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European Biopharmaceutical Review
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Rasika Ramachandran at Frost & Sullivan examines the impact that biomarkers are having on clinical trials
The pharmaceutical industry currently faces mounting pressure from
an array of issues such as revenue loss from patent expirations, more
stringent regulatory requirements and healthcare systems that are
becoming increasingly cost-sensitive. The most apparent solution to
these problems that are restricting the growth and advancement of the
healthcare and pharmaceutical industry is to significantly improve the
quality of innovative medicines and increase the number of such
products, without incurring R&D costs that are unsustainable.
However, as much as these solutions have been recognised over the last
few years, a visible improvement in the R&D productivity of drugs
has yet to be realised. A range of strategies are being implemented by
companies to deal with the critical productivity quagmire that the
industry is currently in.
SKY-ROCKETING DRUG DEVELOPMENT COSTS
One of the key issues that is instrumental in driving up the cost
of drug development is the attrition of drugs, made worse by the fact
that this often occurs at a late stage of drug development when a very
sizeable and irretrievable cost has already gone into the project.
Phase II and III clinical trials are the key stages at which a majority
of drugs have been found to fail. It has been estimated that only a
meagre eight per cent of drugs that complete Phase I are successful in
garnering regulatory approval. This is an alarmingly low number when
compared with the astronomical expenditure that is incurred. The main
reason for this has been the inability of the pharmaceutical industry
to predict the performance of the drug candidate at an early stage to
the required degree of certainty.
BIOMARKERS:MULTIPLE BENEFITS
Biomarkers are fast becoming an essential part of clinical
development. The fact that the pharmaceutical industry has been
proactive in realising the benefits of using biomarkers at every stage
of the drug discovery process and its clinical development has
contributed to this success. Biomarkers offer a much faster alternative
to the conventional drug development approach. In a nutshell, the
myriad applications offered by biomarkers include early disease
identification, potential drug target identification, predicting the
response of patients to medication, aiding in the realisation of
personalised medicine and helping to accelerate clinical trials, to
name but a few. Figure 1 shows the applications of biomarkers at every
stage of clinical drug development
BIOMARKERS IN CLINICAL TRIALS
The use of biomarkers to identify patients that are most likely to
respond to a given drug, be it for the sake of clinical trials or for
treatment, is known as patient stratification. It has been an age-old
practice of the pharmaceutical industry to gauge the performance and
effectiveness of new medicines using clinical outcome or a clinical
endpoint as a measure. A clinical endpoint is a characteristic or
variable that reflects how a patient feels or functions, or how long a
patient survives. However, with the emergence of different kinds of
biomarkers, a novel and faster option is presented to them: biomarkers
can be used as surrogate end-points and are conveniently referred to as
surrogate biomarkers. A surrogate endpoint is a biomarker that is used
in therapeutic trials as a substitute for a clinical endpoint and is
expected to predict the effect, or its lack thereof, of the therapy.
In effect, although the terms ‘surrogate endpoint’ or ‘surrogate
biomarker and stratification biomarkers’ are often used
interchangeably, these two biomarkers perform different functions.
While stratification biomarkers are used for the selection of patients
for clinical trials during the initial stages of patient selection
itself, surrogate biomarkers are indicative of a surrogate end-point
and are used in stages that are further downstream of patient
selection.
A good example of where a biomarker was successful in both the
clinical selection and subsequent clinical trials of a particular drug
was for the chemotherapy drug irinotecan (Camptosar). Irinotecan is
used for the treatment of patients suffering from advanced colorectal
cancer. It was discovered that once the drug was administered, it is
converted to the active metabolite SN-38, and later inactivated by
UGT1A1 enzyme. The toxicity caused by this conversion became a matter
of concern. Thus, in 2005, the US FDA added a warning to the label of
the drug, stating that patients homozygous for a particular version of
the UGT1A1 gene – the UGT1A1*28 allele, associated with decreased
UGT1A1 enzyme activity – should be given a reduced dose. This decision
was guided by the rationale that because patients with this allele
clear the drug less quickly from their system than the rest of the
population, they effectively receive a greater exposure to the drug
from the same dose. As a result, they are exposed to a greater risk of
potentially life-threatening side effects such as neutropaenia, which
is a decrease in white blood cells, and diarrhoea (1).
After this experience, clinicians are now better prepared to
identify patients who are at a high risk of dangerous side effects such
as neutropaenia, as it has been found that about 10 per cent of the
population are homozygous for UGT1A1*28. This pharmacogenomics
information helped not only the case for irinotecan, but also prompted
the use of UGT1A1 biomarkers in subsequent clinical trials for other
new irinotecan-based chemotherapy regimens (2).
THE CLINICAL & ECONOMIC DYNAMICS OF STRATIFICATION BIOMARKERS
Due to the acute buzz about the benefits of biomarkers in clinical
trials, it is easy to misinterpret the issue and believe that all
biomarkers can be used for stratified medicine. There are certain
criteria that a particular biomarker needs to satisfy in order for it
to be of use for patient stratification. Three key factors are
necessary for the emergence of a clinically relevant patient subclass
and consequently stratified medicine:
- A biological characteristic with the potential to induce differential patient responses to a therapy
- Multiple therapeutic options that have sufficiently heterogeneous responses
- An appropriate clinical biomarker that can link therapies to a
subset of patients that are more likely to show that different response
That said, parts of the criteria have been discussed in the past for
the development of stratified medicine in addition to the above stated
criteria for a biomarker to qualify as a stratification marker. These
include the technical feasibility of identifying a patient
sub-population, the need for the economics of the project to be
attractive, and finally, a sustainable franchise (3).
As in the instance of irinotecan, biomarker-based clinical selection of
patients in the past has always been retrospective; this is because,
until recently, only when a drug has failed in certain populations and
succeeded in others have the pharmaceutical companies gone back to
investigate the cause of failure. However, these days, with the
emergence of toxicity biomarker panels, the use of biomarkers has been
more proactive. This practice is expected to percolate to the use of
the more specific stratification biomarkers, as more are being actively
sought out during the course of drug discovery and preclinical
development itself.
As for the economic viability and attractiveness of stratified
medicine, it is expected that drug development costs will be
significantly lower than the traditional empirical model. This is
because, due to patient stratification, the required clinical trial
sizes might be smaller, as the patients will already have been
pre-selected for certain pre-existing parameters, such as the presence
of a certain gene or enzyme. The overall number of clinical trials
could also be substantially lowered, if stratification biomarkers are
adopted. Ultimately, this will lead to faster review cycles by the
regulatory authorities. A good example of this is imatinib, which was
approved by the FDA in three months – a remarkable speed compared to
the historical approval rates that have been prolonged to several
years. Also, the total time that elapsed between first human dose and
FDA approval was less than four years. In addition, it is important to
factor in the cost of the validation of a clinical biomarker for
regulatory approval as a diagnostic.
BLOCKBUSTER MODEL VERSUS STRATIFIED MEDICINE?
The pharmaceutical industry is used to the blockbuster model, which has
done wonders to the revenues of these companies, consistently making
them billions of dollars per annum. This model could be affected by the
adoption of the stratified medicine model as the drug will only be
effective in a selected population. The industry can however find peace
in the knowledge that drug use will be wider and more informed due to
higher drug effectiveness. Big savings will also be realised from fewer
drug recalls and legal payments to people who have suffered from
adverse side-effects, as these will also be significantly lower. The
economics of stratified medicine in its worst form, however, could even
discourage the development of certain treatments because of the fear of
a smaller market and therefore severely affected revenues.
The diagnostic industry stands to gain massively from the use of a
diagnostic along with or before the prescription of a therapy. This
combination of diagnostics and therapy is often known as
‘theranostics’. The power of good diagnostics is such that it can even
increase the uptake of the therapy. Therefore the development of
diagnostics for therapy is mutually beneficial for both the
pharmaceutical and the diagnostic industry.
CONCLUSION
From all these ramifications of stratified medicine, one fact emerges
more clearly than anything else: the cost of a drug developed using
patient stratification and prescribed along with a diagnostic is
definitely going to be higher than the conventional medicines that have
been in the market for time immemorial. There are several other
considerations that also need to be made, such as regulatory and
reimbursement issues and matters of public policy. But one irrefutable
point is that stratified medicines are bound to bring out better and
more effective medicines and are here for the long run.
References
- O’Dwyer PJ and Catalano RB, UGT1A1 and irinotecan: practical pharmacogenomics arrives in cancer therapy, Journal of Clinical Oncology 24 (28), October 2006
- Pfizer, Background Document on the UGT1A1 Polymorphisms and
Irinotecan Toxicity: ACPS November 3, 2004 Advisory Committee Meeting,
published on the FDA website at
www.fda.gov/ohrms/dockets/ac/04/briefing/2004-
4079B1_07_Pfizer-UGT1A1.pdf
- Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers, Nature Reviews Drug Discovery 6, April 2007
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