A Revolution in R&D

Introduction
Throughout the pharmaceutical industry, executives
are worried. They fear they will not be able to
meet the double-digit annual growth expectations
implied by high market capitalizations. The requisite
new drugs will not be forthcoming: R&D just
cannot deliver them all.
One standard response to this problem is to scale
up—that has been the basis of many a recent
merger—but while scale can pay off in commercialization,
global development, marketing, and distribution,
it is unlikely that scale alone can solve the
R&D problem. Another standard response is to buy
in drug candidates. Such a Band-Aid approach cannot
work indefinitely, and is a risky one anyway,
given that the price of these deals will continue to
rise as demand for them grows.
The only sure way to address the problem is to
increase R&D productivity. And the way to ensure
that is either to increase efficiency (lower cost or
higher speed) or reduce failure rates along the
value chain. Many companies have increased productivity
over the past decade, specifically by
reengineering the development phase. That optimization
may be reaching its limits, however. As for
the discovery phase, it has long been less amenable
to such improvements. So the problem of produc-
tivity persists. Traditional approaches cannot provide
an answer, but genomics can. (See Exhibit 1.)
It will not be easy, of course. There are some difficult
obstacles en route—difficult, but not insurmountable.
By making informed strategic choices,
companies can overcome the obstacles and reap the
productivity rewards. Those that embrace the revolution
most boldly could potentially halve the cost
and time it takes to develop a new drug—if they
meet certain challenges successfully.
EXHIBIT 1
GENOMICS IMPROVES R&D PRODUCTIVITY
Cost (time)
spent
Failed targets/
candidates
Successful
drug
SOURCE: BCG analysis.
Total cost to develop a drug
Reduce
failure
Improve
efficiency
Total cost (time) per step
9