The Pharmaceutical Industry: Specifi city, Challenges, and What You Can Learn from this Topic - Innovation and Marketing in the Pharmaceutical Industry - page 4

P1: lR
mU
mT
P2: sR,
sU. sT
Fig. 1.2 Four key dimensions of innovation strategy. s small or short, m medium, l large or long.
The size of the oval denotes the magnitude of the cost. P1 and P2 refer to Project 1 and Project 2
Even when one leaves out these two big chunks of the cost, the money needed to
develop a drug is still substantial. It can easily cost $20-$50 million to conduct 1
year of clinical phase-III testing for one drug candidate. Although drug candidates
target very different diseases, in general, there is actually relatively little variation in
the costs of developing these drugs. This is because most costs are associated with
steps that vary little across projects. According to PhRMA (Pharmaceutical Research
and Manufacturers of America 2010 ), on average, 53.6 % of the innovation cost is
spent on clinical trials that are dependent on the number of patients needed, another
4.7 % is spent on the approval process, and 14.4 % on phase IV (postlaunch market
surveillance). The general process of discovery is also similar across a variety of
therapeutic categories. As a result, the cost of developing a drug plays a constrain-
ing role in the innovation decision, thus limiting the number of new drug projects
that a fi rm can support at a given time. However the cost of developing a drug plays
less of a strategic role in innovation decisions compared to the other three factors:
uncertainty, time, and return.
Uncertainty plays a critical role in a fi rm's innovation strategy. The probability
of success is low across therapeutic categories, and there is a need for a fi rm to
actively manage the success rate. The challenge is that the uncertainties associated
with passing each stage of the innovation process (i.e., preclinical trial, clinical
phase I, clinical phase II, clinical phase III, …) are different for different drug
candidates. For example, central nervous system (CNS) drug candidates have a
higher probability of failure in later stage clinical trials than other drug candidates.
Furthermore, managers need to actively manage the probability of eventual success
in two ways: by supporting correlated drug candidates (e.g., molecules with similar