A Revolution in R&D

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Cellomics are well positioned to exploit the expected
resulting demand for screening resources.
Aurora is a likely winner in the race to resolve chemical
genomics-related bottlenecks, since it boasts
some of the most advanced screening and assay
technologies in the industry. It has an unusual business
model, in that it provides tools and discovery
services but does not engage in any drug discovery
of its own.
* * *
So much for the imminent efficiency savings across
the R&D value chain. They are hardly the end of
TECHNOLOGIES IN WAITING—OTHER TECHNOLOGIES EXAMINED,
BUT OMITTED FROM OUR REPORT
In this report we have focused on the technologies
and approaches that are having the greatest impact
on R&D economics today. Several other exciting advances
appear likely to make a comparable impact
beyond the next three to five years (too far ahead for
inclusion in our analysis for this report), in particular,
the use of proteomics in target identification,
conditional gene inhibition in target validation, and
industrialized structural biology in screening and
drug design.
Proteomics is the study of protein expression and
protein-protein interactions. Its aim is an understanding,
and ultimately exploitation, of protein function.
Identifying proteins through sequence or structure
homology has recently become much more efficient,
thanks to bioinformatics’ role in analyzing largescale
experiments. One example of a genomics company
applying proteomics is Oxford Glycosciences,
which is engaged in identifying targets and surrogate
markers, both in collaboration with pharmaceutical
companies and in an independent pipeline. But proteomics
is not really industrialized yet, and has high
hurdles to overcome before it is.
We examined the economics of proteomic expression
studies using two-dimensional gel analysis, followed
the story, of course. Other technological advances
are bound to improve R&D productivity further in
due course. Important emerging technologies
include proteomics, partial target inhibition, and
structural biology. (See sidebar, “Technologies in
Waiting.”)
Improving Decision Making
The economics of R&D hinge on success rates, and
success rates depend largely on a cascade of decisions
that have to be made again and again:
whether or not to pursue a target or lead, and if so,
how—to what extent and with what approach.
by identification of interesting proteins through mass
spectrometry.
Under optimal conditions today, this approach has
the potential to save about as much in cost as
genomics-based approaches do, though not as much
in time (about six months less). As the technology
becomes industrialized, proteomics could well surpass
genomics-based approaches, but that is still
several years away.
The aim of the second promising technology we
investigated, conditional gene inhibition, is to overcome
a common problem in target validation. Here
is the background. A standard technique for target
validation uses “target knockouts.” The potential target
is removed, or “knocked out,” from an animal at
conception; this results in the total inhibition of the
target’s function from embryo to adult. The trouble is
that drugs work differently. Very seldom do they
inhibit target function fully, and they are taken only
after genes have already fulfilled their developmental
role in utero. So the use of target knockouts as a target
validation technique does run the risk of creating
false negatives (in some cases indicated by death,
because of the unnatural disruption of embryonic
development). What is needed instead of total gene