| Frontiers
in Drug Design and Discovery
ISBN: 90-77527-03-6
Upcoming Articles
Present and Future Mass Spectrometry-Based Approaches
for Exploratory Drug Metabolism and Pharmacokinetic Studies
Yunsheng Hsieh
[Abstract]
Methylphenidate Extended-Release Capsules: A New Formulation
for Attention-Deficit Hyperactivity Disorder
Pilar García-García, Francisco
López-Muñoz, Juan D. Molina, Roland Fischer
and Cecilio Alamo
[Abstract]
Across Skin Barrier: Known Methods, New Performances
Krzysztof Cal
[Abstract]
Important Drug Interactions for Clinical Oncologists
Hiroshi Ishiguro, Ikuko Yano and Masakazu Toi
[Abstract]
Pharmacogenomic Considerations in Breast Cancer Management
Hiroshi Ishiguro, Ikuko Yano and Masakazu Toi
[Abstract]
New Sampling Techniques for Pharmacokinetic-Pharmacodynamic
Modeling
Christian Höcht, Marcos Mayer, Javier A.W.Opezzo,
Guillermo F. Bramuglia and Carlos A. Taira
[Abstract]
The Tape Stripping Method as a Valuable Tool for Evaluating
Topical Applied Compounds
J.J. Escobar-Chávez, L.M. Melgoza-Contreras, M.
López-Cervantes, D. Quintanar-Guerrero and A. Ganem-Quintanar
[Abstract]
A Review on Virtual Reality and Haptics Approaches
in Drug Design and Discovery
Susana K. Lai-Yuen
[Abstract]
Advances in ADMET Predictions and Modelling: Rapid
Drug Discovery Efforts in 21st Centuries
Mahmud Tareq Hassan Khan
[Abstract]
Glutathione Transferases in Drug Discovery And Development:
Towards Safer and Efficacious Drugs
Katholiki Skopelitou, Dimitris Platis, Irene Axarli and
Nikolaos E. Labrou
[Abstract]
Computational Intelligence Methods for ADMET Prediction
David Hecht and Gary B. Fogel
[Abstract]
Role of Inflammatory Biomarkers in Establishing PK/PD
Relationships and Target Organ Toxicity
Sivaram Pillarisetti and Ish Khanna
[Abstract]
Data Modeling and Chemical Interpretation of ADME
Properties Using Regression and Rule Mining Techniques
Kiyoshi Hasegawa and Kimito Funatsu
[Abstract]
Abstracts
[Back to top]
Present and Future Mass Spectrometry-Based Approaches
for Exploratory Drug Metabolism and Pharmacokinetic Studies
Yunsheng Hsieh
For more than a decade, mass spectrometry (MS) has played
an important role in absorption, distribution, metabolism,
excretion and toxicology (ADMET) studies for drug discovery
to help convert lead compounds into drug candidates. Drug
discovery efforts have been focused on identifying drug metabolism
and pharmacokinetic (DMPK) issues at the earliest possible
stage to reduce attrition rate of drug candidates throughout
the drug development process by applying cutting edge MS-based
techniques. These emerging techniques have proven to be extremely
valuable to accelerate the lead optimization and characterization
processes by eliminating potentially unpromising candidates.
In this article, the current MS-based approaches and their
future perspectives in supporting exploratory DMPK studies
including in vitro and in vivo pharmacokinetic
profiling, physical property, metabolite identification and
molecular imaging tests are reviewed.
[Back to top]
Methylphenidate Extended-Release Capsules: A New Formulation
for Attention-Deficit Hyperactivity Disorder
Pilar García-García, Francisco
López-Muñoz, Juan D. Molina, Roland Fischer
and Cecilio Alamo
In recent years Attention Deficit Hyperactivity Disorder (ADHD)
has been the focus of growing interest, and different drugs
have been introduced for its treatment. Thus, there is a range
of medication for ADHD, but new formulations are necessary
for more individualized therapy. The choice will depend upon
the circumstances and detailed assessment. A new extended-release
formulation of methylphenidate (Medikinet®)
has increased the drug-delivery treatment options for ADHD.
Medikinet® combines the advantages of immediate-release
(IR) and extended-release (ER) formulations of methylphenidate,
with rapid onset and prolonged duration of action (7-8 h),
in a single dose intended for once-daily administration. The
concentration-time profile is achieved through the particular
formulation of Medikinet®, whose
hard-gelatine capsule contains 50% enteric-coated and 50%
uncoated pellets, providing both a first, immediate release
and a second, delayed release. The coated pellets only dissolve
at a pH > 5.5 and release the active drug in a sustained
way into the intestine. There is no difference in the bioavailability
of the IR/ER product when administration follows a normal
or high-calorie breakfast. Medikinet®
also shows a bioavailability comparable to that of the b.i.d.
10 mg immediate release regime, as well as a high level of
efficacy and good tolerability. In this review, we describe
the pharmacokinetics of Medikinet®
and compare its characteristics with those of other formulations
used for treating ADHD.
[Back to top]
Across Skin Barrier: Known Methods, New Performances
Krzysztof Cal
Skin is still the desirable route for the delivery of drug
substances into the human body. Transdermal drug delivery
offers many advantages over the conventional oral route of
application, such as the elimination of hepatic first-pass
effect, reduced side effects, constant concentration of a
drug in the blood. Human intact skin is normally permeable
for molecules with log P in the range of 1-3, smaller than
500 Da and present in a unionized form. Usually, obtained
fluxes of drug substances are too low for the induction of
systemic therapeutic effects. It is caused by the specific
structure and composition of the outer layer of the skin –
the stratum corneum. Closely packed, built as “brick”
(corneocytes) and “mortar” (lipid bilayers), the
stratum corneum is the most important limiter for transdermal
drug delivery. Molecules that permeated the stratum corneum
are easily taken up by capillary vessels present in the deeper
skin layers. This chapter presents different methods used
for skin permeation enhancement. Various drug forms and carriers,
chemical permeation enhancers, electrically supported methods
and devices, and the stratum corneum bypassing or removing
methods are described, and the recent achievements in the
field and possible practical use in market products are discussed.
The special subchapters are dedicated to the skin disposition
of one of the most often used penetration enhancers –
terpenes, and the use of cyclodextrins in formulations applied
onto the skin.
[Back to top]
Important Drug Interactions for Clinical Oncologists
Hiroshi Ishiguro, Ikuko Yano and Masakazu Toi
Drug interactions can cause severe side effects and lead to
early termination of drug development, refusal of drug approval,
prescribing restrictions or drug withdrawal from the market.
Of drugs used to treat humans, cytotoxic anti-neoplastic drugs
have a particularly strong action. Furthermore, they have
a complex pharmacological profile, a narrow therapeutic window,
and a steep dose-toxicity curve, and are associated with considerable
inter- and intra-patient pharmacokinetic and pharmacodynamic
differences. The recommended dose is usually close to the
maximally tolerated dose in order to achieve the maximum therapeutic
effect. Thus, some adverse effects are usually inevitable,
so these drugs are approved for usage based on a clinical
risk to benefit ratio. Therefore, drug interactions affecting
the pharmacokinetics of anti-neoplastic drugs are of particular
concern. Any physicians treating oncology patients must understand
the pharmacokinetic behavior (absorption, distribution, metabolism,
excretion, etc.) of a drug, as well as the factors affecting
its pharmacokinetic behavior, for example the effects of concomitantly
administered drugs, and hepatic and renal function. Medical
oncologists must have expertise in achieving a good balance
between safety and efficacy in medical treatment, with a proper
knowledge of supportive care and an understanding of pharmacokinetics,
pharmacodynamics and pharmacogenomics. We summarize the drug
interactions that are important in day-to-day oncology practice.
We cover pharmaceutical interactions at the levels of absorption,
distribution, metabolism and excretion. This review is the
one of the most comprehensive to date in the field of clinical
oncology, where the level of understanding of drug interactions
can directly affect patient management.
[Back to top]
Pharmacogenomic Considerations in Breast Cancer Management
Hiroshi Ishiguro, Ikuko Yano and Masakazu Toi
Many factors affect an individual’s response to a drug,
and large inter-ethnic, intra-ethnic, and even intra-individual
variations exist. These variations may affect both the therapeutic
response to a drug, or the side effects that the patient experiences.
Since anti-neoplastic drugs often have a very narrow therapeutic
range, it is very desirable to be able to predict these variations
in response or to ensure that these variations are as small
as possible. It has recently become possible to predict some
extreme responses, such as severe side effects, using pharmacogenomic
approaches; for example, the uridine diphosphate-glucuronosyltransferase
(UGT) 1A1 genetic polymorphism is a predictor of irinotecan
toxicity. Further, adding pharmacokinetic and pharmacodynamic
information may increase the accuracy of response prediction.
Both severe toxicity and clinical benefit can be predicted
using a combination of pharmacogenomic and pharmacokinetic
information. For example, the clinical benefit obtained from
adjuvant treatment with tamoxifen is reduced in patients who
have either a particular cCytochrome P450 (CYP) 2D6 genetic
polymorphism or who are taking paroxetine, a strong inhibitor
of CYP2D6. It is possible to monitor pharmacodynamic parameters,
such as serum estrogen levels, as a measure of the therapeutic
effect of aromatase inhibitors. In this review, we summarize
current knowledge in the field of pharmacogenomics as it relates
to breast cancer, focusing particularly on clinical data.
[Back to top]
New Sampling Techniques for Pharmacokinetic-Pharmacodynamic
Modeling
Christian Höcht, Marcos Mayer, Javier A.W.Opezzo,
Guillermo F. Bramuglia and Carlos A. Taira
Considering that pharmacokinetic–pharmacodynamic (PK–PD)
modeling describes the relationship between tissue concentrations
of drugs and their corresponding pharmacological response,
an important issue of PK-PD studies is the availability of
powerful sampling techniques that allow measurement of tissue
concentrations of drugs at multiple time points. Traditional
sampling techniques, including biopsy, blood and saliva sampling,
and skin blister sampling, have several limitations for drug
monitoring during PK-PD studies, considering that these techniques
did not allow the measurement of drug concentrations at the
site of action. In the last decades, new sampling techniques,
including membrane based techniques (microdialysis and ultrafiltration)
and imaging techniques (positron emission tomography and magnetic
resonance spectroscopy), have been available for measurement
of drug concentration at the target site. The possibility
of simultaneous monitoring of target site concentrations of
drugs and their pharmacological effect with these new sampling
techniques have significantly improves current knowledge of
PK-PD modeling. In addition, membrane based techniques also
allow simultaneous monitoring of endogenous compounds and
therefore permit the study of the relationship between drug
target site concentrations and their effect on biochemical
markers, making these techniques highly useful for PK-PD modeling
studies. The aim of this chapter is to describe the principles
of membrane based techniques and imaging techniques, and their
applicability for drug monitoring in PK-PD modeling.
[Back to top]
The Tape Stripping Method as a Valuable Tool for Evaluating
Topical Applied Compounds
J.J. Escobar-Chávez, L.M. Melgoza-Contreras, M.
López-Cervantes, D. Quintanar-Guerrero and A. Ganem-Quintanar
Quantification of drugs within the skin is essential for topical
and transdermal delivery research. Over the last two decades,
horizontal sectioning, consisting of tape stripping throughout
the stratum corneum, has become one of the traditional investigative
techniques. Tape stripping of human stratum corneum is widely
used as a method for studying the kinetics and penetration
depth of drugs.
The Food and Drug Administration released a draft guidance
proposing a Dermatopharmacokinetic method for evaluating bioavailability
and/or bioequivalence of topical dermatological drug products.
As specified in this document, the method measures topically
applied drug levels in the outermost layer of the skin, the
stratum corneum, as a function of time post-application and
postremoval of the formulation, so as to generate a stratum
corneum concentration versus time profile. The stratum corneum
is collected by successive application and removal of adhesive
tape providing a minimally invasive technique by which the
drug’s concentration in the skin can be determined.
The Dermatopharmacokinetic method assumes that: (i) in normal
circumstances, the stratum corneum is the rate-determining
barrier to percutaneous absorption, (ii) the stratum corneum
concentration of drug is directly related to that which diffuses
into the underlying viable epidermis, and (iii) Stratum corneum
drug levels are more useful and relevant for assessing local,
dermatological efficacy than plasma concentrations.
This paper shows the applications of the tape stripping technique
to evaluate drug penetration through the skin as well as stratum
corneum composition and physiology, underlining its versatile
application in the area of topical and transdermal drugs.
[Back to top]
A Review on Virtual Reality and Haptics Approaches
in Drug Design and Discovery
Susana K. Lai-Yuen
Virtual reality interfaces and haptics are rapidly becoming
a powerful technology to enable researchers to interactively
manipulate and evaluate potential drug molecules in an immersive
virtual environment to accelerate the drug design process.
Virtual reality refers to a computer-generated and
interactive three-dimensional environment that immerses people
into a virtual world while haptic devices are electromechanical
devices that exert forces on users giving the illusion of
touching something in the simulated environment. As molecular
forces play a major role in determining the successful docking
of drug molecules, virtual reality and haptics can provide
researchers with invaluable human-computer interface tools
for visualizing, manipulating, and “feeling” complex
molecular systems in real time. The force feedback provided
by haptic devices can direct researchers towards favorable
drug molecule positions and orientations increasing the understanding
of key forces during molecular interactions and enabling new
kinds of drug design exploration. However, the main difficulty
of modeling molecular systems through virtual reality and
haptics is that visualization models and simulations need
to be processed rapidly to satisfy the update requirements
needed for real-time visualization and sense of touch. Any
time delay between a user action and the corresponding update
of the virtual object can lead to unrealistic visualization,
unstable force response, and simulation sickness. This paper
reviews some of the research advances for addressing these
computational challenges ranging from new graphical representations
of molecules for effective haptic force feedback calculation
to virtual reality algorithms and devices for modeling complex
molecular systems in a real-time virtual environment.
[Back to top]
Advances in ADMET Predictions and Modelling: Rapid
Drug Discovery Efforts in 21st Centuries
Mahmud Tareq Hassan Khan
A large number of compounds in the development stage
got failure due to the unfavourable ADMET (absorption, distribution,
metabolism, excretion and toxicity) profiles. The utilities
of ADMET properties are becoming progressively more imperative
in the drug discovery processes, assortment, development and
promotion processes. In recent years several review papers
have been published about the possibilities of the prediction
or the ADMET properties using different structural features
of the molecules, i.e., molecular descriptors, and
utilizing multiple approaches. One of the most important approaches
is QSAR modelling of the data derived from their activity
profiles and their different structural features (i.e., quantitative
molecular descriptors). More and more efforts are put to the
field of ADMET predictions. This chapter will critically assess
some of the most important and recently reported topics for
the effective in silico predictions of the ADMET
properties of the potential drug candidates based on QSAR
modelling approaches.
[Back to top]
Glutathione Transferases in Drug Discovery And Development:
Towards Safer and Efficacious Drugs
Katholiki Skopelitou, Dimitris Platis, Irene Axarli and
Nikolaos E. Labrou
Glutathione transferases (GSTs) are enzymes involved
in cellular detoxification by catalysing the nucleophilic
attack of glutathione (GSH) on the electrophilic centre of
a number of electrophilic compounds of both endogenous and
exogenous origins. This conjugation reaction usually makes
the electrophilic substrates more water soluble and, thereby,
facilitates their excretion from the body. Determination of
metabolic properties of a new chemical entity (NCE) is one
of the most important steps during the drug discovery and
development process. Nowadays, in vitro methods are
used for early estimation and prediction of in vivo
metabolism of NCEs. In this review detailed descriptions are
given of several biotransformation reactions catalyzed by
GSTs that can be used at very early phases of drug development,
thereby enabling unsuitable candidates to be eliminated from
consideration much earlier in the drug discovery process.
Knowledge of the structure-function relationships in classes
of compounds that are substrates for GSTs enables the design
of molecules that can be stable, or labile which has potential
applications in drug and prodrug design.
[Back to top]
Computational Intelligence Methods for ADMET Prediction
David Hecht and Gary B. Fogel
Quantitative structure-property relationship (QSPR)
models have proven to be an effective approach for increasing
the efficiency of small molecule drug discovery and development
processes. Despite their importance to drug discovery, difficulties
remain in the appropriate selection and weighting of descriptors,
determination of appropriate descriptor combinations, and
optimization strategies that can increase the value of QSPR
models. Here we review the utility of some of the more popular
applications of computational intelligence to QSPR modeling
including: artificial neural networks, fuzzy logic, and evolutionary
computing.
[Back to top]
Role of Inflammatory Biomarkers in Establishing PK/PD
Relationships and Target Organ Toxicity
Sivaram Pillarisetti and Ish Khanna
High levels of inflammatory cytokines and adhesion
molecules are associated with many inflammatory disorders
[e.g. rheumatoid arthritis, inflammatory bowel disease and
lupus] as well as metabolic and cardiovascular diseases including
diabetes and obesity. Examples of such markers include tumor
necrosis factor [TNFα],
interleukins [IL-1, IL-6, IL-8 and IL-18], vascular cell adhesion
molecules and markers of macrophage inflammation [e.g. MMPs].
In many preclinical disease models, levels of these markers
are significantly elevated relative to normal animals. Modulation
of these biomarkers with pharmaceutical agents in preclinical
and clinical studies can be effectively used for concept validation,
effective dose selection, and establishing good pharmacokinetics/pharcodynamics
correlation. On the other hand, elevation of these markers
in normal animals, following treatment with an agent, could
indicate safety concerns leading to potential tissue damage.
Monitoring of inflammatory markers in normal animals can be
diagnostic and of high value in evaluating safety or efficacy
of new molecules. The levels of biomarkers can be monitored
either by high throughput microarrays/proteomics or by specific
ELISA based assays. Since many of the biomarkers appear in
systemic circulation, these can be monitored in blood/plasma
without interference with tissues. This makes the approach
particularly attractive for clinical studies. An overview
of the biomarkers, potential applications and case histories
linking biomarkers to PK/PD correlation from preclinical and
clinical studies are discussed.
[Back to top]
Data Modeling and Chemical Interpretation of ADME
Properties Using Regression and Rule Mining Techniques
Kiyoshi Hasegawa and Kimito Funatsu
In pharmaceutical industry, in addition to high potency, good
absorption, distribution, metabolism and excretion (ADME)
profiles of compounds are needed for drug development. Data
modeling of ADME model is a crucial step for efficient drug
design. However, we have to avoid so called a situation, the
black box, which might be difficult for chemical interpretation.
The right balance between precision and interpretation is
required for practical drug design.
We review the related articles to focus several ADME modeling
techniques. As regression, multiple linear regressions (MLR),
partial least squares (PLS), artificial neural networks (ANN),
support vector machines (SVM) are picked up and their algorithms
and the representative applications are introduced. We pay
attention to rule mining methods for chemical interpretation.
As rule mining, rough set theory (RST) is shown as an example.
Visualization is a classical but never neglected technique
for easily understanding the overall behaviors of huge compounds.
We especially spend more pages about kohonen neural networks
(KNN) and decision trees (DT) as the representative methods.
Furthermore, web application for chemists is another important
aspect for practical drug design. Recent trend about this
topic is shown in two industry cases. As conclusion, we will
show future direction concerning in silico ADME
prediction.
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