a potent

inhibitor of MDR1-mediated transport of aliskiren in vitro. This suggests that

hydroxyitraconazole may contribute to the interaction in vivo. However, the results are

preliminary and more standardization of the test circumstances is needed. Due to time

limitations, only a simple pharmacokinetic model was tested to describe the intestinal

absorption of aliskiren. The integration of kinetic parameters (Km) from in vitro studies

requires further optimization on how to describe the intracellular drug concentrations.

Table 9. Criteria for preferred in vitro MDR1 probe substrates (FDA 2006)

32

7 REFERENCES

Azizi, M., Webb, R., Nussberger, J. & Hollenberg, N.K. 2006, "Renin inhibition with

aliskiren: where are we now, and where are we going?", Journal of hypertension,

vol. 24, no. 2, pp. 243-256.

Backman, J.T., Olkkola, K.T., Aranko, K., Himberg J.-J. & Neuvonen, P.J. 1994, "Dose

of midazolam should be reduced during diltiazem and verapamil treatments",

British journal of clinical pharmacology, vol. 37, no. 3, pp. 221-5.

Benet, L.Z., Wu, C.-Y., Hebert, M.F. & Wacher, V.J. 1996, "Intestinal drug metabolism

and antitransport processes: A potential paradigm shift in oral drug delivery",

Journal of Controlled Release, vol. 39, no. 2-3, pp. 139-143.

Cummins , C.L., Jacobsen, W. & Benet, L.Z. 2002, "Unmasking the Dynamic Interplay

between Intestinal P-glycoprotein and CYP3A4", Journal of Pharmacology and

Experimental Therapeutics, vol. 300, no. 3, pp. 1036-1045.

de Lannoy, I.A.M. & Silverman, M. 1992, "The mdr-1 gene product, P-glycoprotein,

mediated the transport of the cardoac glycoside, digoxin." Biochemical and

Biophysical Research Communications", vol. 189, pp.155-157

Drugs@FDA: FDA Approved Drug Products, Tekturna. From the Internet:

www.accessdata.fda.gov

European Medicines Agency (EMA): Draft guideline on the Investigation of Drug

Interactions, 2010.

Food and Drug Administration (FDA): Draft guidance for Industry. Drug Interaction

Studies - Study Design, Data Analysis, and Implications for Dosing and Labeling,

2006.

Jalava, K.M., Partanen, J. & Neuvonen, P.J. 1997, "Itraconazole decreases renal

clearance of digoxin",Therapeutic Drug Monitoring, vol 19., no. 6, pp. 609-613

Keogh, J.P. & Kunta, J.R. 2006, "Development, validation and utility of an in vitro

technique for assessment of potential clinical drug-drug interactions involving P-

glycoprotein", European Journal of Pharmaceutical Sciences (Netherlands),

vol.27, (5), pp.543-554, 2006, , pp. 543-554.

Kortejärvi, H., Urtti, A. & Yliperttula, M. 2007, "Pharmacokinetic simulation of

biowaiver criteria: The effects of gastric emptying, dissolution, absorption and

elimination rates", European Journal of Pharmaceutical Sciences, vol. 30, no. 2,

pp. 155-166.

33

Linnankoski, J., Mäkelä, J., Ranta, V.-P., Urtti, A. & Yliperttula, M. 2006,

"Computational Prediction of Oral Drug Absorption Based on Absorption Rate

Constants in Humans", Journal of Medicinal Chemistry, vol. 49, no. 12, pp. 3674-

3681.

Mouly, S. & Paine, M.F. 2003, "P-glycoprotein increases from proximal to distal

regions of human small intestine", Pharmaceutical research, vol. 20, no. 10, pp.

1595-1599.

Olkkola, K.T., Backman J.T. & Neuvonen, P.J. 1994, "Midazolam should be avoided in

patients receiving the systemic antimycotics ketoconazole or itraconazole",

Clinical Pharmacology & Therapeutics, vol. 55, no. 5, pp. 481-5

Partanen, J., Jalava, K.M. & Neuvonen, P.J. 1996, "Itraconazole increases serum

digoxin concentration", Pharmacology & Toxicology, vol. 79, no. 5, pp. 274-276

Quinney, S.K., Galinsky, R.E., Jiyamapa-Serna, V.A., Chen, Y., Hamman, M.A., Hall,

S.D. & Kimura, R.E. 2008, "Hydroxyitraconazole, Formed During Intestinal First-

Pass Metabolism of Itraconazole, Controls the Time Course of Heptaic CYP3A4

Inhibition and the Bioavailability of Itraconazole in Rats", Drug Metabolism and

Disposition, vol. 36, no. 6, pp.1097-1101.

Paine, M.F., Hart, H.L., Ludington, S.S., Haining, R.L., Rettie, A.E., Zeldin, D.C. 2006,

"The human intestinal cytochrome P450 "pie", Drug Metabolism and Disposition,

vol. 34, no. 5, pp.880-886.

Rautio, J., Humphreys, J.E., Webster, L.O, Balakrishnan, A., Keogh, J.P., Kunta, J.R.,

Serabjit-Singh, C.J. & Polli, J. 2006, "In vitro p-glycoprotein inhibition assays for

assessment of clinical drug interaction potential of new drug candidates: a

recommendation for probe substrates", Drug Metabolism & Disposition, vol. 34,

no. 5, pp. 786-92.

Rebello, S., Leon, S., Hariry, S., Dahlke, M. & Jarugula, V. 2010, "Effect of Verapamil

on the Pharmacokinetics of Aliskiren in Healthy Participants", Journal of Clinical

Pharmacology, vol 51, no. 2, pp. 218-228.

Rebello, S., Compain, S., Feng, A., Hariry, S., Dieterich, H.-A. & Jarugula, V. 2011,

"Effect of Cyclosporine on the Pharmacokinetics of Aliskiren in Healthy Subjects",

Journal of clinical pharmacology, vol. 51, no. 11, pp. 1549-1560.

Sarkadi, B. 1992, "Expression of the human multidrug resistance CDNA in insect cells

generates a high-activity drug-stimulated membrane ATPase", Journal of

Biological Chemistry, vol. 267, no. 7, pp. 4854-4858.

Shapiro, A.B. & Ling, V. 1997, "Extraction of Hoechst 33342 from the cytoplasmic

leaflet of the plasma membrane by P-glycoprotein", European Journal of

Biochemistry, vol. 250, no. 1, pp. 122-129.

34

Szeremy, P., Pal, A., Mehn, D., Toth, B., Fulop, F, Krajcsi, P. & Heredi-Szabo, K. 2011,

"Comparison of 3 Assay Systems Using a Common Probe Substrate, Calcein AM,

for Studying P-gp Using a Selected Set of Compounds", Journal of Biomolecular

Screening, vol. 16, no. 1, pp. 112-119.

Tang, F., Horie, K. & Borchardt, R.T. 2002, "Are MDCK Cells Transfected with the

Human MDR1 Gene a Good Model of the Human Intestinal Mucosa?,

Pharmaceutical Research, vol. 19, no. 6, pp. 765-772.

Tapaninen, T., Backman, J.T., Kurkinen, K.J., Neuvonen, P.J. & Niemi, M. 2010a,

"Itraconazole, a P-Glycoprotein and CYP3A4 Inhibitor, Markedly Raises the

Plasma Concentrations and Enhances the Renin-Inhibiting Effect of Aliskiren",

Journal of clinical pharmacology, vol. 51, no. 3, pp. 359-367.

Tapaninen, T., Neuvonen, P.J. & Niemi, M. 2010b, "Effect of ABCB1 haplotypes on

the pharmacokinetics and renin-inhibiting effect of aliskiren", European Journal of

Clinical Pharmacology, vol. 66, no. 9, p.865.

Thorn, M., Finnström, N., Lundgren, S., Rane, A. & Lööf, L. 2005, "Cytochromes P450

and MDR1 mRNA expression along the human gastrointestinal tract", British

journal of clinical pharmacology, vol. 60, no. 1, pp. 54-60.

Urbatsch, I.L., Sankaran, B., Weber, J. & Senior A.E. 1995, "P-glycoprotein is Stably

Inhibited by Vanadate-Induced Trapping of Nucleotide at a Single Catalytic Site" ,

Journal of Biological Chemistry, vol. 270, no. 33, pp. 19383-19390.

Vaidyanathan, S., Jin, Y., Schiller, H. & Jensen C. 2005, "Aliskiren, a novel renin

inhibitor, has no interaction with cytochrome P450 isoenzymes in vitro (Abstr.)",

Basic Res Pharmacology and Toxicology, vol. 97, (Suppl 1), p.230.

Vaidyanathan, S., Jermany, J., Yeh, C., Bizot, M. & Camisasca, R. 2006, "Aliskiren, a

novel orally effective renin inhibitor, exhibits similar pharmacokinetics and

pharmacodynamics in Japanese and Caucasian subjects", British journal of clinical

pharmacology, vol. 62, no. 6, pp. 690-698.

Vaidyanathan, S., Camenisch, G., Schuetz, H., Reynolds, C., Ching-Ming Yeh, Bizot,

M., Dieterich, H.A., Howard, D. & Dole, W.P. 2008, "Pharmacokinetics of the

Oral Direct Renin Inhibitor Aliskiren in Combination With' Digoxin, Atorvastatin,

and Ketoconazole in Healthy Subjects: The Role of P-Glycoprotein in the

Disposition of Aliskiren", Journal of clinical pharmacology, vol. 48, no. 11, pp.

1323-1338.

Waldmeier, F., Glaenzel, U., Wirz, B., Oberer, L., Schmid, D., Seiberling, M., Valencia,

J., Riviere, G.-J., End, P. & Vaidyanathan, S. 2007, "Absorption, distribution,

metabolism, and elimination of the direct renin inhibitor aliskiren in healthy

volunteers", Drug Metabolism and Disposition, vol. 35, no. 8, pp. 1418-1428.

35

Wang, J.S., Wen, X., Backman, J.T., Taavitsainen, P., Neuvonen, P.J. & Kivistö, K.

1999, "Midazolam alpha-hydroxylation by human liver microsomes in vitro:

Inhibition by calcium channel blockers, itraconazole and ketoconazole",

Pharmacology & toxicology, vol. 85, no. 4, pp. 157-161.

Wang, E.J., Lew, K., Casciano, C.N. & Clement, R.P. 2001, Interaction of Common

Azole Antifungals with P-glycoprotein, Antimicrobial Agents and Chemotherapy,

vol. 46, no. 1, pp. 160-165.

Weir, M.R. & Dzau, V.J. 1999, "The renin-angiotensin-aldosterone system: A specific

target for hypertension management", AMERICAN JOURNAL OF

HYPERTENSION, vol. 12, no. 12, pp. 205S-213S.

Von Moltke, L.L., Greenblatt, D.J., Duan, S.X., Harmatz, J.S. & Shader, R.I. 1998,

"Inhibition of triazolam hydroxylation by ketoconazole, itraconazole,

hydroxyitraconazole and fluconazole in-vitro", Pharmacy and Pharmacology

Communications, vol. 4, no. 9, pp. 443-445.

Wood, J.M., Maibaum, J., Rahuel, J., Grutter, M.G., Cohen, N., Rasetti, V., Ruger, H.,

Goschke, R., Stutz, S., Fuhrer, W., Schilling, W., Rigollier, P., Yamaguchi, Y.,

Cumin, F., Baum, H., Schnell, C.R., Herold, P., Mah, R., Jensen, C. & O'Brien, E.

2003, "Structure-based design of aliskiren, a novel orally effective renin inhibitor",

Biochemical & Biophysical Research Communications, vol. 308, no. 4, pp. 698.

Yu, L.X., Crison, J.R. & Amidon, G.L. 1996, "Compartmental transit and dispersion

model analysis of small intestinal transit flow in humans", International Journal of

Pharmaceutics, vol. 140 (1), pp.111-118

APPENDIX I

Actively_transported(t) = Actively_transported(t - dt) + (Active_efflux) * dt

INIT Actively_transported = 0

INFLOWS:

Active_efflux =

MDR1_1+MDR1_2+MDR1_3+MDR1_4+MDR1_5+MDR1_6+MDR1_7

AUC(t) = AUC(t - dt) + (AUC_laskuri) * dt

INIT AUC = 0

INFLOWS:

AUC_laskuri = C_plasma

Central(t) = Central(t - dt) + (True_absorption_rate - Elimination_rate) * dt

INIT Central = 0

INFLOWS:

Gut Solid drug S1 Gut Dissolv ed drug D1 Enterocy te E1

Kd1

Permeation into enterocy teP1

Portal v ein

Absorption f rom intestine A1

Kd

Activ ely transported

V2 cell

C2 cell

Stomach Solid drug Stomach Dissolv ed drug

S2

S3

S4

S5

S6

S7

Colon

D2

D3

D4

D5

D6

D7

A2

E2

E3

E4

E5

E6

E7

Kt7

A4

A3

Kt14

Kt

A5

MDR1 1

A6

MDR1 2

A7

GE

Kt1

Kt2

Kt3

Kt4

Kt5

Kt6

Kd2

Kd3

Kd4

Kd5

Kd6

Kd7

Dissolution Kd

P4

P3

P5

P6

P7

P2

MDR1 3

MDR1 4

MDR1 5

MDR1 7

MDR1 6

Transf er Kt

Kt8

Kt9

Kt10

Kt11

Kt12

Kt13

Kge

First pass liv er

Drug lost in f irst

pass metabolism

Drug transf er in portal v ein

Central

True absorption rate

Hepatic extraction ratio

Fraction av oiding f irst

pass metabolism

First pass metabolism rate

Eliminated

Elimination rate

C plasma Vd

Kel

Vmax

Activ e ef f lux

AUC

Noname 3

Passiv e transport

AUC laskuri

A solukalv o A solukalv o b

Km

C2b

C2c

C2d

C2e

C2f

C2g

Ba

V1

C1b

C1c

C1d

C1e

C1f

C1g

C1 lumen

True_absorption_rate =

Fraction_avoiding_first_pass_metabolism*Drug_transfer_in_portal_vein

OUTFLOWS:

Elimination_rate = Kel*Central

Colon(t) = Colon(t - dt) + (Kt7 + Kt14) * dt

INIT Colon = 0

INFLOWS:

Kt7 = S7*Kt

Kt14 = D7*Kt

D2(t) = D2(t - dt) + (Kd2 + Kt8 + MDR1_2 - Kt9 - P2) * dt

INIT D2 = 0

INFLOWS:

Kd2 = S2*Kd

Kt8 = Gut_Dissolved_drug_D1*Kt

MDR1_2 = (Vmax*C2b)/(Km+C2b)

OUTFLOWS:

Kt9 = D2*Kt

P2 = A_solukalvo*0.00451*2*(C1b-C2b)

D3(t) = D3(t - dt) + (Kd3 + MDR1_3 + Kt9 - P3 - Kt10) * dt

INIT D3 = 0

INFLOWS:

Kd3 = S3*Kd

MDR1_3 = (Vmax*C2c)/(Km+C2c)

Kt9 = D2*Kt

OUTFLOWS:

P3 = A_solukalvo*0.00451*2*(C1c-C2c)

Kt10 = D3*Kt

D4(t) = D4(t - dt) + (Kd4 + MDR1_4 + Kt10 - P4 - Kt11) * dt

INIT D4 = 0

INFLOWS:

Kd4 = S4*Kd

MDR1_4 = (Vmax*C2d)/(Km+C2d)

Kt10 = D3*Kt

OUTFLOWS:

P4 = A_solukalvo*0.00451*2*(C1d-C2d)

Kt11 = D4*Kt

D5(t) = D5(t - dt) + (Kd5 + MDR1_5 + Kt11 - P5 - Kt12) * dt

INIT D5 = 0

INFLOWS:

Kd5 = S5*Kd

MDR1_5 = (Vmax*C2e)/(Km+C2e)

Kt11 = D4*Kt

OUTFLOWS:

P5 = A_solukalvo*0.00451*2*(C1e-C2e)

Kt12 = D5*Kt

D6(t) = D6(t - dt) + (Kd6 + MDR1_6 + Kt12 - P6 - Kt13) * dt

INIT D6 = 0

INFLOWS:

Kd6 = S6*Kd

MDR1_6 = (Vmax*C2f)/(Km+C2f)

Kt12 = D5*Kt

OUTFLOWS:

P6 = A_solukalvo*0.00451*2*(C1f-C2f)

Kt13 = D6*Kt

D7(t) = D7(t - dt) + (MDR1_7 + Kd7 + Kt13 - Kt14 - P7) * dt

INIT D7 = 0

INFLOWS:

MDR1_7 = (Vmax*C2g)/(Km+C2g)

Kd7 = S7*Kd

Kt13 = D6*Kt

OUTFLOWS:

Kt14 = D7*Kt

P7 = A_solukalvo*0.00451*2*(C1g-C2g)

Drug_lost_in_first_pass_metabolism(t) = Drug_lost_in_first_pass_metabolism(t - dt) +

(First_pass_metabolism_rate) * dt

INIT Drug_lost_in_first_pass_metabolism = 0

INFLOWS:

First_pass_metabolism_rate = Hepatic_extraction_ratio*Drug_transfer_in_portal_vein

E2(t) = E2(t - dt) + (P2 - A2 - MDR1_2) * dt

INIT E2 = 0

INFLOWS:

P2 = A_solukalvo*0.00451*2*(C1b-C2b)

OUTFLOWS:

A2 = A_solukalvo_b*0.00451*2*C2b

MDR1_2 = (Vmax*C2b)/(Km+C2b)

E3(t) = E3(t - dt) + (P3 - A3 - MDR1_3) * dt

INIT E3 = 0

INFLOWS:

P3 = A_solukalvo*0.00451*2*(C1c-C2c)

OUTFLOWS:

A3 = A_solukalvo_b*0.00451*2*C2c

MDR1_3 = (Vmax*C2c)/(Km+C2c)

E4(t) = E4(t - dt) + (P4 - A4 - MDR1_4) * dt

INIT E4 = 0

INFLOWS:

P4 = A_solukalvo*0.00451*2*(C1d-C2d)

OUTFLOWS:

A4 = A_solukalvo_b*0.00451*2*C2d

MDR1_4 = (Vmax*C2d)/(Km+C2d)

E5(t) = E5(t - dt) + (P5 - A5 - MDR1_5) * dt

INIT E5 = 0

INFLOWS:

P5 = A_solukalvo*0.00451*2*(C1e-C2e)

OUTFLOWS:

A5 = A_solukalvo_b*0.00451*2*C2e

MDR1_5 = (Vmax*C2e)/(Km+C2e)

E6(t) = E6(t - dt) + (P6 - A6 - MDR1_6) * dt

INIT E6 = 0

INFLOWS:

P6 = A_solukalvo*0.00451*2*(C1f-C2f)

OUTFLOWS:

A6 = A_solukalvo_b*0.00451*2*C2f

MDR1_6 = (Vmax*C2f)/(Km+C2f)

E7(t) = E7(t - dt) + (P7 - A7 - MDR1_7) * dt

INIT E7 = 0

INFLOWS:

P7 = A_solukalvo*0.00451*2*(C1g-C2g)

OUTFLOWS:

A7 = A_solukalvo_b*0.00451*2*C2g

MDR1_7 = (Vmax*C2g)/(Km+C2g)

Eliminated(t) = Eliminated(t - dt) + (Elimination_rate) * dt

INIT Eliminated = 0

INFLOWS:

Elimination_rate = Kel*Central

Enterocyte_E1(t) = Enterocyte_E1(t - dt) + (Permeation_into_enterocyteP1 -

Absorption_from_intestine_A1 - MDR1_1) * dt

INIT Enterocyte_E1 = 0

INFLOWS:

Permeation_into_enterocyteP1 = A_solukalvo*0.00451*2*(C1_lumen-C2_cell)

OUTFLOWS:

Absorption_from_intestine_A1 = A_solukalvo_b*0.00451*2*C2_cell

MDR1_1 = (Vmax*C2_cell)/(Km+C2_cell)

First_pass_liver(t) = First_pass_liver(t - dt) + (Drug_transfer_in_portal_vein -

True_absorption_rate - First_pass_metabolism_rate) * dt

INIT First_pass_liver = 0

INFLOWS:

Drug_transfer_in_portal_vein =

A2+A3+A4+A5+A6+A7+Absorption_from_intestine_A1

OUTFLOWS:

True_absorption_rate =

Fraction_avoiding_first_pass_metabolism*Drug_transfer_in_portal_vein

First_pass_metabolism_rate = Hepatic_extraction_ratio*Drug_transfer_in_portal_vein

Gut_Dissolved_drug_D1(t) = Gut_Dissolved_drug_D1(t - dt) + (Kd1 + Transfer_Kt +

MDR1_1 - Kt8 - Permeation_into_enterocyteP1) * dt

INIT Gut_Dissolved_drug_D1 = 0

INFLOWS:

Kd1 = Gut_Solid_drug_S1*Kd

Transfer_Kt = Stomach_Dissolved_drug*Kge

MDR1_1 = (Vmax*C2_cell)/(Km+C2_cell)

OUTFLOWS:

Kt8 = Gut_Dissolved_drug_D1*Kt

Permeation_into_enterocyteP1 = A_solukalvo*0.00451*2*(C1_lumen-C2_cell)

Gut_Solid_drug_S1(t) = Gut_Solid_drug_S1(t - dt) + (GE - Kd1 - Kt1) * dt

INIT Gut_Solid_drug_S1 = 0

INFLOWS:

GE = 4250

OUTFLOWS:

Kd1 = Gut_Solid_drug_S1*Kd

Kt1 = Gut_Solid_drug_S1*Kt

Noname_3(t) = Noname_3(t - dt) + (Passive_transport) * dt

INIT Noname_3 = 0

INFLOWS:

Passive_transport = P2+P3+P4+P5+P6+P7+Permeation_into_enterocyteP1

Portal_vein(t) = Portal_vein(t - dt) + (Absorption_from_intestine_A1 + A2 + A3 + A4 +

A5 + A6 + A7 - Drug_transfer_in_portal_vein) * dt

INIT Portal_vein = 0

INFLOWS:

Absorption_from_intestine_A1 = A_solukalvo_b*0.00451*2*C2_cell

A2 = A_solukalvo_b*0.00451*2*C2b

A3 = A_solukalvo_b*0.00451*2*C2c

A4 = A_solukalvo_b*0.00451*2*C2d

A5 = A_solukalvo_b*0.00451*2*C2e

A6 = A_solukalvo_b*0.00451*2*C2f

A7 = A_solukalvo_b*0.00451*2*C2g

OUTFLOWS:

Drug_transfer_in_portal_vein =

A2+A3+A4+A5+A6+A7+Absorption_from_intestine_A1

S2(t) = S2(t - dt) + (Kt1 - Kt2 - Kd2) * dt

INIT S2 = 0

INFLOWS:

Kt1 = Gut_Solid_drug_S1*Kt

OUTFLOWS:

Kt2 = S2*Kt

Kd2 = S2*Kd

S3(t) = S3(t - dt) + (Kt2 - Kt3 - Kd3) * dt

INIT S3 = 0

INFLOWS:

Kt2 = S2*Kt

OUTFLOWS:

Kt3 = S3*Kt

Kd3 = S3*Kd

S4(t) = S4(t - dt) + (Kt3 - Kt4 - Kd4) * dt

INIT S4 = 0

INFLOWS:

Kt3 = S3*Kt

OUTFLOWS:

Kt4 = S4*Kt

Kd4 = S4*Kd

S5(t) = S5(t - dt) + (Kt4 - Kt5 - Kd5) * dt

INIT S5 = 0

INFLOWS:

Kt4 = S4*Kt

OUTFLOWS:

Kt5 = S5*Kt

Kd5 = S5*Kd

S6(t) = S6(t - dt) + (Kt5 - Kt6 - Kd6) * dt

INIT S6 = 0

INFLOWS:

Kt5 = S5*Kt

OUTFLOWS:

Kt6 = S6*Kt

Kd6 = S6*Kd

S7(t) = S7(t - dt) + (Kt6 - Kd7 - Kt7) * dt

INIT S7 = 0

INFLOWS:

Kt6 = S6*Kt

OUTFLOWS:

Kd7 = S7*Kd

Kt7 = S7*Kt

Stomach_Dissolved_drug(t) = Stomach_Dissolved_drug(t - dt) + (Dissolution_Kd -

Transfer_Kt) * dt

INIT Stomach_Dissolved_drug = 0

INFLOWS:

Dissolution_Kd = Stomach_Solid_drug*Kd

OUTFLOWS:

Transfer_Kt = Stomach_Dissolved_drug*Kge

Stomach_Solid_drug(t) = Stomach_Solid_drug(t - dt) + (- GE - Dissolution_Kd) * dt

INIT Stomach_Solid_drug = 300000

OUTFLOWS:

GE = 4250

Dissolution_Kd = Stomach_Solid_drug*Kd

A_solukalvo = 2857

A_solukalvo_b = 28.57

Ba = Central/300000

C_plasma = Central/Vd

C1_lumen = Gut_Dissolved_drug_D1/V1

C1b = D2/V1

C1c = D3/V1

C1d = D4/V1

C1e = D5/V1

C1f = D6/V1

C1g = D7/V1

C2_cell = Enterocyte_E1/V2_cell

C2b = E2/V2_cell

C2c = E3/V2_cell

C2d = E4/V2_cell

C2e = E5/V2_cell

C2f = E6/V2_cell

C2g = E7/V2_cell

Fraction_avoiding_first_pass_metabolism = 1-Hepatic_extraction_ratio

Hepatic_extraction_ratio = 0.10

Kd = 0.0317

Kel = (4.873*10^-4)

Kge = 0.0583

Km = 2.79

Kt = 0.035

V1 = 35.7

V2_cell = 2.86

Vd = 135000

Vmax = 50000