A Revolution in R&D

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almost to that of more familiar target classes. We
estimate the time required for this is about three to
five years from the discovery of a novel target,
which is the amount of time it should take to complete
validation and early screening (assay development).
(See Exhibit 4.)
Putting the New Technology into Operation
It is one thing to acquire and install new capabilities
and another to get them to function as they are
meant to. The challenge of making genomics technologies
operational has two major components:
easing the bottlenecks that will develop, and resolving
the personnel conundrums that are sure to
arise.
The Problem of Bottlenecks
The bottlenecks result, in effect, from the unevenness
of the efficiency gains at different points in the
value chain. (See Exhibit 5.)
Consider the sixfold increase in target identification
described above. This escalating quantity of
targets could turn out to be not so much a glorious
profusion as an exasperating glut. Unless there is
some corresponding increase in the capacity to
process them downstream, these targets will simply
EXHIBIT 4
IMPACT OF QUALITY ON COST TO DRUG
Pre-genomics Post-genomics
Mix of novel and
known targets
Novel targets only
Novel targets and
novel compounds only
Benefits of experience
over 3-5 years
SOURCES: BCG analysis; industry interviews.
590
590
790
880
1,080
Approximate cost ($M)
EXHIBIT 5
UNEVEN PRODUCTIVITY GAINS CREATE IMBALANCE
Number today
to get one drug
Not to scale
2,400 1
Potential
targets
400
Potential
targets
108
Validated
targets
Increased
productivity
138
Lead
candidates
loiter at their source in a wasteful logjam. Or consider
chemical genomics. Implementing this
approach will build up huge pressure on screening
resources: sending unvalidated targets for screening
could involve a 120-fold increase. So too with
efficiency gains at other points in the value chain:
without the necessary downstream adjustments,
bottlenecks will inevitably develop.
Our capacity to do functional experiments was
completely choked by potential targets.
—VP of discovery,
major pharmaceutical company
But the problem is a dynamic one, and accordingly
very awkward to deal with. Ease one bottleneck and
you often create another downstream. Or ease it
too much and you convert it into a bulge—over-
72
Drug
candidates
Required
productivity 2
Targets Compounds
30
7
INDs Drug
ID Biology
Chemistry
Development
Target ID Target Validation
Screening Optimization
Preclinical Clinical
SOURCES: BCG analysis; industry interviews.
NOTE: Does not include impact of pharmacogenetics, to be addressed in
next installment.
1Number of targets identified by investing same resources post-genomics as
pre-genomics.
2 Productivity required to exploit all potential targets from target identification.