161

10 PERMEABILITY AND TRANSPORTER MODELS IN DRUG DISCOVERY AND DEVELOPMENT

Praveen V. Balimane , Yong - Hae Han , and Saeho Chong

10.1 INTRODUCTION

The path to successful drug discovery and development in a pharmaceutical company is a very long and tortuous one, fraught with uncertainty and risks, and demanding massive resources and cost. A recent report has pegged the fi nal price tag of bringing a molecule from lab to market at higher than a billion dollars, with an esti-mated research time running into multiple years [1] . Despite the considerable investment in terms of fi nance and resources, the number of drug approvals per year have held steady or decreased for the last few years. The success rate of progressing from initial clinical testing to fi nal approval has remained disappointingly low, with less than 10% of the compounds entering Phase I clini-cal testing eventually reaching the patients [2] . Efforts to increase the success rate of drug discovery and devel-opment have led to an industry - wide adoption of the parallel matrix approach, where pharmacological prop-erties (i.e., potency and effi cacy) are screened in parallel with absorption, distribution, metabolism, excretion, and toxicity (ADMET) profi ling (i.e., developability) to maximize the ability to select superior drug candidates with the best chances of making it to market. The avail-ability of highly accurate, low - cost, and high - throughput screening ( HTS ) techniques that can provide fast and reliable data on the developability characteristics of drug candidates is crucial for the new strategy to succeed.

Screening discovery compounds for their biophar-maceutical properties (e.g., solubility, intestinal perme-ability, cytochrome P450 [CYP] inhibition, metabolic sta bility, and more recently, drug – drug interaction [DDI] potential involving drug transporters) has become a critical step that can make or break the fortune of a company. When defi ning a preferred absorption, metabolism, distribution, and excretion (ADME) space, fast and reliable determination of the permeability/absorption properties and drug – transporter interaction potentials of drug candidates is quickly becoming the key characterization study performed during lead selec-tion and lead optimization.

Currently, a variety of experimental models is avail-able for evaluating the intestinal permeability and transporter interaction potential of drug candidates [3, 4] . The most popular models for assessing permeability/absorption include in vitro methods (an artifi cial lipid membrane such as is used in a parallel artifi cial mem-brane permeability assay [ PAMPA ], cell - based systems such as Caco - 2 cells, Mardin – Darby canine kidney [ MDCK ] cells, etc., the tissue - based Ussing chamber); in situ methods (intestinal single - pass perfusion); and in vivo methods (whole - animal absorption studies). Models to investigate transporter interaction potential (also referred to as transporter phenotyping) include in vitro methods (intact cells such as hepatocytes, transient and stable transfected cells, insect vector (sf9) vesicles,

ADME-Enabling Technologies in Drug Design and Development, First Edition. Edited by Donglu Zhang and Sekhar Surapaneni.© 2012 John Wiley & Sons, Inc. Published 2012 by John Wiley & Sons, Inc.

162 PERMEABILITY AND TRANSPORTER MODELS IN DRUG DISCOVERY AND DEVELOPMENT

Xenopus oocytes); ex vivo methods (organ slices and perfusions); and in vivo methods (transgenic knockout animal models, etc.).

10.2 PERMEABILITY MODELS

Despite tremendous innovations in drug delivery methods in the last few decades, the oral route still remains as the most preferred route of administration for most new chemical entities ( NCE s). The oral route is preferred by virtue of its convenience, low cost, and high patient compliance compared with alternative routes. However, compounds intended for oral admin-istration must have adequate aqueous solubility and intestinal permeability in order to achieve therapeutic concentrations. With the explosive growth in the fi eld of genomics and combinatorial chemistry, coupled with technological innovations in the last few years, synthe-sizing a large number of potential drug candidates is no longer a bottleneck in the drug discovery process. Instead, the task of screening compounds simultane-ously for biological activity and biopharmaceutical properties (e.g., solubility, permeability/absorption, sta-bility) has become the major challenge. This has pro-vided a great impetus within the pharmaceutical industry to implement appropriate screening models that are high capacity, cost - effective, and highly predictive of in vivo permeability and absorption. Typically, a combina-tion of models is used synergistically in assessing intes-tinal permeability. A tiered approach is the most popular design, which involves high - throughput (but less predic-tive) models for primary screening followed by low - throughput (but more predictive) models for secondary screening and mechanistic studies. PAMPA and cell culture - based models offer the right balance between predictability and throughput, and currently enjoy wide popularity throughout the pharmaceutical industry.

10.2.1 PAMPA

The PAMPA model was fi rst introduced in 1998 [5] , and since then numerous reports have been published illus-trating the general applicability of this model as a high - throughput permeability screening tool. The model consists of a hydrophobic fi lter material coated with a mixture of lecithin/phospholipids dissolved in an inert organic solvent such as dodecane, creating an artifi cial lipid membrane barrier that mimics the intestinal epi-thelium. The rate of permeation across the membrane barrier was shown to correlate well with the extent of drug absorption in humans. The use of 96 - well microti-ter plates coupled with rapid analysis using a spectro-photometric plate reader makes this system a very

attractive model for screening a large number of com-pounds and libraries. PAMPA is much less labor - intensive than cell culture methods, but it appears to show similar predictability. One of the main limitations of this model is that PAMPA underestimates the absorp-tion of compounds that are actively absorbed via drug transporters. Despite this limitation, PAMPA serves as an invaluable primary permeability screen during the early drug discovery process because of its high through-put capability. Lately there have been signifi cant improvements to the model to accommodate its broader use at the discovery stage (stable PAMPA plates for long - term usage, pH adaptability, specialized plates for estimating permeability into various target organs — brain, liver, etc.) [6] .

10.2.2 Cell Models ( C aco - 2 Cells)

Varieties of cell monolayer models that mimic in vivo intestinal epithelium in humans have been developed and currently enjoy widespread popularity. Unlike enterocytes, human immortalized (tumor) cells grow rapidly into confl uent monolayers followed by a spon-taneous differentiation, providing an ideal system for transport studies. A few of these cell models that are most commonly used are Caco - 2, MDCK, LLC - PK1, and HT - 29.

The Caco - 2 cell model has been the most popular and most extensively characterized cell - based model in examining the permeability of drugs in both the phar-maceutical industries and academia. Caco - 2 cells, a human colon adenocarcinoma, undergo spontaneous enterocytic differentiation in culture and become polar-ized cells with well - established tight junctions, resem-bling intestinal epithelium in humans. It has also been demonstrated that the permeability of drugs across Caco - 2 cell monolayers correlated very well with the extent of oral absorption in humans. In the last 10 – 15 years, Caco - 2 cells have been widely used as an in vitro tool for evaluating the permeability of discovery com-pounds and for conducting in - depth mechanistic studies [3, 7] (Figure 10.1 ).

10.2.3 P - glycoprotein ( P gp) Models

Adequate permeability is required not only for oral absorption but also for suffi cient drug distribution to pharmacological target organs (e.g., tumor, liver). In addition to simple passive diffusion across lipid bilayers, numerous transporters appear to play a critical role in selective accumulation and distribution of drugs into target organs. Pgp is one of the most extensively studied transporters that have been unequivocally known to impact the ADMET characteristics of drug molecules.

TRANSPORTER MODELS 163

It is a ubiquitous transporter, which is present on the apical surface of the enterocytes, canalicular membrane of hepatocytes, and the apical surface of kidney, pla-centa, and endothelial cells of brain membrane. Because of its strategic location, it is widely recognized that Pgp is a major determinant in disposition of a wide array of drugs in humans. The oral bioavailability of fexofena-dine increased signifi cantly when erythromycin or ketoconazole (a well - known inhibitor of Pgp) was coad-ministered in humans, suggesting Pgp as a permeability barrier at the absorption site. Similarly, Pgp at the blood – brain barrier limits the entry of drugs into the brain. The biliary elimination of vincristine decreased signifi cantly in the presence of verapamil (a known Pgp substrate/inhibitor). Therefore, the early screening of drug candidates for their potential to interact with Pgp (either as a substrate or inhibitor) is becoming neces-sary and critical. There are various in vitro and in vivo models used for assessing Pgp interaction [8] . In vitro assays such as ATPase activity [9] , rhodamine - 123 uptake [10] , calcein AM uptake [11] , cell - based bidirec-tional transport, and radioligand binding along with in vivo models such as transgenic (knockout mice) animals [12] are often used to assess the involvement of Pgp. The cell - based bidirectional permeability assay is the most popular method for identifi cation of Pgp substrate in drug discovery labs [3, 8] . This cell model provides the right balance of adequate throughput and functional utility (Figure 10.2 ).

10.3 TRANSPORTER MODELS

Lately it has been realized that in addition to CYPs (which control the metabolism of compounds and thus its disposition), transporter proteins expressed in several key absorption and elimination organs (liver, kidney, intestine, brain, etc.) can also play a leading role in dic-tating the disposition of drugs. There is a plethora of these transporter proteins that are broadly classifi ed into the ATP - binding cassette (ABC) transporter family (involved in effl ux transport) and the solute carrier (SLC) transporter family (involved in infl ux transport). The ones that have demonstrated unequivocal clinical signifi cance are the ones that have strategic expression at inlet and outlet locations in key organs and generally have broad substrate specifi city. Some prominent ones in each family are as follows: ABC family = Pgp, breast cancer resistance protein (BCRP), and multi-drug resistance protein 2 (MRP2); SLC family = organic anion-transporting polypeptides (OATPs), organic cation transporter (OCT), and organic anion transporter (OAT) [13] . Study of transporters is becoming exceed-ingly important because they have the potential to infl u-ence the ADME properties of drugs, they can signifi cantly impact the safety and toxicity profi les of drugs (via accu-mulation in target organs), they can lead to clinical DDIs [14] , and they also help explain clinical variability due to polymorphisms [15] . Additionally, there are increasing market and regulatory pressures that are also

FIGURE 10.1. Correlation between permeability and % absorption in humans of ∼ 25 marketed compounds.

Permeability (nm/s)

1 10 100 1000

Abs

orpt

ion

in H

uman

s (%

)

0

20

40

60

80

100

120

PAMPA Caco-2 cells

164 PERMEABILITY AND TRANSPORTER MODELS IN DRUG DISCOVERY AND DEVELOPMENT

10.3.1 Intact Cells

Using fresh hepatocytes to model hepatic transport pro-cesses in humans and preclinical species is fast being recognized as a reliable fi rst - line assessment method [20] . Since fresh hepatocytes are equipped with all hepatic transporters as well as Phase I and Phase II enzymes, the hepatocyte system provides an appropri-ate model for evaluating transporter - and enzyme - mediated hepatic clearance [21] . Generally, the uptake into the hepatocytes is measured in suspension by a centrifugation method using oil - layered tubes to sepa-rate hepatocytes from the incubation medium. Alterna-tively, the assay can be run in semi - high throughput fashion with plated hepatocytes (in 24 - and 96 - well plates). Hepatocytes are also sometimes used in primary culture mode after growing for several days. However, there are scientifi c limitations inherent to this confi gura-tion, such as the decrease in functionality of uptake transporters (e.g., OATPs) as well as Phase I and Phase II enzyme activities during culture. Recently, cryopre-served hepatocytes have become popular in a drug dis-covery environment, and several laboratories have shown that transporters and CYP activities can be main-tained in rat, dog, cynomolgus monkey, and human cryopreserved hepatocytes [21] . Due to the obvious advantages of cryopreserved hepatocytes (availability, resource consistency, etc.), the use of cryopreserved hepatocytes is likely to increase in the future.

encouraging companies to integrate transporter inter-action models earlier during compound profi ling para-digms [16] . Most companies are beginning to apply coordinated transporter interaction screening strategies beginning in the discovery stage and carrying on up to the late development stage to help anticipate interac-tions, design clinical studies, provide guidance on label-ing, and help manage the interactions in the clinic. There are a plethora of in vitro and in vivo models for trans-porter interaction studies that are discussed extensively in several review articles [17 – 19] . Listed below are the most popular methodologies that are utilized in dis-covery and development for transporter interactions (Table 10.1 ).

FIGURE 10.2. Bidirectional effl ux (B to A/A to B) ratio of classical Pgp substrates in Caco - 2 cells (mannitol and metoprolol are used as negative controls). * = signifi cantly different.

Man

nitol

Saquin

avir

Vincris

tine

Digoxin

Vinblas

tine

Indin

avir

Taxol

Met

opro

lol

Per

mea

bilit

y (n

m/s

)

0

100

200

300

400

500A to B B to A

*

*

*

**

*

TABLE 10.1. Major Drug Transporters in Key Target Organs

Uptake/SLC Type Effl ux/ABC Type

Liver OATP1B1/1B3/2B1, OCT1, OAT2

MRP2, Pgp, BCRP, BSEP

Kidney OAT1/3, OCT2/3, OCTN1/2, MATE1/2, PEPT1/2

MRP2/4, Pgp

Intestine OATPs, PEPT1 MRP1/2/3, Pgp, BCRP

Brain OAT3, OCT2, OATP1A2 Pgp, MRPs, BCRP

TRANSPORTER MODELS 165

into the cytoplasm of the cells [22] . This leads to the overexpression of the single transporter at the oocyte plasma membrane layer, thus providing a suitable model for transporter studies. To evaluate transporter - mediated uptake into oocytes, water - injected oocytes are used as a reference, and the uptake amounts are compared between water - and transporter cRNA - injected oocytes. Many models for major uptake transporters (OATPs, OATs, OCTs, etc.) in Xenopus oocytes are commercially available from various vendors. However, extreme care should be taken while performing such studies because oocytes are very fragile and can lead to higher variabil-ity than other models.

10.3.4 Membrane Vesicles

Membrane vesicles prepared from a variety of intact tissues have been used for several decades to assess the transporter mechanism in major tissues such as liver, kidney, and intestinal tissue [23] . The blood side of cell membranes (liver - sinusoidal, kidney, and intestine - basolateral) and lumenal side of cell membranes (liver - bile canalicular, the intestine, and kidney - brush border) can be prepared separately by a series of centrifugations and/or precipitations with metal ions (e.g., Ca2 + ). Mem-brane vesicles prepared from intact tissues express mul-tiple transporters, thus the observed transport can be attributed to the mixed roles of different transporters. Therefore, the use of membrane vesicles prepared from the cells overexpressing single transporter cells provide us with unequivocal information supporting our under-standing of transport mechanisms. Various cells such as Sf9, HEK - 293, MDCK, and LLC - PK1 cells are com-monly used as host cells to prepare vesicles that are transfected with ABC transporters (MRPs, Pgp, BCRP, BSEP, etc.) for mechanistic studies [18] . Since mem-brane vesicles do not contain metabolic enzymes, the

10.3.2 Transfected Cells

Wild - type cell lines such as Caco - 2, MDCK, and LLC - PK1 are popular tools for mechanistic transporter studies but suffer from a major drawback in that they express signifi cant levels of several different transport-ers (Papt1, Pgp, BCRP, MRPs, etc.) that make delinea-tion of the role of individual transporters almost impossible [18] . To overcome this issue, transfected cell lines have been developed that are essentially engi-neered cells overexpressing a single transporter of inter-est and thus maximizing the role of a single transporter in a particular study. The molecular - level process involves incorporation of the transporter cDNA into the naive mock cell line leading to the enhanced protein expression of the single transporter in the cells. Once DNAs are stably transfected in cell lines, the cell lines maintain transporter activity over subsequent passages. The most widely utilized cell lines for stable transfection are COS - 7, CHO, HEK - 293, and MDCK cells since they express low levels of endogenous transporter proteins. Many stable cell lines for the uptake and effl ux trans-porters are successfully established, and their functional characterizations are well documented in the literature. Although development of stably transfected cells is a time - consuming and labor - intensive process, the stably transfected cells generally offer advantages in cost, data variation, and analytical fl exibility, as compared with other transporter models (Figure 10.3 ). Therefore, stably transfected cells are very attractive transporter phenotyping tools.

10.3.3 Xenopus Oocyte

Drug transporters can be transiently expressed in imma-ture eggs (oocytes) from the South African clawed frog, Xenopus laevis , by injecting the cRNA of transporters

FIGURE 10.3. (A) Uptake of estradiol - 17 β - D - glucuronide (E - glu, 1 μ M) into stably transfected OATP1B1 or mock/HEK - 293 cells. (B) Uptake of 1 - methyl - 4 - phenylpyridinium (MPP + , 1 μ M) into Xenopus oocytes injected with OCT1 cRNA or water. (C) Uptake of estradiol - 17 β - D - glucuronide (E - glu, 1 μ M) into MRP - expressing membrane vesicles in the presence of 5 mM AMP or ATP.

OATP1B1 Cells

0

2

4

6

8

10

12

14

Mock OCTP1B1

E-g

lu U

ptak

e (p

mol

/mg)

OCT1 Oocytes

0

1

2

3

Water OCT1

MP

P+

Upt

ake

(pm

ol/o

ocyt

e/h)

MRP2 Vesicles

0

50

100

150

200

250

300

AMP ATP

E-g

lu U

ptak

e (µ

L/ng

)

(A) (B) (C)

166 PERMEABILITY AND TRANSPORTER MODELS IN DRUG DISCOVERY AND DEVELOPMENT

vitro and in vivo models. For the discovery process to be effi cient and eventually fi nancially rewarding for the companies, the screening models need to be extremely high throughput and inexpensive at the early stage (where one deals with thousands of compounds) and more mechanistic and predictive at the later stages (where one deals with only a few leads). The process of selecting the right compounds to progress through the discovery stage to development and fi nally to navigate to market hinges on utilizing the “ right models ” at the “ right time ” to understand the benefi t/liability ratio of a compound and making a decision for the next step.

The “ ideal strategy ” for compound selection would involve the use of a combination of in vitro models that are high throughput (but less predictive) with in vivo models that are low throughput (but more predictive) to effectively evaluate the intestinal permeability and transport characteristics of a large number of drug can-didates during the lead selection and lead optimization processes. PAMPA and Caco - 2 cells are the most fre-quently utilized in vitro models to assess intestinal per-meability. The popularity of these models stems from their potential for high throughput, cost - effectiveness, and adequate predictability of absorption potential in humans (Table 10.2 ). However, several caveats associ-ated with these models, such as poor predictability for transporter - mediated and paracellularly absorbed com-pounds, signifi cant nonspecifi c binding to cells/devices leading to poor recovery, and variability associated with experimental factors, need to be considered carefully to realize their full potential. Transporter interaction studies with Pgp, the most well - studied and pharmaceu-tically relevant transporter, forms the next layer of pro-fi ling to ensure that Pgp transporter - mediated DDIs would not be a clinical issue. Assays such as ATPase, inhibition assays, and the bidirectional assay in cell models form the mainstay for Pgp studies. The investiga-tive studies for interaction with other transporters are often performed based on critical information gener-ated by other functional areas (chemistry, biology, preclincal in drug metabolism and pharmacokinetics [DMPK], etc.). OATPs and effl ux transporters are studied if the liver is the target organ (effi cacy or toxic-ity) or if a compound (or its metabolites) is eliminated via biliary excretion. OATs and OCTs are studied if the kidney is the target organ, or drug elimination is primar-ily via urinary excretion. Effl ux transporters are studied if the target is the central nervous system or tumors. Both infl ux and effl ux intestinal transporters are studied to investigate nonlinear PK as well as to make other preclinical PK observations of interest.

A typical transporter interaction study involves iden-tifi cation of specifi c drug transporter(s) involved in the disposition of test compounds using one or more of the

model presents a signifi cant advantage over other models (cell based or in vivo ) when dealing with meta-bolically labile compounds. Recently, assay methods with membrane vesicles have been greatly improved, and a study can be performed in a high - throughput setting by using 96 - well plates and cell harvesting devices [18] . However, the nonspecifi c binding to mem-brane fi lters can often be a signifi cant technical issue, especially for lipophilic compounds (Table 10.2 ).

10.3.5 Transgenic Animal Models

Although many in vitro transporter assay tools have been developed so far, the prediction often lacks an in vitro – in vivo bridge. Transgenic animal models are genetically engineered animals that have undergone a targeted gene mutation (gene knockout) leading to a complete absence of a selected transporter protein. Par-allel studies in a wild type (that expresses all transport-ers) along with knockout (where one targeted transporter has been deleted) provides an attractive in vivo model to tease out the role of transporter proteins. Knockout mice models of various transporters have been estab-lished to date, and their usefulness has been demon-strated for Mdr1a, Mdr1b, Mdr1a/1b, Mrp1, Mrp2, Mrp4, Bcrp, Bsep, and so on [24 – 26] .. Knockout mice for SLC transporters have also been established and character-ized functionally: Oct1, Oct2, Oct3, Octn2, Oat1, Oat3, Pept1, Pept2, and so on [24, 27, 28] .

10.4 INTEGRATED PERMEABILITY – TRANSPORTER SCREENING STRATEGY

Drug discovery and development is an endeavor that is both resource heavy as well as extremely time sensitive. In various stages of the discovery cycle, compounds are selected via profi ling their properties through several in

TABLE 10.2. Comparison of Popular Transporter Models

Cell Lines Membrane

Vesicles Xenopus Oocytes

Availability Limited Commercial Commercial Cost Inexpensive Expensive Expensive Labeled

compound requirement

Preferred Yes Preferred

Throughput Low High Low Nonspecifi c

binding Negligible Signifi cant Negligible

Quality of data

High Medium Low

REFERENCES 167

6. Faller B ( 2008 ) Artifi cial membrane assays to assess per-meability . Curr Drug Metab 9 ( 9 ): 886 – 892 .

7. Artursson P , Karlsson J ( 1991 ) Correlation between oral drug absorption in humans and apparent drug permeabil-ity coeffi cients in human intestinal epithelial (Caco - 2) cells . Biochem Biophys Res Commun 175 ( 3 ): 880 – 885 .

8. Polli JW , et al. ( 2001 ) Rational use of in vitro P - glycoprotein assays in drug discovery . J Pharmacol Exp Ther 299 ( 2 ): 620 – 628 .

9. Hrycyna CA , et al. ( 1998 ) Mechanism of action of human P - glycoprotein ATPase activity. Photochemical cleavage during a catalytic transition state using orthovanadate reveals cross - talk between the two ATP sites . J Biol Chem 273 ( 27 ): 16631 – 16634 .

10. Feller N , et al. ( 1995 ) Functional detection of MDR1/P170 and MRP/P190 - mediated multidrug resistance in tumour cells by fl ow cytometry . Br J Cancer 72 ( 3 ): 543 – 549 .

11. Hollo Z , et al. ( 1994 ) Calcein accumulation as a fl uoro-metric functional assay of the multidrug transporter . Biochim Biophys Acta 1191 ( 2 ): 384 – 388 .

12. Wijnholds J , et al. ( 1997 ) Increased sensitivity to antican-cer drugs and decreased infl ammatory response in mice lacking the multidrug resistance - associated protein . Nat Med 3 ( 11 ): 1275 – 1279 .

13. Shitara Y , Horie T , Sugiyama Y ( 2006 ) Transporters as a determinant of drug clearance and tissue distribution . Eur J Pharm Sci 27 ( 5 ): 425 – 446 .

14. Lin JH ( 2007 ) Transporter - mediated drug interactions: Clinical implications and in vitro assessment . Expert Opin Drug Metab Toxicol 3 ( 1 ): 81 – 92 .

15. Ieiri I , Higuchi S , Sugiyama Y ( 2009 ) Genetic polymor-phisms of uptake (OATP1B1, 1B3) and effl ux (MRP2, BCRP) transporters: Implications for inter - individual dif-ferences in the pharmacokinetics and pharmacodynamics

models discussed earlier in this chapter. The objective of transporter interaction studies is to provide unequiv-ocal evidence that the test compound interacts with specifi c transporter(s) so that we may anticipate such an interaction at the clinical level. Transporter phenotyping studies are performed at the preclinical stage, and the results are often incorporated in designing appropriate clinical studies to determine the extent of interaction in humans. These specialized clinical DDI studies play a critical role in devising an effective strategy in managing transporter - mediated DDIs in the clinic and thus making the approved drugs safer (Figure 10.4 ).

REFERENCES

1. FDA ( 2004 ) Challenges and opportunities on the critical path to new medical products . In FDA Report . Rockville, MD : Food and Drug Administration .

2. Kola I , Landis J ( 2004 ) Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov 3 ( 8 ): 711 – 715 .

3. Balimane PV , Han YH , Chong S ( 2006 ) Current industrial practices of assessing permeability and P - glycoprotein interaction . AAPS J 8 ( 1 ): E1 – 13 .

4. Kerns EH , et al. ( 2004 ) Combined application of parallel artifi cial membrane permeability assay and Caco - 2 per-meability assays in drug discovery . J Pharm Sci 93 ( 6 ): 1440 – 1453 .

5. Kansy M , Senner F , Gubernator K ( 1998 ) Physicochemical high throughput screening: Parallel artifi cial membrane permeation assay in the description of passive absorption processes . J Med Chem 41 ( 7 ): 1007 – 1010 .

FIGURE 10.4. Typical screening paradigm incorporating permeability and transporter assays in various stages of discovery and development cycle.

Permeability models Transporter models

In silico tools (PAMPA, Caco-2, Pgp)

PAMPA(dual pH)

Caco-2 (bi-direc onal)

Pgp

Intact cells andhepatocytes

Transfectedcells, oocytes,sf9 vesicles,

Transgenic animals

Physico-chemicalprofiling P

inhibi onetc.

DISCOVERY ASSAYS

DEVELOPMENT ASSAYS

168 PERMEABILITY AND TRANSPORTER MODELS IN DRUG DISCOVERY AND DEVELOPMENT

of statins and other clinically relevant drugs . Expert Opin Drug Metab Toxicol 5 ( 7 ): 703 – 729 .

16. Giacomini KM , et al. ( 2010 ) Membrane transporters in drug development . Nat Rev Drug Discov 9 ( 3 ): 215 – 236 .

17. Oswald S , et al. ( 2007 ) Transporter - mediated uptake into cellular compartments . Xenobiotica 37 ( 10 – 11 ): 1171 – 1195 .

18. Sahi J ( 2005 ) Use of in vitro transporter assays to under-stand hepatic and renal disposition of new drug candi-dates . Expert Opin Drug Metab Toxicol 1 ( 3 ): 409 – 427 .

19. Kitamura S , Maeda K , Sugiyama Y ( 2008 ) Recent pro-gresses in the experimental methods and evaluation strat-egies of transporter functions for the prediction of the pharmacokinetics in humans . Naunyn Schmiedebergs Arch Pharmacol 377 ( 4 – 6 ): 617 – 628 .

20. Hewitt NJ , et al. ( 2007 ) Primary hepatocytes: Current understanding of the regulation of metabolic enzymes and transporter proteins, and pharmaceutical practice for the use of hepatocytes in metabolism, enzyme induction, transporter, clearance, and hepatotoxicity studies . Drug Metab Rev 39 ( 1 ): 159 – 234 .

21. Houle R , et al. ( 2003 ) Retention of transporter activities in cryopreserved, isolated rat hepatocytes . Drug Metab Dispos 31 ( 4 ): 447 – 451 .

22. Pritchard JB , Miller DS ( 2005 ) Expression systems for cloned xenobiotic transporters . Toxicol Appl Pharmacol 204 ( 3 ): 256 – 262 .

23. Ruetz S , et al. ( 1987 ) Isolation and characterization of the putative canalicular bile salt transport system of rat liver . J Biol Chem 262 ( 23 ): 11324 – 11330 .

24. Glaeser H , Fromm MF ( 2008 ) Animal models and intes-tinal drug transport . Expert Opin Drug Metab Toxicol 4 ( 4 ): 347 – 361 .

25. Vlaming ML , Lagas JS , Schinkel AH ( 2009 ) Physiological and pharmacological roles of ABCG2 (BCRP): Recent fi ndings in Abcg2 knockout mice . Adv Drug Deliv Rev 61 ( 1 ): 14 – 25 .

26. Xia CQ , Milton MN , Gan LS ( 2007 ) Evaluation of drug - transporter interactions using in vitro and in vivo models . Curr Drug Metab 8 ( 4 ): 341 – 363 .

27. Ahn SY , et al. ( 2009 ) Interaction of organic cations with organic anion transporters . J Biol Chem 284 ( 45 ): 31422 – 31430 .

28. Ocheltree SM , et al. ( 2005 ) Role and relevance of peptide transporter 2 (PEPT2) in the kidney and choroid plexus: In vivo studies with glycylsarcosine in wild - type and PEPT2 knockout mice . J Pharmacol Exp Ther 315 ( 1 ): 240 – 247 .