Review
The road map to oral
bioavailability: an industrial
perspective
2. Solubilit y
V Hayden T homas, Shobha Bhattachar, Linda Hitchingham, Philip Zocharski,
Maryanne Naath, Narayanan Surendran, Chad L Stoner & Ayman El-Kattan†
3. Permeabilit y
2800 Plymouth Road, Ann Arbor, MI 48105, USA
1. Int roduct ion
Pfizer Global Research and Development, Department of Pharmacokinetics, Dynamics and Metabolism,
4. M et abolism
5. Conclusion
6. Expert opinion
Opt imisat ion of oral bioavailabilit y is a cont inuing challenge f or t he pharmaceut ical and biot echnology indust ries. The number of pot ent ial drug candidat es requiring in vivo evaluat ion has signif icant ly increased w it h t he advent
of combinat orial chemist ry. In addit ion, drug discovery programmes are
increasingly f orced int o more lipophilic and low er solubilit y chemical space.
To aid in t he use of in vit ro and in silico t ools as w ell as reduce t he number of
in vivo st udies required, a t eam-based discussion t ool is proposed t hat provides a ‘road map’ t o guide t he select ion of prof iling assays t hat should be
considered w hen opt imising oral bioavailabilit y. This road map divides t he
f act ors t hat cont ribut e t o poor oral bioavailabilit y int o t w o int errelat ed cat egories: absorpt ion and met abolism. This road map provides an int erf ace f or
cross discipline discussions and a syst emat ic approach t o t he experiment at ion
t hat drives t he drug discovery process t ow ards a common goal – accept able
oral bioavailabilit y using minimal resources in an accept able t ime f rame.
Keywords: absorption, ADME optimisation, bioavailability, distribution, drug discovery,
elimination, metabolism, pharmacokinetics, solubility
Expert Opin. Drug Metab. Toxicol. (2006) 2(4):591-608
1.
For reprint orders,
please contact:
[email protected]
Introduction
Discovering novel therapeutic agents is an increasingly time-consuming and costly
process. Most estimates indicate that it takes ∼ 10 – 15 years and > $800 million to
discover and develop a successful drug product [1]. During the past decade, the pharmaceutical industry used parallel medicinal chemistry and high-throughput screening (HT S) approaches in drug discovery programmes [2]. T his approach enabled the
creation of millions of compounds that were screened against hundreds of potential
targets with a common goal of discovering chemical matter with high affinity for the
intended pharmacological target. One of the major limitations to this approach is
that the newly discovered leads tend to have high molecular weight and lipophilicity
with low aqueous solubility, resulting in new chemical entities (NCEs) that are usually associated with poor oral bioavailability [3]. It is well established in the literature
that poor oral bioavailability is one of the leading causes of compound failure in preclinical and clinical development [4]. Compounds with poor oral bioavailability tend
to have low plasma exposure and high interindividual variability, which would limit
their therapeutic usefulness.
To improve the oral plasma exposure of a leading candidate and increase the
probability of a successful development, its physicochemical properties and pharmacological activity should be optimised in parallel. However, the cost and time
required to screen all newly synthesised compounds in relevant assays are prohibitive. T herefore, the current approach is to perform selective biopharmaceutical and
pharmacokinetic ‘spot checks’ on these leading compounds to funnel information
10.1517/17425255.2.4.591 © 2006 Informa UK Ltd ISSN 1742-5255
591
The road map to oral bioavailability: an industrial perspective
Rat F%
≥ 30%
Manageable
risk
< 30%
Lipinski RO5 compliant
PSA ≤ 140 Å2
GI chemical stability
No
Physicochemical
SAR
Yes
Absorption or
metabolism
Absorption
Metabolism
Permeability
Solubility
Figure 1. Entry into the road map w ith the initial evaluation of a compound series. Compounds w ith poor oral bioavailability in
rat are evaluated against a subset of physicochemical properties prior to entering the main body of the road map.
GI: Gastrointestinal; PSA: Polar surface area; RO5: Rule of 5; SAR: Structure–activity relationship.
into rapid optimisation loops based on structure–activity relationship (SAR) screens [5]. Assays developed to fit this
approach have advanced considerably over the past few years
in the areas of kinetic solubility, metabolism screens and
plate-based permeability assays [6,7]. T hese assays, in conjunction with improvements in predictive software for pKa, logP
and polar surface area (PSA), and other relevant physicochemical parameters, provide a useful semiquantitative guide
to discovery scientists during lead optimisation [3,4,8]. T his
multiparameter optimisation generates a great deal of data
requiring clear interpretation and a firm understanding of the
various pharmacokinetic issues involved. T his is often a
multifaceted challenge that tends to slow down drug discovery
and development timelines due to misdirected attempts at
solving incorrectly identified problems. Hence, it is pivotal
that the discovery team visualises and interprets the data in a
manner that will enable the next round of compound design
and synthesis [9]. T he task of resolving challenging pharmacokinetic behaviours with respect to oral bioavailability
becomes less troublesome if broken down into manageable
modules of experimentation.
T his article provides discovery teams with a ‘road map’ of
experimentation that determines the most probable causes of
poor oral bioavailability, when optimising a chemical series
and ultimately selecting lead compounds for preclinical development. T his systematic approach divides the potential factors leading to the compound’s (template’s) low oral
bioavailability into two interrelated categories: absorption
(product of solubility and permeability) and metabolism. In
each category, moderate- to high-throughput assays are used
to rapidly evaluate various attributes of a chemical series with
592
two possible outcomes to each assay: a manageable risk where
a discovery team proceeds to the next assay, or high risk where
SAR and troubleshooting is warranted to overcome the liablity that is contributing to the limited oral bioavailability of
the chemical series.
Using this approach to identify key properties that contribute
to the poor oral bioavailability of a chemical series will decrease
discovery cycle time and cost required in the optimisation of a
chemical series. In addition, it will play a key role in the
selection of drugable candidates for preclinical development.
T his road map was developed as a result of an extensive
literature review. It should be noted that corporate business
practices and technological resources are anticipated to vary
depending on project focus and individual business models.
As the road map described in this paper is based on fundamental aspects of physicochemical and pharmacokinetic concepts, similar systematic approaches may be developed based
on the proposed model to assist discovery teams.
Initial evaluation
T here are many parallel activities taking place in the mid to
late phases of the drug discovery cycle to bring an NCE into
full preclinical development. T hese include chemical scalability, biopharmaceutical characterisation and pharmacokinetic/pharmacodynamic profiling [10]. T hese studies are
focused on entering preclinical development in the shortest
time frame possible, giving little consideration to potential
development hurdles. Given the high cost and lengthy time
frame for drug development, it is pivotal to achieve a minimally acceptable oral bioavailability standard for selecting
compounds prior to moving forward. In discovery projects,
1.1
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
Thomas, Bhattachar, Hitchingham, Zocharski, Naath, Surendran, Stoner & El-Kattan
10,000
Log solubility (µg/ml)
2100
520
1000
207
52
100
100
21
10
10
5
1
1
0.1
0.1 high 0.1 avg 0.1 low 1.0 high 1.0 avg 1.0 low 10 high 10 avg
Ka
Ka
Ka
Ka
Ka
Ka
Ka
Ka
10 low
Ka
Projected dose in mg/kg
Figure 2. The predicted solubility required for a compound series to achieve a minimally acceptable oral absorption. Bars
show the minimum solubility in µg/ml (absolute values are denoted above the bar) for low, medium and high permeability (Ka – apparent
absorption rate) at three projected clinical doses (0.1, 1 and 10 mg/kg, denoted by bar colour).
M odified w ith permission from Lipinsky CA. In Pharmaceutical Profiling in Drug Discovery for Lead Selection . Borchardt RT, Kerns EH, Lipinski CA, Thakker DR, Wang B,
(Eds), Arlington, VA: American Association of Pharmaceutical Scientists (2004):95, Copyright 2004, American Association of Pharmaceutical Scientists [13,20].
oral bioavailability is usually first assessed in rats as they are
readily available. Moreover, pharmacokinetic parameters
obtained in rat can be commonly scaled to human, providing
a basis for rational compound selection [11]. A minimal
acceptable oral bioavailability of 30% has been established for
a typical oral programme [12-14]. T his minimum threshold will
help the team to achieve an early proof of concept. If this criterion is not achieved during preliminary in vivo rat testing,
the impact on drugability must be determined by conducting
key studies on compounds in the selected chemical series.
Once representative compounds have been evaluated and a
chemical series has been shown to exhibit low oral bioavailability, the project team may use this road map to determine
the physicochemical and/or pharmacokinetic parameters that
contribute to the poor oral bioavailability and optimise them
accordingly (Figure 1 ).
For candidates with < 30% oral bioavailability in rat, the
first assessment is to ensure that it meets desirable physicochemical properties, such as the Lipinski’s rule of 5 (RO5),
PSA < 140 Å2 , and acceptable chemical stability in the dosing
vehicle and various simulated gastrointestinal conditions
(Figure 1 ). Failure of the candidate to meet one of these simple
descriptors would trigger the discovery team to execute specific studies to determine their potential impact on the candidate oral absorption. For example, PSA is a parameter, which
is defined as the area occupied by nitrogen and oxygen atoms
and the hydrogen atoms attached to these heteroatoms [15].
T his descriptor is widely used to assess compound absorption
potential. Veber et al. [14] have shown that compounds with a
PSA ≤ 140 Å2 will have a high probability of good oral
absorption in the rat. T herefore, a compound exhibiting a
PSA value > 140 Å2 would require an assessment for its
permeability potential, possibly using the Caco-2 cell line to
determine if its intestinal permeability is limited by its PSA.
Furthermore, if the candidate meets RO5 and standard
physicochemical requirements, it would undergo a parallel
evaluation in each of the discussion tool’s two interrelated
categories: absorption and metabolism.
Absorption
Absorption is a dynamic process of drug transfer from the site
of administration, the gastrointestinal lumen, across the intestinal epithelium and into portal blood. Taking the simplest
approach, oral drug absorption can be expressed using Fick’s
First Law applied to membranes [16]:
1.2
(1)
J wall = P wall ⋅ C int
where J wall is the drug flux across a homogeneous intestinal
membrane, Pwall is the effective permeability, which is the rate
that dissolved drug will cross the intestinal wall to reach the
portal blood circulation, and C int is the drug concentration in
the luminal fluid. T herefore, drug flux is a product of drug
permeability and solubility [17].
A qualitative understanding of permeability, solubility and
their impact on drug absorption is essential in achieving
acceptable oral bioavailability. A proper balance must be
established between these two parameters during early SAR
optimisation, while still considering other factors such as
dose and drug stability in the intestinal medium, which can
significantly impact oral absorption.
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
593
The road map to oral bioavailability: an industrial perspective
HTS
solubility
(kinetic)
≥ 60 µg/ml
high
solubility at
pH 6.5
< 60 µg/ml
low
solubility at
pH 6.5
High order
≥ 250˚C
Consider
permeability
and
metabolism tree
Solubiity
(thermodynamic)
≥ 60 µg/ml
Assess
crystal lattice energy
(melting point)
Low to mild order
< 250˚C
Yes
Yes
LogP
≤ 3.5
No
No
Consider crystal
packing/H-bonding
(computations)
LogP
SAR optimisation
to improve solubility
Team discussion – consider other
factors affect solubility including
dissolution, media, kinetics,
pKa, dose, etc.
Figure 3. Solubility section of the road map. This section of the road map should be used to as a guide to determine w hich of the
main solubility related factors are resulting in low aqueous solubility and thus poor oral bioavailability.
HTS: High-throughput screening; SAR: Structure–activity relationship.
2.
Solubility
As shown with Equation 1, the prerequisite for good oral drug
absorption is ensuring a sufficient compound amount is in
solution at the primary site of absorption. Various approaches
are available to measure compound aqueous solubility. In general, the different types of solubility measurements may be classified into thermodynamic and kinetic solubility methods [3].
T hermodynamic solubility is defined as the equilibrium concentration of a compound that is saturated in a given solvent.
T hermodynamic solubility is dependent on many variables
such as compound crystal lattice, temperature and pressure [18].
On the other hand, kinetic solubility is a measurement of
compound solubility where it is predissolved in an organic
solvent (typically dimethyl sulfoxide) then titrated with aqueous medium over a period of time until the compound precipitates [19]. Kinetic solubility determination is the preferred
method at the discovery stage as it is more amenable to HTS,
requiring virtually no equilibration time. However, the main
594
disadvantage of this approach is the lack of consideration for
any crystal lattice effects as shown with thermodynamic solubility measurements [20]. It should be stressed that both thermodynamic and kinetic solubility are generally measured in a
phosphate-based buffer (pH range: 6.5 – 7) as this medium is
considered to be a surrogate for intestinal pH.
Determining the minimum solubility necessary to achieve
adequate oral absorption is dependent on the compound projected human dose and permeability [13,20]. Lipinski depicted
this relationship graphically, as shown in Figure 2 , which
serves as a quick reference guide to determine the minimum
level of solubility that is needed by a compound to have reasonable absorption in human. For example, given a compound series with a projected human dose of ∼ 1 mg/kg and
average permeability, assessed using the apparent absorption
rate (Ka), an aqueous solubility of ≥ 52 µg/ml would be
needed to ensure that oral bioavailability is not solubility limited. In actual practice, discovery teams routinely target a
kinetic solubility > 60 µg/ml (pH 6.5) when developing a
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
Thomas, Bhattachar, Hitchingham, Zocharski, Naath, Surendran, Stoner & El-Kattan
O
Kow is the octanol–water partition coefficient of the compound. T his equation clearly demonstrates that decreasing
lipophilicity by one logP unit or decreasing melting point by
100°C will increase compound aqueous solubility by
∼ 10-fold. Even though this equation cannot be used to estimate the solubility for all compounds, specifically ionisable
molecules, it demonstrates the importance of considering these
pivotal factors when optimising compound aqueous solubility.
O
O
O
N
N
HN
N
O
O
O
O
Thalidomide
N-methyl-thalidomide
Crystal lattice energy and solubility
A compound that can assemble into a highly ordered crystal
tends to have a higher melting point and lower aqueous solubility [22]. T his highly ordered crystal lattice primarily originates from two types of strong cohesive interactions:
i) intermolecular hydrogen bonding and/or ii) short-ranged
dispersion forces. T hese cohesive interactions are most noted
in compounds that contain one or more of the following
properties: high number of hydrogen-bond acceptor
(HBA)/donor (HBD) groups, planar or inflexible conformation or a high degree of symmetry [23]. All of these factors promote tight packing within the crystal lattice that is not readily
solubilised by aqueous media. In general, a compound with a
high melting point (> 250°C) will have poor thermodynamic
solubility, requiring a discovery team to develop an SAR to
reduce its crystal lattice energy (Figure 3 ). T his approach was
taken by Goosen et al. when evaluating the effect of structural
modification on the physicochemical properties of thalidomide, which has an aqueous solubility of 52 µg/ml and a
melting point of 275°C [24]. T halidomide’s poor aqueous
solubility is attributed to an acidic imido hydrogen on the
glutarimide ring, which is responsible for the strong hydrogen
and dipolar bonding in the crystalline state. When this group
was replaced with an alkyl group, the highly ordered crystal
lattice was disrupted (Figure 4 ). As a result, N -methyl thalidomide has an aqueous solubility of 276 µg/ml and 159°C melting point [24]. PNQX had desirable in vitro and in vivo
activity; however, it suffered from low solubility (Figure 5 ). In
an effort to improve its physicochemical properties and
potency, Nikam et al. synthesised a novel ring-opened analogue series to reduce packing efficiency in the crystal lattice,
which significantly increased aqueous solubility [25].
2.1
Figure 4. N-alkylation of thalidomide disrupts the highly
ordered crystal lattice, improving solubility by more than
fourfold.
O
OH
N
N
O2N
H
N
O
N
H
O
PNQX
(pH 7.4, solubility: 8.6 µg/ml)
O2N
H
N
O
N
H
O
Nonplanar analogue PNQX
(pH 7.4, solubility: 420 µg/ml)
Figure 5. PNQX ring opening and out-of-plane substitution
results in a reduced crystal lattice energy and hence higher
aqueous solubility.
compound series, as this solubility value is expected to lead to
reasonable absorption provided that the compound has
average permeability and dose (Figure 3 ).
In the case where a compound series has a kinetic solubility
< 60 µg/ml (pH 6.5) and low oral bioavailability, aqueous
solubility could be the rate-limiting factor in achieving
acceptable compound oral plasma exposure. T herefore, the
discovery team should determine the main factors that are
contributing to the compound low aqueous solubility and
thus poor oral bioavailability. In general, these factors are
demonstrated in the general solubility equation developed by
Jain et al. (Equation 2) [21]:
(2)
solid
log S W
= 0.5 – 0.01 ( MP – 25 ) – log K ow
where SW solid is the molar aqueous solubility, MP is the
melting point (widely used to assess crystal lattice energy), and
M odulating lipophilicity for improved
compound solubility
A more commonly encountered reason for poor aqueous solubility than that of a highly ordered crystal lattice is lipophilicity. LogP is a widely accepted measure of lipophilicity, and
compounds demonstrating a clogP > 3.5 generally have poor
aqueous solubility [19], and should warrant a logP SAR optimisation to improve oral absorption (Figure 3 ). In general,
decreasing lipophilicity will improve solvation potential by
increasing solvent–solute interactions in aqueous media. A
common approach to the reduction of lipophilicity is through
the introduction of ionisable or polar groups. T his approach
was considered in the development of indinavir (Figure 6 ),
2.2
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
595
The road map to oral bioavailability: an industrial perspective
Ionisable
centre
N
O
OH
O
OH
OH
H
N
HN
OH
N
H
N
N
O
N
H
O
O
L-685,434
Indinavir
Figure 6. Solubilisation SAR w here an ionisable basic amine group w as substituted into the backbone of L-685,434 to
increase aqueous solubility.
SAR: Structure–activity relationship.
Table 1. Example of functional group addition.
Dimethylaminoethyl group added to
6-amino-seco-cyclopropylindole compound to improve solubility
5
6
Cl
R
7
N
H
N
O
NH2
R
Solubility (µg/ ml)
5,6,7-triOCH3
13
5-OCH3
8
5-O(CH2)2N(CH3)2
290
5-OM e, 6-O(CH2)2N(CH3)2
> 500
where an ionisable basic amine (and a pyridine) group were
incorporated into the hydroxyl ethylene backbone of
L-685,434 (logP 5.36), reducing the logP by 2.5 units and
notably increasing aqueous solubility [26]. In another example,
Milbank et al. decreased lipophilicity in a series of
6-amino-seco-cyclopropylindole compounds, by incorporating a dimethylaminoethyl group at the 5- or 6-position on the
ring, which significantly increased its aqueous solubility
(Table 1 ) [27].
When oral absorption is solubility limited in a series that
has a clogP < 3.5 and a low to mid order crystal lattice, little
can be gained by reducing lipophilicity without adversely
affecting intestinal permeability. As a general rule of thumb, a
logP value of 2 – 3 provides a good balance with respect to
solubility and permeability [5]. In this case, the discovery team
must carefully consider the contributions of other solubility
596
associated factors, including compound polarity, ionisation,
and so on, to improve solubility (Figure 3 ).
Solubility associated factors limiting
oral absorption
A compound series can have sufficient solubility (thermodynamic, ≥ 60 µg/ml) and still have limited oral absorption due
to solubility related physicochemical factors, such as dissolution
kinetics in biorelevant media, pKa, and so on [28-31]. Therefore,
the discovery team should consider these factors when optimising a chemical series (Figure 3 ). For example, a slight shift in
pKa, decreasing acidic and increasing basic, can improve a compound series’ solubility in physiologically relevant conditions. As
seen with Jiang et al. in optimising a series of phosphodiesterase
type 5 inhibitors, they demonstrated the effect of shifting a basic
pKa from 4.4 to 5, and thereby increasing rat oral bioavailability
from 12 to 38% [32]. Other factors such as dissolution rate can
limit oral absorption of a compound series, with moderate solubility. The most common approach to confirm dissolution-limited oral absorption is through particle size reduction [33].
Discovery teams can use a mathematical model, microscopic
mass balance approach, developed by Oh et al. to determine
what particle size would be necessary to achieve an acceptable
oral absorption [34]. Particle size reduction was shown to significantly increase the dissolution rate of phenytoin and improve its
oral absorption in humans [35]. Another example of particle size
reduction to increase dissolution rate was in the dosing of a
danazol nanoparticulate dispersion, which improved the oral
bioavailability in dogs [36].
2.3
3.
Permeability
Various routes exist by which administered drugs can cross the
intestinal membrane. In general, the main routes are by passive
diffusion or active transport (Figure 7 ). Passive diffusion is the
most common mechanism of absorption across the intestinal
membrane and is divided into two pathways: the paracellular
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
Thomas, Bhattachar, Hitchingham, Zocharski, Naath, Surendran, Stoner & El-Kattan
Passive diffusion
Apical (gut)
Transcellular
Paracellular
Active transport
Influx
Efflux
Enterocytes
Basolateral (blood)
Figure 7. Primary mechanisms of intestine permeability.
Passive diffusion can be paracellular or transcellular and active
transport can be influx or efflux.
pathway, in which drug diffuses through the aqueous pores at
the tight junctions between the intestinal enterocytes; and the
transcellular (lipophilic) pathway, which requires drug diffusion across the lipid cell membrane of the intestinal enterocyte.
T he active transport pathway is mediated by transporters and
is divided into active drug influx and efflux. T he relevance of
each route is determined by the compound’s physicochemical
properties and its potential affinity for transport proteins, as
will be discussed in the following sections. T herefore, it is
pivotal to investigate and determine the major absorption
pathways when optimising oral drug absorption.
In paracellular diffusion, drug molecules can cross the
intestinal enterocytes through the water-filled pores between
these cells [37]. In general, drugs that are absorbed through this
pathway are quite small molecules (e.g., molecular weight
[MW] < 250 Da) and hydrophilic in nature (logP < 0).
Because the junctional complex has a net negative charge,
positively charged molecules pass more readily, whereas negatively charged molecules are repelled [38]. It is interesting to
note that the paracellular pathway offers a limited window for
absorption as the tight junctions between cells become tighter
travelling from the jejunum towards the colon [39]. T he paracellular pathway of absorption is a minor pathway due to the
tight junctions and small surface area, which accounts for
∼ 0.01% of the total surface area of intestinal membrane [40].
T herefore, compounds with paracellular absorption have
dose- and regional-dependent absorption, as seen with cimetidine [41]. It is, therefore, preferred to design compounds
without a significant paracellular component.
On the other hand, the transcellular pathway is the major
route of absorption of compounds absorbed. The passive transcellular transport starts with the penetration of apical membrane, followed by diffusion through the cytoplasm. Finally, the
drug molecule exits through the basolateral membrane into the
portal blood [42]. In general, the rate of passive transcellular
permeability is mainly determined by the rate of transport
across the apical cell membrane, which is controlled by the
physicochemical properties of the absorbed compound. According to solubility diffusion model, pH partition theory and RO5,
compounds that are absorbed through the transcellular pathway
are unionised, with reasonable lipophilicity and molecular
weight (logP > 0 and MW > 300 Da, respectively). In addition,
the hydrogen-bonding capacity determined by the number of
HBAs and HBDs is < 10 and 5, respectively [3,8].
A large number of influx transporters are expressed by the
small intestinal mucosa and play a major role in the absorption
of nutrients and vitamins. In addition, these influx transporters mediate the absorption of some drugs and xenobiotics.
T here are several reviews that discussed the involvement of
these transporters in intestinal drug absorption [42,43]. Examples of these transporters are di-/tripeptides (PEPT 1), large
neutral amino acids (system L), bile acids, nucleosides and
monocarboxylic acid transporters. In general, compounds that
are substrates for these influx transporters exhibit intestinal
absorption higher than expected from their diffusion across
intestinal cell membranes. For example, PEPT 1, which is
expressed predominantly, but not exclusively, in the small
intestine, is a well-characterised influx transporter with many
substrates, such as angiotensin-converting enzyme inhibitors,
β-lactam antibiotics (both cephalosporins and penicillins),
PD-158473 and renin inhibitors [43,44]. Discovery teams
commonly use PEPT 1 as a promising strategy for oral drug
delivery due to its broad substrate specificity.
Unlike absorption influx transporters, efflux transporters
function as an absorptive barrier that limits oral bioavailability
of many drugs and xenobiotics. T hese transporters belong to
the AT P-binding cassette superfamily of transporters and are
expressed at the apical surface of the small intestine enterocytes. T hey include P-glycoprotein (P-gp), breast cancer
resistance protein (BCRP), multi-drug resistance-associated
protein (MRP) and organic ion transporters [42,45,46]. P-gp,
the best-characterised member of the apical efflux transporters, is a product of the multi-drug resistance (MDR1) gene.
Different research groups have shown P-gp to limit the intestinal absorption of a large number of drugs such as digoxin,
talinolol, UK-343,664 and ciclosporin, to name a few [47-49].
Several research groups are beginning to establish a better
understanding in P-gp substrate recognition [50-54]. In an
interesting study, Didziapetris et al. established a rule of four
to predict P-gp substrate interaction. T his rule is roughly
determined by the following factors: i) compound’s size
expressed through molecular weight; ii) number of HBA; and
iii) extent of ionisation determined by the acid/base pKa values. In general, compounds with HBA > 8, MW > 400 Da,
and acid pKa > 4 are likely to be P-gp substrates. On the other
hand, compounds with HBA < 4, MW < 400 Da and base
pKa < 8 are not likely to be P-gp substrates [51].
3.1 Using Caco-2 cell-based assay to classify
compound permeability
A variety of in silico, in situ, in vivo and in vitro models are
available for the assessment of intestinal drug permeability [55].
However, in vitro models using Caco-2 cells are the most commonly used techniques, as it is amenable to HTS [56]. For
passively absorbed compounds, several reports demonstrated a
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
597
The road map to oral bioavailability: an industrial perspective
Permeability
Yes
Caco-2
≥ 1 x 10-6 cm/s
Acceptable permeability
and no evidence of efflux
or paracellular pathway
Consider
solubility and
metabolism tree
No
No
Yes
Evidence of high efflux
or paracellular pathway
Have discussion
with team regarding
the impact of low
Caco-2 results.
Consider Caco-2
SAR
No
Spot check
MDCK/MDR1
BA/AB results
≥ 2.5
Not a P-gp
substrate
Have discussion
with team to
consider other efflux
transporters
Yes
P-gp
substrate
P-gp SAR
optimisation
Consider
solubility and
metabolism tree
Figure 8. Permeability section of the road map. Once a compound series is determined to have Caco-2 permeability < 1 x 10 -6 cm/s,
steps should be taken to determine if paracellular or active efflux is playing a significant role and seek to eliminate this potential liability
through structural modifications.
AB: Apical to basal; BA: Basal to apical; M DCK: M adin–Darby Canine Kidney; M DR: M ulti-drug resistance; P-gp: P-glycoprotein; SAR: Structure–activity relationship.
good correlation between Caco-2 permeability and the oral
fraction absorbed in humans [57-60]. Caco-2 cells also have
active transport mechanisms similar to those present in the
human intestine [61]. T here are a few factors that limit the use
of the Caco-2 cell line, such as a long culture time (21 days) to
reach confluence and the reported underexpression of
metabolic enzymes as compared with levels observed in human
small intestine [56,62]. Caco-2 is also not a good model for the
assessment of paracellular absorption due to the tight junctions
between the cells as shown by the high transepithelial
resistance (∼ 400 Ω cm2) compared with human intestine
(∼ 60 – 120 Ω cm2) [63]. Even considering these relevant
points, Caco-2 has been proven valuable as a model to project
human absorption and to answer mechanistic questions
regarding intestinal permeability. It should be emphasised that
other institutions may use other tools to assess passive permeability such as Parallel Artificial Membrane Permeability Assay
or Mardin–Darby Canine Kidney cell line [52].
598
As shown in Figure 8 , if a chemical series has a Caco-2 permeability rate > 1 x 10 -6 cm/s, then a moderate to high
absorption (Fa = 30 – 100%) in human is predicted [60]. In
this case, other factors in the road map, solubility and/or
metabolism, should be evaluated for their role in limiting oral
bioavailability of the series. If a compound has a Caco-2 permeability < 1 x 10 -6 cm/s, human absorption is predicted to
be permeability limited (Fa = 0 – 30%). Factors affecting
intestinal permeability should be considered, including
paracellular absorption and significant efflux.
To increase passive transcellular permeability and reduce
paracellular permeability contribution to the total absorption
of a compound, three common approaches are taken:
i) increase compound molecular weight and lipophilicity, if
below the optimum range (MW ∼ 300 – 400 Da and logP
∼ 2 – 3); ii) reduce hydrogen-bond functionality by decreasing the number of HBDs or HBAs; and/or iii) reduce net
ionisation in the physiological pH range 5.5 – 7.0. Examples
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
Thomas, Bhattachar, Hitchingham, Zocharski, Naath, Surendran, Stoner & El-Kattan
highlighting these approaches are common in the literature
and here only a few are noted. A popular way to effectively
increase lipophilicity, while maintaining target potency, is
through bioisosteric replacement of hydrophilic core groups.
Lin et al. demonstrated this approach in optimising a series of
very late antigen-4 antagonists, by replacing the anilide core
with benzoxazole. T his resulted in an ∼ 30-fold net increase in
rat oral bioavailability without compromising target potency
[64]. In another interesting study, Walker et al. demonstrated
the importance of hydrogen-bond functionality with a series
of endothelin antagonists. Earlier compounds in this series
had poor intestinal absorption due in part to a high number
of HBDs and HBAs, and by effectively reducing the number
of these groups permeability significantly improved, which
was seen in Caco-2 cells [65]. Another approach to reducing
hydrogen-bond functionality is through the promotion of
intramolecular hydrogen bonding. T his technique reduces a
compound’s polar group interaction with water, as hydrogen
bonding is internally satisfied. For example, sildenafil, which
does not meet RO5 criteria, still has a good oral absorption
profile, largely due to significant intramolecular hydrogen
bonding [3]. In addition, altering or reducing a compound net
charge in the pH range 5.5 – 7.0 is usually associated with significant improvements in intestinal permeability. Depending
on the series, this can be done by increasing pKa of acids,
decreasing pKa of bases or avoiding zwitterions [66].
Marsilje et al. used this approach to optimise the oral exposure of a set of melanocortin 4 receptor antagonists. T he
group demonstrated that reducing the compound basicity by
substituting an amidine with an imidazole significantly
improved its oral exposure [67]. In the above examples,
physicochemical changes mainly influenced compound intestinal permeability. However, discovery teams should also consider the impact of these changes on other relevant parameters
such as solubility, metabolism and pharmacological potency.
T herefore, discovery teams are advised to establish a balance
between these interrelated parameters.
Efflux transporters and permeability
Efflux transporters play a major role in limiting the intestinal
permeability of various xenobiotics. T his is usually demonstrated by using Caco-2 cell system by comparing permeability in two directions, apical to basal (A→B) and basal to
apical (B →A). When a compound series has a BA/AB permeability ratio > 2.5, with low passive permeability, efflux transporters are playing a significant role in reducing the effective
intestinal permeability [68]. It is interesting to observe that
Caco-2 cell line expresses not only P-gp transporter, but also
other relevant efflux transporters such as BCRP, MRP and
organic ion transporters [69]. In order to determine if efflux is
primarily due to P-gp, BA/AB permeability ratio is measured
in the Madin–Darby Canine Kidney/MDR1 cell line
(Figure 8 ). T his cell line has the advantage of short culture
times and a capacity to stably overexpress specific transporters,
in this case MDR1 (P-gp) [46]. If the ratio in these cells is
3.2
similar or greater than that obtained in Caco-2 cells, efflux is
likely due to P-gp. If lower, other transporters present in
Caco-2 cells may be responsible for the high efflux. As a result
of efflux involvement, it is quite likely that the effective permeability of the compound series will be concentration
dependent and the rate of permeation should be evaluated at
concentrations relevant to the projected dose. Walker et al.
provides a detailed study in defining the role of efflux transporters and the superproportional dose–exposure relationship
seen with UK-427,857 [70].
Many successful compounds are substrates of P-gp, such as,
digoxin [71], erythromycin [72] and atorvastatin [73], to name a
few. P-gp substrates can also cause competitive inhibition of
coadministered medications, resulting in altered absorption
profiles, as is the case when atorvastatin is administered with
digoxin [74,75]. It is key to understand the implications of having an efflux transporter on the oral bioavailability of compounds evaluated and if possible eliminate this potential
liability through structural modifications via a P-gp SAR optimisation (Figure 8 ). It should be emphasised that excipients
can inhibit P-gp activity and/or CYP-mediated gut metabolism, resulting in a significant increase in the plasma exposure of the administered drug [76]. As a general approach,
reduction in compound lipophilicity and HBA groups is a
good starting point [77].
4.
M etabolism
In 2002, hepatic metabolism was the major route of elimination for around three-quarters of the top 200 prescribed
drugs in the US [201]. Hepatic metabolism is an enzymatic
process in which a drug is chemically modified into a polar
metabolite that can be more easily excreted through urine or
bile [78]. In general, discovery teams strive to identify molecules that have adequate hepatic stability to allow for
once-a-day dosing. To that end, selected chemical series are
inherently metabolically stable and/or can be modified to
reduce metabolic liability.
Metabolism is divided into phase I and II processes [79]. In
phase I, the drug undergoes oxidative attack that introduces
or exposes a polar functional group on the drug molecule. For
example, a hydroxyl group is introduced onto the phenyl
group on mephenytoin by aromatic hydroxylation to form
hydroxy(S)-mephenytoin [80]. Dextromethorphan is demethylated to form dextrophan [81]. A list of common reactions and
enzymes involved in these processes is shown in Tables 2
and 3 , respectively [82,83]. From this list, the CYP superfamily
is the major family of enzymes that is responsible for the
metabolism of most marketed drugs and xenobiotics [84-87]. In
phase II, a polar moiety is usually added into either the parent
molecule or its phase I metabolites [88]. T he resulting polar
metabolites are then excreted from the body through urine or
bile, or in some cases sweat or exhalation. Phase II processes
involve conjugation reagents that are normally derived from
biochemical compounds involved in carbohydrate, fat and
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
599
The road map to oral bioavailability: an industrial perspective
Table 2. Phase I reactions.
Phase I reactions
F = ( 1 – E h ) ⋅ Fa ⋅ Fg
Examples
Oxidation
Hydroxylation
Phenytoin, acetaminophen
Dealkylation
Diazepam, phenacetin
Deamination
Amfetamine
Sulfoxidation
Chlorpromazine
Reduction
Sulfasalazine, chloramphenicol
Hydrolysis
Aspirin, phenacetin
(3)
where F is the oral drug bioavailability, Fa is the fraction of
the dose that is absorbed after oral administration and Fg is
the fraction of the dose that escapes intestinal metabolism. Eh
is the hepatic extraction ratio, which is a measure of the liver’s
ability to extract drug from the systemic circulation and is
used to assess the impact of hepatic extraction on oral
bioavailability. Eh is calculated using Equation 4 [89]:
(4)
Table 3. Phase I enzymes.
Phase I reactions
Enzymes
Oxidation
P450 monooxygenase
CL h
E h = ---------Q
Xanthine oxidase
Peroxidases
Amine oxidase
Dioxygenase
Semicarbizide-sensitive amine
oxidase
M onoamine oxidase
Reduction
where CLh is the hepatic drug blood clearance and Q is the
hepatic blood flow. Because hepatic metabolism is the primary clearance mechanism for most marketed drugs, it is reasonable to assume that the total blood clearance (CL) is equal
to CLh; shown in Equation 5:
P450 monooxygenase
CL
F = ⎛ 1 – -------⎞ ⋅ Fa ⋅ Fg
⎝
Q⎠
Ketoreducatase
Glutathione peroxidases
Hydrolysis
Epoxide hydrolase
Table 4. Phase II reactions.
Phase II reactions
Examples
Glucoronidation
Phenytoin, chloramphenicol
M ethylation
Noradrenaline
Acetylation
Proconamide, isoniazid
protein metabolism [89]. It is interesting to note that these
reactions include a high-energy form of the conjugating
agent, such as uridine diphosphate-glucuronic acid, acetyl
CoA, 3 ′-phosphoadenosine-5 ′-phosphosulfate or S-adenosylmethionine, which in the presence of appropriate transferase
enzyme, combines with the drug or its phase I metabolite to
form the phase II conjugate [88]. T he major reactions and
enzymes involved in these processes are shown in Tables 4
and 5 , respectively [90].
Oral bioavailability can be defined as the product of
absorption and metabolism, as shown in Equation 3 [55,89]:
600
(5)
As shown in Figure 9 , if a compound series has a rat blood
CL value < 50 ml/min/kg and considering that the rat Q is
equal to 70 ml/min/kg [91], then its E h is < 0.7 and its poor
oral bioavailability can be assumed to be predominately a
result of poor absorption and/or significant intestinal
metabolism rather than high hepatic metabolism. T herefore,
it is pivotal to consider factors in the absorption section of
the road map that may influence compound oral bioavailability. As for the intestinal metabolism, it should be
emphasised that our current understanding of intestinal
metabolism has increased significantly as a result of major
strides in the fields of molecular sciences and biochemistry.
In the literature, it has been clearly demonstrated that the
small intestine plays a pivotal role in first-pass metabolism,
especially with compounds with poor aqueous solubility and
low oral dose (dose < 100 mg/day) [55]. However, it is clear
that both the protein level and catalytic activity of
drug-metabolising enzymes in the small intestine are
generally lower than those in the liver and that this is
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
Thomas, Bhattachar, Hitchingham, Zocharski, Naath, Surendran, Stoner & El-Kattan
Table 5. Phase II enzymes.
Phase II enzymes
Reactions
Glucuronosyltransferase
M ethylation
Enzymes
Sulfotransferase
O-methyltransferase
Glutathione S-transferase
N-methyltransferase
Glucosyltransferase
S-methyltransferase
Amide synthesis (transcylase)
Acetylation
N-acetyltransferase
Acetyltransferase
Thiosulfate
Sulfotransferase
particularly true for CYP enzymes. Considering the limited
drug-metabolising capacity in the small intestine, the contribution of this organ to the overall metabolism of a drug is
less likely to be quantitatively as important as that of the
liver, unless a very small oral dose is given [78].
It should be noted that each species has a different value for
Q (blood flow) and most likely different values for blood CLh.
T herefore, comparing E h values simplifies comparisons
between rat, dog, man and other evaluated species [78]. If a
compound series has a rat CL > 50 ml/min/kg, then the
discovery team should determine if the compound series has
species differences in its hepatic stability.
Importance of monitoring species differences
It is important to note, as seen with the variable type and
expression of transporters in oral absorption, species differences also exist in drug-metabolising enzymes. Several investigators attributed these findings to differences in physiological
factors such as hepatic blood flow, or enzyme type and expression [78,89]. For example, Nelson et al. reported that so far
14 CYP gene families have been identified in mammals with
significant variations in the primary sequence of amino acids
across species. However, these members of the superfamily
had highly conserved regions of amino acid sequence [92].
Similar findings were also reported with uridine diphosphoglucose transferases and carboxylesterases [93,94]. Overall,
these small differences in the amino acid sequences can lead to
significant differences in substrate affinity and specificity
which translates into differences in the metabolism rate and
metabolism profiles.
As a general rule, compounds with good passive absorption,
high rat hepatic extraction ratio, and poor oral bioavailability
tend to have better oral bioavailability in higher species such as
dogs, monkeys and humans. T here are many cited examples
that are consistent with this trend. For example, the pharmacokinetics of remoxipride was studied in rodents (mice, rats,
hamsters), dogs and humans [95]. Remoxipride was rapidly and
completely absorbed through the intestinal wall in all species
evaluated. However, the bioavailability was low in the rodents
(< 10% in mice and hamsters and < 1% in rats) due to extensive first-pass elimination in the hepato–portal system. Blood
clearance estimated after the same intravenous doses was high
in rodents and similar to or exceeding normal liver blood flow.
On the other hand, in dogs and humans, clearance values were
low and the bioavailability high (> 90%) [95]. Other examples
of marketed drugs that have poor oral bioavailability in rodents
yet good bioavailability in higher species include reboxetine,
diazepam and indinavir [26,95-98]. T hese successful medications
would not be on the market if the discovery team solely
depended on rat oral bioavailability to evaluate their
metabolism in humans.
4.1
4.2 Liver microsomes as an indicative model for
reducing metabolism-limited absorption
Liver microsomes are widely used as a tool to assess the contribution of phase I enzymes such as CYP enzymes, flavin-containing
monooxygenases and other metabolising enzymes (Table 3 ) [99].
Microsomes are convenient as they can be stored frozen, for long
periods of time (years) without compromising their enzymatic
activity [100]. The most common approach to using human
microsomes is in determining hepatic stability, by measuring the
intrinsic hepatic clearance (CLint) detailed in Equation 6
summarised by Obach et al. in a previous report [100]:
(6)
gm liver wt
1
CL int = 0.693 × -------- × ----------------------------t1 ⁄ 2 kg body wt
ml incubation
45 mg microsomal prot
× ----------------------------------------------------- × -----------------------------------------------------------mg microsomal prot
gm liver wt
A human CLint value > 40 µl/min/mg protein is considered high and warrants a metabolism SAR optimisation to
improve the metabolic profile (Figure 9 ). One of the most
widely used approaches to improve the metabolic stability of
various compounds is to reduce drug lipophilicity, as higher
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
601
The road map to oral bioavailability: an industrial perspective
Metabolism
Rat CL
> 50 ml/min/kg
Yes
Yes
No
Human microsomes
CLint > 40 µl/min/mg
Discuss with team absorption
and/or metabolism-limiting
factors. Consider factors in the
absorption tree
Metabolism SAR
optimisation
Discuss with team
soft spot analysis
(MetaSite)
No
No
Human hepatocytes
Eh > 0.7
Yes
Metabolism SAR
optimisation
No
Discuss with team
species for
toxicology studies
Yes
Dog hepatocytes
Eh > 0.7
Metabolism SAR
optimisation
Figure 9. M etabolism section of the road map. When a compound series has a rat CL > 50 ml/min/kg, then the discovery team
should determine if the compound series has species differences in its hepatic stability through the use of microsomes. These studies
should then be follow ed by a thorough hepatic stability evaluation in human hepatocytes.
CLint : Intrinsic hepatic clearance; Eh: Hepatic extraction ratio; SAR: Structure–activity relationship.
lipophilicity increases the binding affinity of various drugs
and xenobiotics to metabolising enzymes [8,101,102]. T here are
two generally accepted approaches to reduce the lipophilic
nature of a molecule. T he first is by replacing a bulky
lipophilic group, which has minimal relevance to the pharmacological activity of the compounds, with groups known
to lower lipophilicity. For example, Dragovich et al. replaced
a benzyl group in the rhinovirus 3C protease inhibitor lead
compound with ethyl and propyl groups. T hese changes were
associated with significant improvement in the monkey oral
exposure [103]. T he second approach is to introduce polar
functional groups (e.g., pyridine) or isosteric atoms such as
nitrogen or oxygen to improve the metabolic stability of
compounds tested. Tagat et al. replaced the benzamide group
602
in the CCR5 antagonist lead compound with nicotinamide,
which was associated with a significant improvement in its
metabolic stability in rat, dog and monkey [104]. Another
approach that is gaining interest from medicinal chemists is
the use of in silico models of biotransformation such as
MetaSite. T his technique is a new in silico method that provides the metabolism site for any human CYP-mediated reaction [105]. T he methodology can be applied automatically to
all major CYP enzymes and used by medicinal chemists to
detect positions that should be protected in order to avoid
metabolic degradation or to check the suitability of a new
scaffold or prodrug. Although this and other similar
approaches do not identify rates of hepatic clearance, they
provide information on molecular ‘soft spots’ and hence
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
Thomas, Bhattachar, Hitchingham, Zocharski, Naath, Surendran, Stoner & El-Kattan
provide for a handle to medicinal chemists to design
analogues with superior properties [106,107].
4.3 Hepatocytes: the more definitive guide
to metabolism
In the case where human microsomal data of a chemical
series suggest low to moderate intrinsic clearance (CLint
< 40 µl/min/mg protein), it is recommended to continue
the hepatic stability evaluation in human hepatocytes
( Figure 9 ). Microsomes metabolise compounds primarily
through phase I (e.g., CYP-mediated metabolism), whereas
hepatocytes are known to metabolise compounds through
both phase I and II reactions [108]. Examples have been cited
where compounds were extensively metabolised by phase II,
but not phase I and had significantly lower oral bioavailability. For example, raloxifene is extensively glucuronidated in humans, effectively eliminating its oral
bioavailability (F% = 0.02) [109,110]. Other examples on
drugs with extensive conjugation and poor oral bioavailability (F% < 30) are morphine, nalbuphine and propofol,
to name a few [111-113]. T herefore, evaluating hepatic stability in hepatocytes is critical for developing a compound
series with good oral bioavailability in humans.
In general, compound stability in hepatocytes is assessed by
determining E h using Equations 7 and 8 [100,114]:
(7)
gm liver wt
1
CL int = 0.693 × -------- × ----------------------------t1 ⁄ 2 kg body wt
ml incubation
cells
× ------------------------------------------ × ----------------------------cells incubation gm liver wt
For compounds to be developed in the clinic, an appropriate plasma exposure should be achieved in nonrodent species to study the drug toxicological profile. Dogs are usually
the species of choice because of availability and resemblance
to human physiology [116,117]. T he authors recommend evaluating the metabolism profiles of compounds in dog hepatocytes. If the compound continues to show high clearance in
dog hepatocytes (Eh > 0.7), a metabolism SAR optimisation is
necessary, especially when compounds demonstrate poor
plasma exposure following oral dosing in dogs. T his will limit
the ability of discovery teams to evaluate the compound toxicological profile in dogs. If the compound demonstrates low
to moderate clearance in dog hepatocytes (E h < 0.7) then the
team should consider other factors in the absorption section
of the road map that may influence the compound oral
bioavailability such as permeability or/and solubility.
5.
T he road map concept provides a common language to focus
discussions around the potential causes of poor oral bioavailability when evaluating options in optimising a chemical series.
It is based on dividing the factors that influence the oral bioavailability in two interrelated categories: absorption (product
of solubility and permeability) and metabolism. Each category
has its unique role, but with a great degree of interdependence
in many cases. Such a tool should allow discovery teams to
streamline the process of addressing poor oral bioavailability
by using key assays for evaluation of each factor that may limit
oral exposure with significant emphasis on in vitro and
in silico tools to reduce costs and length of time for optimising
the critical physicochemical and pharmacokinetic properties
of a chemical series.
6.
Q h ⋅ fu ⋅ CL int
CL h = -----------------------------------Q h + fu ⋅ CL int
(8)
where fu is the drug unbound fraction. An E h value > 0.7
suggests the potential for high clearance that would limit
oral drug bioavailability, as shown in Equation 3. Metabolism SAR optimisation should be initiated to address the
projected high human clearance using approaches shown in
Section 3.2. In comparison, an E h value < 0.7 may suggest a
low to moderate risk to metabolism-limiting drug disposition in humans. It should be noted that sometimes in vitro
systems of metabolism can greatly overpredict the biotransformation of compounds that have high plasma protein
binding and, therefore, it is critical to put the E h values in
context [95,111,115].
Conclusion
Expert opinion
It is often difficult and costly to generate a complete set of
physicochemical and pharmacokinetic data in early discovery
settings due to limited compound supply and aggressive discovery timelines. As a result, it is pivotal to quickly identify
major barriers contributing to poor bioavailability with as little compound as possible. T his tool provides a road map of
physicochemical property assessments and molecular modelling to address relationships between molecular structure and
various pharmacokinetic properties. T he Biopharmaceutics
Classification System [202] and the Biopharmaceutics Drug
Disposition Classification System [118] are examples of tools
that move beyond molecular structure and consider both
physicochemical and biological characteristics that impact
drug absorption and disposition. T hese approaches to drug
classification are useful for a particular molecular entity; however, as one progresses through the timelines of a discovery
programme, several molecular templates are typically considered in parallel, greatly increasing the number of species to be
evaluated. A discovery team must be able to triage molecules
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
603
The road map to oral bioavailability: an industrial perspective
from a particular chemical template for potential bioavailability limitations using available high-throughput in vitro
and in silico assays to minimise raw material demands.
T he concept of developing a road map provides a foundation from which a team of scientists may begin to address
the limitations to oral plasma exposure. T he map may be
used either to pursue causal factors leading to poor in vivo
exposure or to evaluate potential absorption/metabolism
barriers prior to in vivo evaluation as an effort to conserve
compound supply and animal resources. In either case, the
map describes a systematic approach towards evaluating
in vivo and in vitro data related to absorption based on
Bibliography
established pharmaceutical principles. It does not, however,
predict the extent of oral absorption or provide a ranking of
drug-likeness based on one’s progression through the various sections of the road map. Conclusions that may be
made are ones of possible risk for certain molecules or
chemical templates based on early in vitro, in vivo and
in silico data.
Acknow ledgements
T he authors wish to thank M Mollan and J Brodfuehrer for
their helpful review of this manuscript.
AVDEEF A, T ESTA B: Physicochemical
8.
16.
FLYNN GL, YALKOWSKY SH,
Papers of special note have been highlighted as
profiling in drug research: a brief survey of
ROSEMAN T J: Mass transport phenomena
either of interest (•) or of considerable interest
the state-of-the-art of experimental
and models: theoretical concepts.
(••) to readers.
techniques. Cell. Mol. Life Sci. (2002)
1.
59 (10):1681-1689.
DIMASI JA, HANSEN RW,
GRABOWSKI HG: T he price of
9.
innovation: new estimates of drug
development costs. J. Health Econ. (2003)
22 (2):151-185.
•
2.
10.
GRIBBON P, SEWING A:
High-throughput drug discovery: what can
11.
and computational approaches to estimate
solubility and permeability in drug
discovery and development settings.
Adv. Drug Deliv. Rev. (2001) 46 (1-3):3-26.
••
4.
T horough overview describing several
12.
GRANT DJW, HIGUCHI T: Solubility
MASUCCI JA, HAGEMAN W, YAN Z:
behavior of organic compounds.
T he new pre-preclinical paradigm:
WH Saunders Jr (Ed.), John Wiley and
Sons, New York, USA (1990):12-88.
19.
DEHRING KA, WORKMAN HL,
MILLER KD, MANDAGERE A,
PARROT T N, PAQUEREAU N,
POOLE SK: Automated robotic liquid
COASSOLO P, LAVE T: An evaluation of
handling/laser-based nephelometry system
the utility of physiologically based models
for high throughput measurement of kinetic
of pharmacokinetics in early drug discovery.
aqueous solubility. J. Pharm. Biomed. Anal.
J. Pharm. Sci. (2005) 94 (10):2327-2343.
(2004) 36 (3):447-456.
HELLRIEGEL ET, BJORNSSON T D,
20.
LIPINSKI CA: Solubility in water and
DMSO: Issues and potential solutions. In:
bioavailability is related to the extent of
Pharmaceutical Profiling in Drug Discovery
VAN DE WAT ERBEEMD H,
absorption: implications for bioavailability
for Lead Selection. RT Borchardt, EH Kerns,
and bioequivalence studies. Clin.
CA Lipinski et al. (Eds), AAPS Press,
Arlington, VA, USA (2004):93-126.
Pharmacol. Ther. (1996) 60 (6):601-607.
13.
LIPINSKI CA: Drug-like properties and the
21.
JAIN N, YALKOWSKY SH: Estimation of
pharmacokinetics. J. Med. Chem. (2001)
causes of poor solubility and poor
the aqueous solubility I: application to
44 (9):1313-1333.
permeability. J. Pharmacol. Toxicol. Methods
organic nonelectrolytes. J. Pharm. Sci.
DI L, KERNS EH: Profiling drug-like
(2000) 44 (1):235-249.
properties in discovery research. Curr. Opin.
••
Chem. Biol. (2003) 7 (3):402-408.
BALANI SK, MIWA GT, GAN L-S,
WU J-T, LEE FW: Strategy of utilizing
14.
in vitro and in vivo ADME tools for lead
KERNS EH: High throughput
physicochemical profiling for drug
discovery. J. Pharm. Sci. (2001)
90 (11):1838-1858.
YALKOWSKY SH: Solubility and
miscibility. In: Solubility and solubilization
rational drug design approaches.
in aqueous media . Oxford University Press,
VEBER DF, JOHNSON SR, CHENG HY
New York, USA (1999):49-80.
J. Med. Chem. (2002) 45 (12):2615-2623.
15.
(2001) 90 (2):234-252.
22.
output obtained from both H TS and
the oral bioavailability of drug candidates.
Curr. Top. Med. Chem. (2005)
5 :1033-1038.
Provides a prospective to chemical matter
et al.: Molecular properties that influence
optimization and drug candidate selection.
604
Pharm. Res. (1995) 12 (3):413-420.
18.
solubility and permeability.
optimization of drug absorption and
7.
CALDWELL GW, RITCHIE DM,
HAUCK WW: Interpatient variability in
WALKER DK: Property-based design:
6.
dissolution and in vivo bioavailability.
discovery approaches for assessing
SMIT H DA, BEAUMONT K,
5.
the correlation of in vitro drug product
selection tool in drug discovery.
Chem. (2001) 1 (5):353-366.
LIPINSKI CA, LOMBARDO F,
DOMINY BW, FEENEY PJ: Experimental
for a biopharmaceutic drug classification:
projection using in vitro screening data as a
phase drug discovery. Curr. Top. Med.
(2005) 10 (1):17-22.
3.
SHAH VP, CRISON JR: A theoretical basis
et al.: Integrated oral bioavailability
compound optimization in early and late
we expect from HTS? Drug Discov. Today
AMIDON GL, LENNERNAS H,
STONER CL, CLETON A, JOHNSON K
Int. J. Pharm. (2004) 269 (1):241-249.
A good overview for the financial impact of
poor decision making.
J. Pharm. Sci. (1974) 63 (4):479-510.
17.
23.
ANDO HY, RADEBAUGH GW:
Property-based drug design and
preformulation. In: Remington: The Science
PALM K, ST ENBERG P, LUT HMAN K,
and Practice of Pharmacy. Philadelphia
ART URSSON P: Polar molecular surface
UotSi (Ed.) Lippincott, Williams and
properties predict the intestinal absorption
Wilkins, Philidelphia, PA, USA
of drugs in humans. Pharm. Res. (1997)
(2005):720-744.
14 (5):568-571.
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
Thomas, Bhattachar, Hitchingham, Zocharski, Naath, Surendran, Stoner & El-Kattan
24.
GOOSEN C, LAING T J, DU PJ,
human bioavailability of phenytoin. Chem.
gastrointestinal secretion of glutathione
GOOSEN TC, FLYNN GL:
Pharm. Bull. (1986) 34 (10):4400-4402.
conjugates in rats. J. Pharmacol. Exp. Ther.
LIVERSIDGE GG, CUNDY KC: Particle
(2000) 292 (1):433-439.
Physicochemical characterization and
solubility analysis of thalidomide and its
36.
size reduction for improvement of oral
N -alkyl analogs. Pharm. Res. (2002)
19 (1):13-19.
25.
UK-343,664 in man. Xenobiotica (2001)
Int. J. Pharm. (1995) 125 (1):91-97.
31 (8-9):665-676.
37.
42 (12):2266-2271.
VACCA JP, DORSEY BD, SCHLEIF WA
et al.: L-735,524: an orally bioavailable
38.
39.
(6-amino-seco-CI) DNA minor groove
alkylating agents and structure–activity
relationships for their cytotoxicity.
J. Med. Chem. (1999) 42 (4):649-658.
CHOWHAN ZT: pH-solubility profiles or
40.
30.
41.
43.
structure requirements for pluronic block
tract of the rate. J. Pharm. Sci. (1998)
copolymers in modifying P-glycoprotein
87 :360-366.
drug efflux transporter activity in bovine
LENNERNAS H: Does fluid flow across
brain microvessel endothelial cells.
Classification analysis of P-glycoprotein
FRIEND DR: Drug delivery to the small
18 (1):1-15.
Good overview of intestinal transporters.
44.
OH DM, HAN HK, WILLIAMSON RM
et al.: Improved intestinal transport of
PD-158473, an N -methyl-D -aspartate
JOHNSON KC, SWINDELL AC:
(NMDA) antagonist, by involvement of
Guidance in the setting of drug particle size
multiple transporters. J. Pharm. Sci. (2002)
specifications to minimize variability in
91 (12):2579-2587.
DOHERT Y MM, CHARMAN WN: T he
•
relevant as an organ of drug metabolism?
Estimating the fraction dose absorbed from
Clin. Pharmacokinet. (2002)
suspensions of poorly soluble compounds in
41 (4):235-253.
46.
GOTOH Y, SUZUKI H, KINOSHITA S
et al.: Involvement of an organic anion
YAKOU S, YAMAZAKI S, SONOBE T
transporter (canalicular multispecific
et al.: Particle size distribution affects the
organic anion transporter/multidrug
resistance-associated protein 2) in
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
Detailed analysis into P-gp substrate
recognition.
52.
GOMBAR VK, POLLI JW,
HUMPHREYS JE, WRING SA,
SERABJIT-SINGH CS: Predicting
P-glycoprotein substrates by a quantitative
structure–activity relationship model.
J. Pharm. Sci. (2004) 93 (4):957-968.
53.
SEELIG A, LANDWOJTOWICZ E:
Structure-activity relationship of
P-glycoprotein substrates and modifiers.
Eur. J. Pharm. Sci. (2000) 12 (1):31-40.
54.
T EODORI E, DEI S, SCAPECCHI S,
GUALT IERI F: T he medicinal chemistry of
multidrug resistance (MDR) reversing
drugs. Farmaco (2002) 57 (5):385-415.
55.
LIN J, SAHAKIAN DC, DE MORAIS SM
et al.: T he role of absorption, distribution,
mucosa of the small intestine: how clinically
OH DM, CURL RL, AMIDON GL:
(1993) 10 (2):264-270.
substrate specificity. J. Drug Target. (2003)
11 (7):391-406.
KAT SURA T, INUI K: Intestinal
Drug Metab. Pharmacokinet. (2003)
45.
DIDZIAPET RIS R, JAPERTAS P,
AVDEEF A, PET RAUSKAS A:
with improved pharmaceutical profiles for
humans: a mathematical model. Pharm. Res.
51.
PIYAPOLRUNGROJ N, ZHOU YS, LI C
•
13 :1795-1798.
304 (2):845-854.
12 (11):1573-1582.
et al.: Pyrroloquinolone PDE5 inhibitors
absorption. Pharm. Res. (1996)
J. Pharmacol. Exp. Ther. (2003)
transporters: mechanisms and regulation.
J. Med. Chem. (2005) 48 (6):2126-2133.
35.
MILLER DW, KABANOV AV: Optimal
absorption of drugs mediated by drug
JIANG W, GUAN J, MACIELAG MJ
BAT RAKOVA EV, LI S, ALAKHOV VY,
drugs in different regions of the intestinal
6 (5):371-376.
Pharm. Res. (2003) 20 (3):406-408.
clinical studies on erectile dysfunction.
50.
LENNERNAS H: Membrane transport of
intestine. Curr. Gastroenterol. Rep. (2004)
depends on the dose/solubility ratio.
34.
disposition in rat. Pharmacology (1998)
56 (6):308-313.
Drug Metab. Dispos. (2000) 28 (1):65-72.
MACHERAS P: T he mean dissolution time
ketoconazole on digoxin absorption and
UNGELL A-L, NYLANDER S,
elimination in rat small intestine.
42.
SALPHAT I L, BENET LZ: Effects of
Eur. J. Pharm. Sci. (1999) 9 (1):47-56.
SERAJUDDIN AT: IV-IVC considerations
RINAKI E, DOKOUMET ZIDIS A,
Pharm. Pharmacol. (2004) 56 (8):967-975.
49.
et al.: Cimetidine absorption and
94 (7):1396-1417.
33.
pharmacokinetics of selected substrates. J.
LI S, HE H, PART HIBAN LJ, YIN H,
oral dosage form. J. Pharm. Sci. (2005)
32.
KARLSSON J, UNGELL A, GRASJO J,
reevaluation? Pharm. Res. (1995)
KRAMER SF, FLYNN GL: Solubility of
in the development of immediate-release
31.
psychoactive compounds-implications for
drug absorption? Is it time for a
J. Pharm. Sci. (1978) 67 (9):1257-1260.
(1972) 61 (12):1896-1904.
substrates and inhibitors among
(1990) 16 (2-3):101-108.
the intestinal mucosa affect quantitative oral
organic carboxylic acids and their salts.
organic hydrochlorides. J. Pharm. Sci.
et al.: Identification of P-glycoprotein
BERGST RAND S, SJOBERG A,
3-(chloromethyl)-6-aminoindoline
EL ELA AA, HART T ER S, SCHMIT T U
cellular pathways. Miner. Electrolyte Metab.
influence of charge and induced water flux.
USA (1994) 91 (9):4096-4100.
et al.: Synthesis of 1-substituted
48.
absorption. Interplay of paracellular and
transport across intestinal epithelia:
protease inhibitor. Proc. Natl. Acad. Sci.
MILBANK JB, T ERCEL M, AT WELL GJ
NELLANS HN: Intestinal calcium
ART URSSON P: Paracellular drug
human immunodeficiency virus type 1
29.
the non-proportional pharmacokinetics of
ORT WINE DF et al.: Design and synthesis
acid derivatives. J. Med. Chem. (1999)
28.
et al.: Potential role for P-glycoprotein in
Absolute oral bioavailability of
nanocrystalline danazol in beagle dogs.
AMPA/GlyN receptor antagonists: amino
27.
ABEL S, BEAUMONT KC, CRESPI CL
NIKAM SS, CORDON JJ,
of novel quinoxaline-2,3-dione
26.
47.
bioavailability of hydrophobic drugs: I.
metabolism, excretion and toxicity in drug
discovery. Curr. Top. Med. Chem. (2003)
3 (10):1125-1154.
56.
LI Y, SHIN YG, YU C et al.: Increasing the
throughput and productivity of Caco-2 cell
permeability assays using liquid
chromatography-mass spectrometry:
application to resveratrol absorption and
605
The road map to oral bioavailability: an industrial perspective
57.
58.
metabolism. Comb. Chem. High Throughput
molecules. Chem. Pharm. Bull. (2004)
Screen. (2003) 6 (8):757-767.
52 (5):561-565.
PORT ER CJH: An in vitro examination of
MARSILJE T H, ROSES JB,
the impact of polyethylene glycol 400,
LENNERNAS H: Human intestinal
67.
permeability. J. Pharm. Sci. (1998)
CALDERWOOD EF et al.: Synthesis and
87 (4):403-410.
biological evaluation of imidazole-based
POLLI JE, GINSKI MJ: Human drug
small molecule antagonists of the
68.
Pharm. Res. (1998) 15 (10):1520-1524.
of analytical solutions for k(a) and F(a).
69.
SUGIYAMA Y: Impact of drug transporter
YEE S: In vitro permeability across Caco-2
studies on drug discovery and development.
cells (colonic) can predict in vivo (small
70.
WAT KINS PB et al.: First-pass midazolam
metabolism catalyzed by 1 α,25-dihydroxy
71.
73.
in microsomal tolbutamide,
S-mephenytoin, and omeprazole
hydroxylations. Arch. Biochem. Biophys.
(1998) 353 (1):16-28.
81.
iv [14 C]erythromycin
LIN LS, LANZA T J, JR.,
potent and orally bioavailable antagonists of
VLA-4. Bioorg. Med. Chem. Lett. (2004)
74.
liver microsomes as a prototype reaction to
monitor cytochrome P450 db1 activity.
Clin. Pharmacol. Ther. (1989) 45 (1):34-40.
breath and urine
82.
DICKINSON RP et al.: Absorption,
distribution, metabolism, and excretion
PELKONEN O, RAUNIO H,
RAUT IO A, LANG M:
the proton-monocarboxylic acid
Xenobiotic-metabolizing enzymes and
co-transporter. Pharm. Res. (2000)
cancer risk: correspondence between
17 (2):209-215.
genotype and phenotype. IARC Sci. Publ.
BOYD RA, ST ERN RH, ST EWART BH
(1999) 148 :77-88.
84.
LIU L, PANG KS: T he roles of transporters
increase digoxin concentrations by
and enzymes in hepatic drug processing.
inhibition of intestinal
Drug Metab. Dispos. (2005) 33 (1):1-9.
J. Clin. Pharmacol. (2000) 40 (1):91-98.
indole-containing endothelin antagonist.
IARC Sci. Publ. (1999) 148 :13-22.
83.
model: contributions of P-glycoprotein and
P-glycoprotein-mediated secretion.
considerations in selection of orally active
LANG M, PELKONEN O: Metabolism of
xenobiotics and chemical carcinogenesis.
WU X, WHIT FIELD LR, ST EWART BH:
et al.: Atorvastatin coadministration may
WALKER DK, DACK KN,
DAYER P, LEEMANN T, ST RIBERNI R:
Dextromethorphan O-demethylation in
LEMAHIEU WP, MAES BD, GHOOS Y
Atorvastatin transport in the Caco-2 cell
replacement of anilide with benzoxazole:
85.
MEIBOHM B, BEIERLE I,
DERENDORF H: How important are
ST EWART BH, KUGLER AR,
gender differences in pharmacokinetics?
29 (11):1424-1431.
T HOMPSON PR, BOCKBRADER HN:
Clin. Pharmacokinet. (2002)
RUELL JA, TSINMAN O, AVDEEF A:
A saturable transport mechanism in the
Acid-base cosolvent method for
determining aqueous permeability of
amiodarone, itraconazole, tamoxifen,
terfenadine and other very insoluble
606
CAVET ME, WEST M, SIMMIONS NL:
Physiol. (2003) 285 (3):G470-G482.
CASTONGUAY LA et al.: Bioisosteric
66.
CYP2C9 from human liver: respective roles
+
segments. Pharm. Res. (1993)
Drug Metab. Dispos. (2001)
Characterization of CYP2C19 and
the impact of species difference.
test. Am. J. Physiol. Gastrointest. Liver
intestinal epithelial cells and rat intestinal
65.
ARAMSOMBAT DEE E, RAUCY JL:
CYP3A4 and PGP activity by combined po
absorption: cultured monolayers of human
LASKER JM, WEST ER MR,
A very well-designed study to determine
et al.: Measurement of hepatic and intestinal
permeability in two models of intestinal
14 (9):2331-2334.
Curr. Drug Metab. (2000) 1 (2):107-132.
80.
Dispos. (2005) 33 (4):587-595.
Br. J. Pharmacol. (1996) 118 :1389-1396.
72.
LOFROT H JE: Selective paracellular
10 (8):1123-1129.
enzymes: mechanisms and functions.
intestinal epithelial (Caco-2) cells.
289 (2):1134-1142.
64.
WALKER DK, ABEL S, COMBY P et al.:
cardiac glycoside, digoxin, by human
monolayers. J. Pharmacol. Exp. Ther. (1999)
ART URSSON P, UNGELL AL,
discovery and development. Pharmacol. Rev.
(1997) 49 (4):403-449.
Transport and epithelial secreation of the
vitamin D3-modified Caco-2 cell
63.
pharmacokinetics and metabolism in drug
A good overview.
potential treatment for HIV. Drug Metab.
••
LIN JH, LU AYH: Role of
SHEWEITA SA: Drug-metabolizing
CCR5 antagonist, UK-427,857, a new
absorption. Expert Opin. Drug Metab.
78.
•
VAN BREEMEN RB, LI Y: Caco-2 cell
FISHER JM, WRIGHTON SA,
Mol. Pharmacol. (2002) 61 (5):974-981.
79.
Species differences in the disposition of the
permeability assays to measure drug
62.
of P-glycoprotein inhibitors and substrates.
Pharmacol. Rev. (2003) 55 (3):425-461.
myth. Pharm. Res. (1997) 14 (6):763-766.
Toxicol. (2005) 2005 (1):175-185.
quantitative structure–activity relationships
MIZUNO N, NIWA T, YOT SUMOTO Y,
314 (1):391-399.
EKINS S, KIM RB, LEAKE BF et al.:
Application of three-dimensional
MDR1-MDCK and Caco-2 monolayers.
development and evaluation and derivation
61.
4 (4):1-13.
77.
cysteine protease inhibitor, across
absorption-disposition model: model
intestinal) absorption in man – fact or
intestine. AAPS PharmaSci (2002)
KO2, a novel vinylsulfone peptidomimetic
Caco-2 permeability using an
60.
enterocyte-based metabolism in excised rat
of P-glycoprotein mediated transport of
human drug oral absorption kinetics from
J. Pharmacol. Exp. Ther. (2005)
ZHANG Z, BENET LZ: Characterization
polyethylene glycol 1000
succinate on P-glycoprotein efflux and
14 (14):3721-3725.
Pharm. Res. (1998) 15 (1):47-52.
USANSKY HH, SINKO PJ: Estimating
D - α-tocopheryl
Bioorg. Med. Chem. Lett. (2004)
Caco-2 monolayer permeabilities.
JOHNSON BM, CHARMAN WN,
pluronic P85, and vitamin E
melanocortin 4 receptor (MC4-R).
absorption kinetics and comparison to
59.
76.
75.
intestinal absorption of gabapentin is the
underlying cause of the lack of
proportionality between increasing dose and
drug levels in plasma. Pharm. Res. (1993)
10 (2):276-281.
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
41 (5):329-342.
86.
SCHMUCKER DL: Liver function and
phase I drug metabolism in the elderly:
a paradox. Drugs Aging (2001)
18 (11):837-851.
Thomas, Bhattachar, Hitchingham, Zocharski, Naath, Surendran, Stoner & El-Kattan
87.
88.
LIN JH, CHIBA M, BALANI SK et al.:
angiotensin II receptor antagonists.
VON MOLT KE LL, GREENBLAT T DJ:
Species differences in the pharmacokinetics
J. Med. Chem. (2005) 48 (13):4389-4399.
Human drug metabolism and the
and metabolism of indinavir, a potent
cytochromes P450: application and
human immunodeficiency virus protease
relevance of in vitro models. J. Clin.
inhibitor. Drug Metab. Dispos. (1996)
Pharmacol. (2001) 41 (11):1149-1179.
24 (10):1111-1120.
VENKATAKRISHNAN K,
XU C, LI CY, KONG AN: Induction of
98.
99.
phase I, II and III drug
clearance from hepatic microsomal
metabolism/transport by xenobiotics.
metabolism data. Curr. Opin. Drug Discov.
Devel. (2001) 4 (1):36-44.
Arch. Pharm. Res. (2005) 28 (3):249-268.
89.
90.
100. OBACH RS, BAXT ER JG, LISTON T E
(1999):353-398.
et al.: T he prediction of human
SHEWEITA SA, T ILMISANY AK: Cancer
pharmacokinetic parameters from
DAVIES B, MORRIS T: Physiological
NELSON DR, KAMATAKI T,
superfamily: update on new sequences, gene
mapping, accession numbers, early trivial
preclinical and in vitro metabolism data. J.
Pharmacol. Exp. Ther. (1997) 283 (1):46-58.
101. LEWIS DF, DICKINS M: Substrate SARs
in human P450s. Drug Discov. Today (2002)
7 (17):918-925.
102. MANNHOLD R: T he impact of
clearance. Drug Metab. Dispos. (2002)
30 (6):694-700.
110. MORELLO KC, WURZ GT,
DEGREGORIO MW: Pharmacokinetics of
selective estrogen receptor modulators.
Clin. Pharmacokinet. (2003)
42 (4):361-372.
111. HIRAOKA H, YAMAMOTO K,
OKANO N et al.: Changes in drug plasma
on β-blockers. Mini. Rev. Med. Chem.
concentrations of an extensively bound and
(2005) 5 (2):197-205.
to altered plasma binding. Clin. Pharmacol.
lipophilicity in drug research: a case report
103. DRAGOVICH PS, PRINS T J, ZHOU R
highly extracted drug, propofol, in response
Ther. (2004) 75 (4):324-330.
names of enzymes, and nomenclature.
et al.: Structure-based design, synthesis, and
DNA Cell Biol. (1993) 12 (1):1-51.
biological evaluation of irreversible human
et al.: Pharmacokinetics of nalbuphine in
BURCHELL B, EBNER T, BAIRD S et al.:
rhinovirus 3C protease inhibitors. Part 7:
infants, young healthy volunteers, and
structure–activity studies of bicyclic
elderly patients. Clin. Pharmacol. Ther.
2-pyridone-containing peptidomimetics.
(1989) 46 (2):226-233.
Use of cloned and expressed human liver
UDP-glucuronosyltransferases for analysis
of drug glucuronide formation and
assessment of drug toxicity. Environ. Health
Perspect. (1994) 102 (Suppl. 9):19-23.
HOSOKAWA M, MAKI T, SATOH T:
Characterization of molecular species of
liver microsomal carboxylesterases of several
animal species and humans. Arch. Biochem.
Biophys. (1990) 277 (2):219-227.
WIDMAN M, NILSSON LB, BRYSKE B,
LUNDST ROM J: Disposition of
remoxipride in different species. Species
differences in metabolism. Arzneim. Forsch.
(1993) 43 (3):287-297.
BERGMANN JF, LANEURY JP,
DUCHENE P et al.: Pharmacokinetics of
reboxetine in healthy, elderly volunteers.
Eur. J. Drug Metab. Pharmacokinet. (2000)
25 (3-4):195-198.
97.
Characterization of raloxifene
Appleton & Lange, Stamford, CT, USA
WAXMAN DJ et al.: T he P450
96.
Dispos. (2005) 33 (12):1852-1858.
109. KEMP DC, FAN PW, ST EVENS JC:
glucuronidation in vitro: contribution of
10 (7):1093-1095.
95.
for five benzodiazepines. Drug Metab.
intestinal metabolism to presystemic
humans. Pharm. Res. (1993)
94.
human hepatocytes: kinetic characteristics
microsomes in a discovery setting.
parameters in laboratory animals and
93.
of metabolic clearance using cryopreserved
Biopharmaceutics and Pharmacokinetics.
Curr. Drug Metab. (2003) 4 (1):45-58.
92.
••
HAKOOZ N, HOUSTON JB: Prediction
Provides an overview to the use of
SHARGEL L, YU A: Applied
and phase II drug-metabolizing enzymes.
91.
OBACH RS: T he prediction of human
108. HALLIFAX D, RAWDEN HC,
COCCHIARA G, BAT TAGLIA R,
PEVARELLO P,
ST ROLIN BENEDET T I M: Comparison
of the disposition and of the metabolic
pattern of Reboxetine, a new antidepressant,
in the rat, dog, monkey and man.
Eur. J. Drug Metab. Pharmacokinet. (1991)
16 (3):231-239.
Bioorg. Med. Chem. Lett. (2002)
12 (5):733-738.
104. TAGAT JR, MCCOMBIE SW,
112. JAILLON P, GARDIN ME, LECOCQ B
113. WEST ERLING D, PERSSON C,
HOGLUND P: Plasma concentrations of
morphine, morphine-3-glucuronide, and
NAZARENO D et al.: Piperazine-based
morphine-6-glucuronide after intravenous
CCR5 antagonists as HIV-1 inhibitors. IV.
and oral administration to healthy
Discovery of
volunteers: relationship to nonanalgesic
1-[(4,6-dimethyl-5-pyrimidinyl)carbonyl]-
actions. Ther. Drug Monit. (1995)
4-[4-[2-methoxy-1(R)-4-(trifluoromethyl)
phenyl]ethyl-3(S)-methyl-1-piperaz inyl]4-methylpiperidine (Sch-417690/Sch-D),
a potent, highly selective, and orally
bioavailable CCR5 antagonist.
J. Med. Chem. (2004) 47 (10):2405-2408.
105. ZAMORA I, AFZELIUS L,
CRUCIANI G: Predicting drug
metabolism: a site of metabolism prediction
tool applied to the cytochrome P450 2C9.
J. Med. Chem. (2003) 46 (12):2313-2324.
106. CRUCIANI G, CAROSAT I E,
DE BOECK B et al.: MetaSite:
understanding metabolism in human
cytochromes from the perspective of the
chemist. J. Med. Chem. (2005)
48 (22):6970-6979.
107. BERELLINI G, CRUCIANI G,
MANNHOLD R: Pharmacophore, drug
metabolism, and pharmacokinetics models
17 (3):287-301.
114. SHARGEL L, YU A: Applied
Biopharmaceutics and Pharmacokinetics.
Appleton & Lange, Stamford, CT USA
(1999).
115. MASIMIREMBWA CM, BREDBERG U,
ANDERSSON T B: Metabolic stability for
drug discovery and development:
pharmacokinetic and biochemical
challenges. Clin. Pharmacokinet. (2003)
42 (6):515-528.
116. CALABRESE EJ: Suitability of animal
models for predictive toxicology: theoretical
and practical considerations.
Drug Metab. Rev. (1984) 15 (3):505-523.
117. SCHIAVO DM: T he use of laboratory
animals in toxicology: an ophthalmoscopic
assessment. Toxicol. Pathol. (1990)
18 (1 Pt 2):222-223.
on non-peptide AT 1, AT 2, and AT 1/AT 2
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)
607
The road map to oral bioavailability: an industrial perspective
118. WU CY, BENET LZ: Predicting drug
disposition via application of BCS:
transport/absorption/elimination interplay
and development of a biopharmaceutics
drug disposition classification system.
Pharm. Res. (2005) 22 (1):11-23.
Websites
201. http://www.rxlist.com/02top.htm
T he top 200 prescriptions for 2002 by
number of US prescriptions dispensed
(2002).
202. http://www.fda.gov/cder/OPS/BCS_
guidance.htm
T he Biopharmaceutics Classification
System (BCS) guidance (2001).
Affiliation
V Hayden T homas1 , Shobha Bhattachar2 ,
Linda Hitchingham3 , Philip Zocharski4 ,
Maryanne Naath3 , Narayanan Surendran5 ,
Chad L Stoner2 & Ayman El-Kattan†1
† Author for correspondence
1
Senior Principal Scientist, Pfizer Global
Research and Development, Department of
Pharmaceutical Sciences, 2800 Plymouth Road,
Ann Arbor, MI 48105, USA
2
Principal Scientist, Pfizer Global Research and
Development, Department of Pharmaceutical
Sciences, 2800 Plymouth Road, Ann Arbor,
MI 48105, USA
3 Senior Associate Scientist, Pfizer Global
Research and Development, Department of
Pharmaceutical Sciences, 2800 Plymouth Road,
Ann Arbor, MI 48105, USA
4
Senior Scientist, Pfizer Global Research and
Development, Department of Pharmaceutical
Sciences, 2800 Plymouth Road, Ann Arbor,
MI 48105, USA
5
Director, Pfizer Global Research and
Development, Department of Pharmaceutical
Sciences, 2800 Plymouth Road, Ann Arbor,
MI 48105, USA
608
View publication stats
Expert Opin. Drug M etab. Toxicol. (2006) 2(4)