| Research Article |
Open Access |
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| Challenges in Drug discovery: Can
We Improve Drug Development |
| Balakrishnan Arun |
Vice President, External Liason, Screening and Natural Products.
Piramal Life Sciences Limited, 1 Nirlon Complex, Goregaon (East), Mumbai 400063, India |
| *Corresponding author: |
Dr. Balakrishnan Arun
Vice President, External
Liason,
Screening and Natural Products. Piramal Life Sciences Limited,
1
Nirlon Complex, Goregaon (East), Mumbai 400063,India
Tel: +91 22
30818401,
Fax: +91 22 30818411,
E-mail: arun.balakrishnan@piramal.com |
|
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| Received November 23, 2009; Accepted December 22, 2009; Published December 22, 2009 |
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| Citation: Arun B (2009) Challenges in Drug discovery: Can We Improve Drug Development. J Bioanal Biomed 1: 050-053. doi:10.4172/1948-593X.1000011 |
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| Copyright: © 2009 Arun B. This is an open-access article distributed
under the terms of the Creative Commons Attribution License, which
permits unrestricted use, distribution, and reproduction in any medium,
provided the original author and source are credited. |
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| Technology drivers in drug discovery |
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| Scientific advancements in healthcare are driven by innovations
in different areas like, understanding the pathogenesis of
a disease, development of technologies for diagnosis, and treatment
of the disease. The advent of molecular pathogenesis has
helped us to understand the complex mechanisms that are involved
in a specific disease. This change has heralded several
novel discoveries in the area of biological sciences and
healthcare. Bryan et al., (2009); Hart et al., (2009); Matta et
al., (2009). |
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| However, several challenges are unmet and there is always a
need to compensate our resources in fighting to solve issues at
a basic science level and also for the development of new drugs
and new approaches for treatment. This challenge will continue
and despite trying to better ourselves with knowledge,
we appear to be far behind in conquering many diseases. There
is always a quest for new knowledge that is available today for
any specific medical condition. There are several unknowns in
this pursuit, thus finding a novel drug for a disease is always a
challenge. Following the path from discovery of a molecule
through the road of development is complex and involves time,
money and multiple disciplines to move it ahead. |
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| Despite efforts to hasten the process of drug development
using innovative technologies, the current efforts still appear
to be ineffective. Several novel strategies like academia-industry
interactions that foster a conversion of novel technologies to
product and public – private funding etc have not helped to
conquer several diseases. In fact, it appears that the efficiency
has slipped. Therefore, it becomes important to identify the
areas in the development chain that needs to be improved or
methods by which one can hasten the process. |
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| Translation of basic research to development of lead compound |
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| Pharmaceutical industry and drug discovery research applied
all the basic scientific data and have helped develop procedures
and guidelines that enable the conversion of such information
into useful tools that can be used to treat or intervene in
the progression of disease. In order to address the question
why discovery productivity has slipped despite large investments,
several reports indicate that between 2005-2006, the
funding for drug discovery rose from $48billion to $94 billion.
But the curve of submissions of new drugs and biologics to
FDA is in the opposite direction, a mirror image of the investment
curve. The major concern is related mainly to the costs of
preclinical and clinical trials study which is called the critical
path. |
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| Early drug discovery genomics and proteomics driven |
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| The flux of new technologies and the understanding of molecular
biology have created a shift in the way we understand the molecular basis of cell regulation and the parameters that
are affected during the disease process. The advent of genomics
and proteomics and automation of various technologies have
created platforms that can effectively be employed to understand
normal cell functions and the changes during a disease. McHugh et al., (2009); McShane et al., (2009); Rajcevic et
al., (2009). The sequence of the human genome and the functional
proteins that are being understood as cell signal molecules
have all cleared the understanding of growth and differentiation
of a normal cell and also implicate several of these
dynamic molecules in a disease. |
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| Molecular pathogenesis |
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| The complexities in biology and the molecular mechanisms
of normal cell regulation is an area where scientific research
always provides more information. Even though the data in
this area is extremely crowded, there seems to be no stop in the
unending new knowledge that is constantly appearing in cited
literature. It is very well understood that a disease exerts its
effect because of malfunction of these molecules and the arrest
of this dysfunction could help us revert the condition and thus
prevent the disease. Hasko et al., (2008); Oka et al., (2008); Shum et al., (2008). |
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| Grey areas in drug discovery research |
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| Several approaches based on the recent developments in different
areas of modern biology have been targeted to evolve
specific methods that can be used to treat diseases. With this
approach in mind and the development chain as required by
regulators fully understood, the development team of scientists
have been working hard to crack the fundamentals of a
disease and how one can stop or prevent the disease progress. |
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| Why are we behind in drug development |
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| Despite several advancements and huge investments, we are
far behind in this pursuit. There are several reviews that highlight
the difficulties one encounters in the present development
cascades. The question one raises are that, from precise early
discovery experiments, followed by translational studies in various animal models and then to clinical trials, there appears to
be something wrong in this translation. Mager et al., (2009).
All the high end predictions of the molecule based on various
approaches from Chemo informatics modeling and wet lab target
specific approaches like target based drug design, identifying
new targets and applying new targets and identifying novel
molecules from diverse sources both through the synthetic route
and by scanning the biodiversity for novel molecules all appear
to be failing at some level. Koehn, (2008); Rollinger et
al., (2006); Rollinger et al., (2008). The drop out of molecules
when moved through the development chain, despite showing
very promising activities in the invitro models is high. Are these
prediction models wrong or are we not able to translate these
positive compounds invitro into animal models. Is there a way
to increase the percentage of translation or are the animal models
which we are currently employing failing at some level.
These questions are difficult to answer, but an answer to such
difficult questions will be important to make animal experimentation
also precise and more predictive. |
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| HITS to preclinical evaluation in animal models |
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| This clearly points out that the various advancements in early
drug discovery has increased the pipeline for early HITS and
despite our strengths to improve a library of potent compounds
from the biodiversity or specific synthetic chemical libraries,
pipeline of new drugs is diminishing world wide. |
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| But the question is, how can one change the current animal
pharmacological parameters and models in which we are trying
to extrapolate information and study different parameters
that are usually studied to take decisions on whether to take a
molecule forward. Just like how conventional pharmacologist
question the wisdom of target based drug discovery, modeling
and validation on cell lines, a scientist who understands the
precision in such approaches may find it illogical when they
understand on how dose for animal studies are decided and
also sometimes question the validity of such models in relation
to the human disease. The only answer is that there is no
other rationale to examine this idea and how to take a molecule
forward. Just like how biologists questioned the modern developments
in molecular biology, human DNA sequencing and
any precise mechanistic study during the time when these information
were been published, the sceptism in these approaches
were always argued upon. Many of the conventional
physiologists were always opposed to such an understanding
of biologists. But the new information of proteomics and
genomics that evolved out of these findings has definitely contributed
to the early discoveries based on many different approaches. Fabre et al., (2009); Uverdevert et al., (2009); Wentzensen et al., (2009). These approaches will probably
improve our current lacunae in drug discovery. |
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| New approaches in prediction of drug efficacy in clinical
trials |
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| My fear is that, it’s time that we exploit some of the modern
approaches and try to improve the development studies using
better approaches in animal pharmacology, developing non invasive
techniques, applying knowledge in the areas of
biomarkers to hasten the understanding of the positive and negative
effect of molecules in invivo pharmacology and reduce the time lines of such development. Greinert, (2009), Hasko et
al., (2008); Mullar, (2009); Wentzensen et al., (2009). The lacunae
is that, now we have shifted our pipeline where we have
large number of potent HITS which can be developed further
into a space were we still rely on primitive modes of selection
criteria, animal models and approaches, where we need to apply
the wisdom of modern molecular biology and
pharmacogenomics information to translational studies, thus
reducing the cost and also improve the bottle neck and selection
criteria which will be more fool proof and robust. Fabre et
al., (2009); Greinert, (2009); Uverdevert et al., (2009). I believe
that the general argument that one molecule in five thousand
molecules will become a drug can be improved if we develop
rationale ways to defining animal experimentation,
interspacing such studies with the modern concepts of molecular
understanding of a disease and rationalize modalities by
which we can hasten the process, such that more molecules
which are defined as robust can be taken into clinics faster and
with a clear understanding of the mode of action. Auffray et
al., (2009); Mullar, (2009); Van et al., (2009). |
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| Currently, 50% lower submission of new drug applications
is noted compared to a decade earlier. NCE’s reaching markets
annually have declined, clinical failure rates have climbed well
above historic averages and mainly failures in Phase III trails
have risen dramatically. What can be the reasons? Can we improve
upon selection of compounds by novel technologies,
which will help us to understand the negativities of a molecule
in trial better before inducting it into clinical trials. |
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| High end technology platforms |
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| High-end platforms like microarray and real time PCR have
all helped us to progressively move forward to understand the
complications of control under normal situations and then compare
it during a disease. These molecular studies have paved
the way for us in pharmaceutical research to employ such target
to effectively combat a disease. Auffray et al., (2009); Chen
et al., (2009); Stimson et al., (2009); Uverdevert et al., (2009); Van et al., (2009). But despite these approaches wherein molecular
mechanisms are reversed by small molecules are the
major route of development of a drug, the translation of such
invitro phenotypic and target based assays still lead to major
failures when such active molecules are tested on animal models.
Several reasons have been used to explain this defect in
translation of many of the invitro positives into animal systems
and the main causes are the absorption parameters or degradation
of the molecule in the invivo situations. These problems
are however addressed by the chemists and by developing
SAR’s around the new scaffold one can turn around the situation
and thereby produce novel molecules that are effective in
the invivo situation. However, despite the availability of effective
technologies one can see a narrowing of the funnel during
animal experimentation and obtaining good invivo parameters.
This should be an area where one should put in new thoughts
and ideas wherein we can improve the speed of assessment
using such animal models. Can we rely on specific markers
that can be used to address the effectiveness of the molecule
invivo. |
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| The other major lacunae both in terms of time and money
are the studies in humans. The translation from animal models to human trials is also a major problem, because in most cases
what one sees in animals need not be the case in the humans
and despite all the effective controls we take to design an animal
studies we will end up in toxicity during long term studies. Auffray et al., (2009); McHugh et al., (2009); McShane et al.,
(2009); Rajcevic et al., (2009); Van et al., (2009). |
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| Prediction of behaviour of molecules in clinic: biomarkers |
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| Can we predict on how the molecule will respond in human
trials using the modern technologies available. This will help
us to cut short clinical trials in terms of years and in terms of
cost. Auffray et al., (2009); Chen et al., (2009); Greinert, (2009);
, Stimson et al., (2009); Van et al., (2009); Wentzensen et al.,
(2009). |
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| Predicting human clinical efficacy is a complex challenge
and can be addressed if the mechanism of action of the drug
and the target can be validated. The novel approaches available
today can be exploited to study the compound action.
Between 1991 to 2001, the failure in drug discovery has been
attributed to pharmacokinetics reasons, absorption, and destruction
of tissue, localization, duration of action and excretion
problems. The current reasons of drug failures are mainly due
to toxicology and clinical safety, even target-based discovery
approaches does not seem to have eased the solution. Thus,
pharmaceutical industry faces unprecedented challenges, as
number of new molecule entities approved by FDA has stagnated
during this period. Hence, we believe there is a growing
need to modernize drug development process and incorporate
advance in science and technology into a new development
model. |
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| Pharmacogenomics in clinical design |
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| Although a great deal of information can be obtained from
invitro phenotypic and target based assays on the possible
mechanism of action of a small molecule. It is still difficult to
predict whether these molecules, which are so effective invitro,
can really pass through several of the preclinical studies. Fabre
et al., (2009); Rollinger et al., (2008); Taketo et al., (2009). Is
there a way to improve the prediction and improve the effectiveness
of animal studies. Pharmacological studies surely do
give us immense confidence and measures that enable us to
translate the effects from animal models to Humans. Abreu et
al., (2007); Hegen et al., (2007); Shum et al., (2008); Uverdevert
et al., (2009). This could be an area where technology, information
on molecular biology and clinical pharmacology can
all work together to evolve better prediction models which will
then be useful to improve the information on the action of such
molecules in a dynamic situation where several of the pharmacological
parameters will assess the potential of the molecule
to move forward in the development chain. |
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| In order to effectively improve the success of molecules in
trials, predicting human clinical efficacy is a complex challenge.
Utlising the molecular concepts of understanding disease,
we must address to identify truly therapeutic targets, prioritize
those targets and set scientific foundation for future
decisions including trial design. Targets with high probability
of clinical efficacy would progress in the pipeline. Extrapolation
of data from an isolated biological response of a gene or a
molecule level to a system side effects of response will help us in prediction of clinical efficacy of a compound and also predict
the side effects. Methods to improve prediction of clinical
efficacy is an application that needs to be addressed, only then
the applications of smart technologies in early phase of drug
discovery can be translated smoothly into the clinics. |
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| Acknowledgements |
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| My sincere thanks to Ms.Sheila Vaz for her typographical
and editorial assistance of this document. The author also acknowledges the valuable support of Dr Somesh Sharma, Managing Director, Piramal Life Sciences Limited |
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