Introduction

New drug discovery and development is becoming an increasingly risky and costly endeavor. A recent report has tagged the final price of bringing a drug to the market at greater than a billion US dollars with an estimated research time running into multiple years (2004). Despite the considerable investment in terms of finance and resources, the number of drug approvals per year have held steady for the last few years. The advent of combinatorial chemistry, automation, and high-throughput screening (HTS) has afforded the opportunity to test thousands of compounds, but the success rate of progressing from initial clinical testing to final approval has remained disappointingly low. Greater than 90% of the compounds entering Phase-I clinical testing fail to reach the patients and as high as 50% entering Phase-III do not make the cut (Kola and Landis, 2004).

Historically, drug discovery adopted a linear design; the new chemical entities were first selected on the basis of their pharmacological activity/potency followed by their sequential profiling to assess the absorption, distribution, metabolism, elimination, and toxicity (ADMET) characteristics. Such a strategy was generally more time and resource intensive and left little room for errors during the discovery process. Today, the new drug design effort integrates a parallel matrix approach where the pharmacological efficacy is screened in parallel with ADMET profiling, providing information in a timely manner to maximize the chance for selecting superior drug candidates with better quality for further development. Therefore, the availability of highly accurate, low cost and HTS techniques that can provide fast and reliable data on the developability characteristics of drug candidates is crucial. Screening a large number of drug candidates for biopharmaceutical properties (e.g., solubility, intestinal permeability, CYP inhibition, metabolic stability, and more recently drug-drug interaction potential involving drug transporters) has become a major challenge. Determination of permeability property

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Figure 5.1. Multiple pathways for intestinal absorption of a compound. (1) passive, transcellular (2) active or secondary active, (3) facilitated diffusion, (4) passive, para-cellular, (5) absorption limited by P-gp and/or other efflux transporters, (6) intestinal first-pass metabolism followed by absorption of parent and metabolite, (7) receptor mediated transport and the drug-transporter interaction of drug candidates is fast becoming key characterization studies performed during the lead selection and lead optimization.

Drug absorption across the intestinal membrane is a complex multipathway process as shown in Fig. 5.1. Passive absorption occurs most commonly through the cell membrane of enterocytes (transcellular route) or via the tight junctions between the enterocytes (paracellular route). Carrier-mediated absorption occurs via an active (or secondary active process) or by facilitated diffusion. Various efflux transporters such as P-gp, BCRP, MRP2 are also functional that could limit the absorption. intestinal enzymes could be involved in metabolizing drugs to alternate moieties that might be absorbed. Finally, receptor mediated endocytosis could also play a role. Because of the multivariate processes involved in intestinal absorption of drugs, it is often difficult to use a single model to accurately predict the in vivo permeability characteristics.

Currently, a variety of experimental models are available when evaluating intestinal permeability of drug candidates (Hillgren et al., 1995; Balimane et al., 2000, 2006; Hidalgo, 2001). A few commonly used models include: in vitro methods; artificial lipid membrane such as parallel artificial membrane permeability assay (PAMPA); cell-based systems such as Caco-2 cells, Mardin-Darby canine kidney (MDCK) cells, etc.; tissue-based Ussing chamber; in situ methods, intestinal single pass perfusion, and in vivo methods, whole animal absorption studies. Typically, a combination of these models is used routinely in assessing intestinal permeability. A tiered approach is often used, which involves high-throughput (but less predictive) 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.

Adequate permeability is required not only for oral absorption but also for sufficient drug distribution to pharmacological target organs (e.g., tumor, liver, etc.). 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. P-gp is one of the most extensively studied transporters that have been unequivocally known to impact the ADMET characteristics of drug molecules (Kim et al., 1999; Polli et al., 1999; Lin, 2003; Lin and Yamazaki, 2003). It's role in influencing the pharmacokinetics of anti-cancer drugs has been extensively reviewed (Krishna and Mayer, 2000). It is a ubiquitous transporter, which is present on the apical surface of the enterocytes, canalicular membrane of hepatocytes, and on the apical surface of kidney, placenta and endothelial cells of brain membrane. Because of its strategic location, it is widely recognized that P-gp is a major determinant in disposition of a wide array of drugs in humans. The oral bioavailability of fexofenadine increased significantly when erythromycin or ketoconazole (well known inhibitor of P-gp) was co-administered in humans, suggesting P-gp as a permeability barrier at the absorption site (Simpson and Jarvis, 2000). Similarly, P-gp at the blood-brain barrier limits the entry of drugs into the brain. The biliary elimination of vincristine decreased significantly in the presence of verapamil (a known P-gp substrate/inhibitor) (Watanabe et al., 1992). Therefore, the early screening of drug candidates for their potential to interact with P-gp (either as a substrate or inhibitor) is becoming necessary and critical. There are various in vitro and in vivo models used for assessing P-gp interaction (Adachi et al., 2001; Polli et al., 2001; Yamazaki et al., 2001; Perloff et al., 2003). In vitro assays such as ATPase activity, rhodamine-123 uptake, calcein AM uptake, cell-based bidirectional transport, radio-ligand binding along with in vivo models such as transgenic (knockout mice) animals are often used to assess the involvement of P-gp. The cell-based bidirectional permeability assay is the most popular method for identification of P-gp substrate in drug discovery labs (Polli et al., 2001). This cell model provides the right balance of adequate throughput and functional utility. However, there are certain caveats that the user must be aware of in order to maximize the utility of the assay. In addition to P-gp, other pharmaceutically important drug transporters (e.g., MRP2, BCRP, OATP, OAT, OCT, etc.) can be examined using a plethora of models (e.g., transfected cell, vesicles, recombinant vaccinia, xenopus oocytes, etc.). A detailed discussion of these models is beyond the scope of this book chapter.

This book chapter will focus on the various techniques that are currently used by drug discovery scientists in evaluating permeability/absorption and P-gp interaction potential of drug candidates. In particular, two experimental models (PAMPA and Caco-2 cells) will be discussed in detail with special emphasis on their complimentary aspects. PAMPA is used as the primary screening tool, and it is capable of providing the structure-permeability relationship that enables a successful lead optimization. Caco-2 cell model is often used as the secondary tool to perform in-depth mechanistic studies, to delineate the various pathways of absorption and to assess the P-gp interaction potential of drug candidates.

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