A Revolution in R&D

GENOTYPING—HOPES RISE AS PRICES FALL
For companies wishing to pursue disease genetics,
one of the major stumbling blocks has been the prohibitive
cost of genotyping. The current average
genotyping cost in the industry is about 50 cents per
SNP. At that price, even narrow candidate-gene studies
could cost as much as $15 million; a direct
genome-wide association study could cost upwards
of $5 billion.
Matters are about to change, however. Costs are
declining, and are expected to continue to fall dramatically—as
much as 50-fold—over the next few
years, thanks to competition and customer demand
on the one hand, and improved automation and
“Genotyping—Hopes Rise as Prices Fall.”) And
once that happens, the two major questions outstanding
can be resolved: the number of patients
needed to attain statistically significant results, and
the utility of SNP maps.
Regarding patient populations, first: the more
patients, of course, the easier it is to discern a true
difference above randomly occurring fluctuations
(noise)—and the more expensive. Size your sample
too sparingly, and you risk emerging empty-handed;
too generously, and you overspend. Striking the
right balance is tricky. It depends on how common
the sought-for SNPs are, and that is very difficult to
estimate. It also depends on the strength of the
association between the disease and the suspect
polymorphism. For common multigenic diseases,
susceptibility depends on a specific combination of
several genetic changes, and is influenced by environmental
factors as well, which weakens the association.
The weaker the association, the larger the
sample needed to detect the influence of a specific
gene. Perhaps the issue will dissolve before being
resolved. If prices plummet as expected, and if
databases become as comprehensive as hoped, sufficient
sample sizes will become easily affordable.
SNP maps can help in the quest to identify a
disease-susceptibility gene, but only if two condi-
miniaturization (which allows companies to reduce
their consumption of expensive reagents) on the
other.
Our calculations are, accordingly, based on a cost of
one cent per SNP genotype—a likely price across the
industry, according to expert consensus, within the
next five years. (Some companies must already be
benefiting from genotyping costs considerably lower
than the current industry average.) That said, the
cost of conducting disease genetics studies will
remain far from negligible, and companies will need
to continue to take it into account when assessing
risk.
tions prevail. First, for any association studies
(whether narrow or broad) to work, the genetic variants
associated with the disease need to be fairly
common—prevalent in more than 1 percent of the
population at large—and that is far from guaranteed.
Then, these polymorphisms need to be either
recognizable (that is, they must produce discernible
changes in a protein) or at least detectable by an
indirect measure (called linkage disequilibrium;
that is, the presence of a particular SNP cluster in
individuals with a given disease). Assuming reasonable
costs, indirect genome-wide association studies—of
all the approaches, the one most likely to
prevail—would, according to our model, result in a
total savings of $395 million in cost per drug on average,
with 0.7 years of time saved to market (producing
an additional $260 million of value per drug).
Of course, for that to happen, you need to do more
than find disease genes—you have to turn them to
good effect by ultimately producing a drug. And
here disease genetics presents a further challenge:
given the long odds involved in pharmaceutical
R&D, will the number of targets yielded by disease
genetics be sufficient?
Practicability—the Limitations of Human Studies
The problem is that human studies—identifying
polymorphic genes in humans—will tend to pro-
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