A Revolution in R&D
A Revolution in R&D
A Revolution in R&D
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will not only help to make the trials faster and<br />
cheaper, but also allow some drugs to pass that<br />
would otherwise have failed ow<strong>in</strong>g to poor efficacy<br />
or side effects.<br />
High-Risk, High-Reward Research<br />
In the near-to-medium term, genetics promises to<br />
reduce R&D costs dramatically. Or does it? Our<br />
model shows that the application of disease genetics<br />
and pharmacogenetics together could, <strong>in</strong> the very<br />
best case, save as much as two-thirds of the current<br />
cost to develop a drug and nearly two years. Of<br />
these potential sav<strong>in</strong>gs, the vast majority comes<br />
from disease genetics. Of the rema<strong>in</strong>der, some cannot<br />
be clearly apportioned to either disease genetics<br />
or pharmacogenetics but must be credited to<br />
their jo<strong>in</strong>t efforts, be<strong>in</strong>g the product of synergies<br />
realized when disease genetics <strong>in</strong>formation is <strong>in</strong>corporated<br />
<strong>in</strong>to pharmacogenetics-driven cl<strong>in</strong>ical trials.<br />
(Although genetics can be comb<strong>in</strong>ed with the<br />
genomics technologies described <strong>in</strong> the previous<br />
chapter, the potential sav<strong>in</strong>gs are not additive. In<br />
the next chapter, we will assess the total sav<strong>in</strong>gs realistically<br />
achievable through the application of genomics<br />
and genetics.)<br />
Our model also shows that realiz<strong>in</strong>g this potential<br />
will be far from straightforward and is far from<br />
guaranteed. The high-end sav<strong>in</strong>gs estimate assumes<br />
a positive resolution of several scientific, technical,<br />
and market risks. With every setback, the sav<strong>in</strong>gs<br />
dim<strong>in</strong>ish. Too many setbacks, and the sav<strong>in</strong>gs fall to<br />
zero. Implement<strong>in</strong>g genetics could even turn out to<br />
have a negative impact on value, ow<strong>in</strong>g to adverse<br />
market dynamics.<br />
Such a double-edged sword is awkward to wield. If<br />
companies fail to grasp it at all, they forfeit the<br />
opportunity to reap enormous rewards—nearly<br />
double the sav<strong>in</strong>gs possible with genomics technologies.<br />
If they do grasp it, they put themselves <strong>in</strong><br />
some danger, and will need to develop a genetics<br />
strategy aligned with their risk profile and with specific<br />
market conditions. As an approach to research<br />
and development, genetics rema<strong>in</strong>s risky, but full of<br />
promise, too. This chapter assesses the promise and<br />
the risk alike.<br />
Disease Genetics<br />
Underly<strong>in</strong>g many diseases are genetic variants, or<br />
polymorphisms—alterations <strong>in</strong> the DNA sequence<br />
of a given gene that <strong>in</strong>fluence <strong>in</strong>dividual risk of disease.<br />
(The term polymorphism usually refers to a<br />
common variant—one found <strong>in</strong> more than 1 percent<br />
of the population.) Often the genetic difference<br />
consists of just a s<strong>in</strong>gle altered letter <strong>in</strong> the<br />
genetic code (the variant is then known as a s<strong>in</strong>gle<br />
nucleotide polymorphism, or SNP). Such a t<strong>in</strong>y alteration<br />
can have fatal consequences; for example, the<br />
substitution of an A for a T <strong>in</strong> the hemoglob<strong>in</strong> ß<br />
gene is responsible for sickle cell anemia. The goal<br />
of disease genetics is to identify such DNA alterations;<br />
so far, this goal has proved elusive for all but<br />
the most strongly <strong>in</strong>herited conditions. (See sidebar,<br />
“Disease Genetics—Various Approaches to<br />
Variants.”) But researchers persevere, s<strong>in</strong>ce f<strong>in</strong>d<strong>in</strong>g<br />
the causal variants can be a major step to f<strong>in</strong>d<strong>in</strong>g a<br />
treatment—and potentially a cure.<br />
Uncerta<strong>in</strong>ty persists: the technologies have yet to<br />
prove their full worth by produc<strong>in</strong>g the necessary<br />
quota of practical results. But if all goes accord<strong>in</strong>g<br />
to plan, the sav<strong>in</strong>gs realized by pharmaceutical<br />
companies will be enormous.<br />
The Potential<br />
The sav<strong>in</strong>gs would come partially from improved<br />
efficiency <strong>in</strong> discovery, but pr<strong>in</strong>cipally from<br />
improved success <strong>in</strong> target validation and cl<strong>in</strong>ical<br />
trials. The improvements <strong>in</strong> efficiency result from<br />
the consolidation of target discovery <strong>in</strong>to a s<strong>in</strong>gle<br />
step; the improved success rates result from the<br />
ref<strong>in</strong><strong>in</strong>g of target identification, mak<strong>in</strong>g it possible<br />
to p<strong>in</strong>po<strong>in</strong>t the targets associated with disease susceptibility<br />
<strong>in</strong> humans.<br />
Once the targets have been located, they can boast<br />
a collective superiority <strong>in</strong> three particular respects.<br />
First, their relevance to human disease is certa<strong>in</strong>.<br />
They have, after all, been validated <strong>in</strong> humans,<br />
show<strong>in</strong>g directly that modulation of gene activity<br />
leads to alteration <strong>in</strong> the <strong>in</strong>tensity or duration of<br />
disease. (By contrast, other targets are usually iden-<br />
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