Bringing a drug from bench to bedside is a risky and expensive proposition. The development of a new drug is estimated to cost many hundreds of millions of dollars; as a result, decisions about funding a drug-development program are based as much on economics as on science and medicine.2Decisions to invest and reinvest at all stages of development are driven by the imperative to generate an attractive return on the capital invested, whether by venture-capital and public investors or by pharmaceutical companies.
It
is not mysterious why projects get funded. As venture-capital
investors, we evaluate projects along four primary dimensions:
development costs, selling costs, differentiation of the drug relative
to current treatments, and incidence and prevalence of the targeted
disease (see table.
For a project to be attractive, it needs to be favorably reviewed on at
least two of these dimensions. Many drugs designed for orphan diseases
and cancers are good investments of scarce capital, since they tend to
have relatively low development costs and selling costs and to be
strongly differentiated from the current treatment options. Conversely,
investors are less likely to fund drugs with much higher development and
selling costs (e.g., drugs for type 2 diabetes or psychiatric
disorders) and drugs that cannot be strongly differentiated from current
treatment options — often because low-cost generics are available to
treat the targeted condition — despite the condition's high incidence
and prevalence (e.g., drugs for hypertension or hypercholesterolemia).
Fortunately,
much can be done to bring more drugs and a more diverse set of drugs to
market. The two economic dimensions — development costs and selling
costs — can be most easily improved. The most expensive step in creating
a new drug is conducting clinical trials. Conducting a trial costs
$25,000 or more per patient studied, and phase 3 trial programs consume
more than 40% of a sponsoring company's expenditures.3 Unfortunately,
every patient is not equally valuable when it comes to clinical trials,
and many clinical development programs are economically inefficient in
that they are excessively large relative to the amount of information
they yield, especially in light of the information-technology
breakthroughs that have lowered the cost of data acquisition and
analysis over the past 20 years. Changing the capacity for
differentiation or changing the incidence and prevalence of disease
requires breakthroughs in science that can be influenced only indirectly
through investments in basic science research.
High-frequency,
material information about clinical efficacy and safety comes from the
first few hundred patients studied in a trial. Unfortunately, most
clinical development programs go far past the point of diminishing
returns for frequent safety events, but they do not go far enough to
permit detection of rare events.4 Statistically,
it is only in the long tail of patient data that reliable signals of
rare adverse effects can emerge and comprehensive safety can be
established (as demonstrated, for example, by the finding of progressive
multifocal leukoencephalopathy in patients taking Tysabri
[natalizumab]). Safety is critical, but studying the long tail of
adverse events is not feasible from either a time or a capital
perspective until after a new drug enters the market, especially if the
drug is for a chronic condition.
Redesigning
trials to include fewer patients, providing conditional approval of
drugs, and requiring postmarketing surveillance could have a profound
effect, allowing smaller development programs to achieve greater
success. We estimate that development costs for drugs could be reduced
by as much as 90%, and the time required by 50%, if the threshold for
initial approval were defined in terms of efficacy and fundamental
safety. Cutting costs and time, while requiring high-quality and
transparent patient registries for independent safety monitoring, would
be a more informative and cost-effective approach. With the widespread
adoption of electronic health records and the introduction of many
low-cost data-analysis tools, it is now feasible to develop mandatory
postmarketing surveillance programs that make thousand-patient trials
obsolete. Large data sets would also inoculate drug makers against
spurious claims such as the false association of pancreatitis with the
glucagon-like peptide 1 (GLP-1) and dipeptidyl peptidase 4 (DPP-4)
inhibitors. At the same time, it is essential to empower the FDA to
quickly remove or restrict the use of drugs when safety signals emerge
from the improved data and safety monitoring.
This
approach to reducing drug-development costs would have the greatest
effect on drugs for chronic conditions such as cardiovascular disease
and type 2 diabetes, since such drugs currently require the largest
trials. Moreover, our ability to identify rare side effects and take
action to protect patients would be substantially improved when many
more patients are being followed, albeit in the absence of a control
group. We believe this approach would have no adverse effect on the
trend in the development of drugs for orphan diseases and cancers, since
those drugs will continue to have low development and selling costs and
substantial differentiation from existing treatments. Yet, this
approach would make it attractive to pursue drug candidates for many
more disease conditions and would lower the threshold for financing a
drug's development so that more drugs would be brought forward.
Story Source: The above story is based on materials provided by THE NEW ENGLAND JOURNAL OF MEDICINE
Note: Materials may be edited for content and length
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Note: Materials may be edited for content and length
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