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Blockbuster Deathwatch Debate Heats Up With NEJM Editorial and In Blogs

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The big question of whether pharma’s blockbuster model is sustainable received another shake of the head in a New England Journal of Medicine editorial last week.
 
Soon after the editorial appeared, a mainstream blog challenged its arguments.
 
In the editorial, The Demise of the Blockbuster?, Harvard University economics professor David Cutler said his belief is based on the following trends: shrinking exclusivity periods and the rapid entry of generics; eroding tolerance among Americans of increasing prescription drugs costs; and the entry of targeted medicines.
 
“For decades, blockbuster drugs have nourished big pharma, but it is increasingly uncertain whether they can be counted on to support the industry in the future,” Cutler writes in the March 29 issue of NEJM.
 
The blockbuster deathwatch debate has been ongoing for some time now. While some say that pharmacogenomics technologies will eat into the profitable model, others have long predicted that big pharma will not abandon the blockbuster but rather use biomarkers and pharmacogenomics opportunistically to arrive more efficiently at cash-cow drugs.
 
NEJM Editorial
 
Statistics show that the industry has become increasingly dependent on the blockbuster for its livelihood. In 2001, blockbuster drugs accounted for 28 percent of world pharmaceutical sales; by 2005, blockbusters were 36 percent of the industry’s drug sales.
 
Currently, the success of uber-blockbusters like Pfizer’s Lipitor, with $13 billion in yearly sales, could suggest that pharma’s profit model has a long life span. However, the fallout from recent high-profile drug failures serves as a red flag to the industry to check the blockbuster’s vital signs.
 
Pfizer’s failed investigational cholesterol drug torcetrapib was essentially an $800 million warning for industry to invest in predictive technologies to learn as much as possible about agents before entering costly, late-stage clinical trials. After Pfizer halted studies for torcetrapib last December, the company’s market value dropped $21 billion overnight, Cutler notes in his editorial.
 
In an email to Pharmacogenomics Reporter this week, Cutler wrote that the most salient factor contributing to the death of the blockbuster model is the soaring cost of research and development.
 
“The big issue in the pharmaceutical industry going forward will be how to lower the costs of R&D,” Cutler wrote. “With costs being as high as they are, the prospects for all new drugs declines.”
 
This is one area where PGx technologies and genetics may help, and some drug makers have taken note. For instance, Novartis has said it is using PGx to help make go/no go decisions for investigational candidates early in their development [see PGx Reporter 03-14-07].
 
According to Cutler, genetics can shrink the market for certain classes of drugs like selective serotonin reuptake inhibitors for depression, which yield “idiosyncratic and unpredictable” responses in patients.
 
“Someday, genetic science may tell us why some patients are more responsive than others,” Cutler wrote in his article. “When that happens and drugs can be targeted more accurately to patients likely to have the desired response, the market for any particular SSRI will shrink.”
 
Furthermore, due to technological advancements it is getting more difficult for a single product to monopolize a class of drugs for a substantial period. In 1970, a drug in a new class typically held 10.2 years of market exclusivity. However, by the 1990s that advantage shrank to 1.2 years, Cutler said.
 
The rising cost of drugs is another big challenge to the viability of the blockbuster model. According to statistics Cutler cites, patients’ copayments for “non-preferred” drugs are increasing. For a drug in the third tier of a formulary, patients may incur between $600 and $960 in yearly out-of-pocket costs.
 
Blockbuster on Life Support
 
In response to Cutler’s NEJM editorial, CNBC analyst Paul Kedrosky in his blog argued  against the idea that the blockbuster model is dying.
 

“Personalized medicine, where individual genetic profiles are used to target one-size-fits-one therapies to individual patients is the obvious application of Long Tail theory, although it's not going to happen overnight.”

According to Kedrosky, the blockbuster model is still viable because “personalized medicines are and remain a pipedream.”
 
Kedrosky further argues that the one-size-fits-all profit model will be sustained by other countries where “Western patterns of bad eating and unhealthy living” are cropping up.
 
For instance, increasing obesity in India is bringing related health problems to the country. Currently, an estimated 25 million Indians have diabetes, and this population is projected to grow to 57 million by 2025.
 
However, the success of blockbusters in countries outside the US is dependent upon pricing. Cutler told Pharmacogenomics Reporter that in poorer nations like India, drug prices are constrained. “A lot of the [pharma industry’s] profits come from the US,” Cutler said. “I suspect there will be even more fighting over this issue in the future.”
 
The question of the blockbuster’s sustainability has reached other industry observers. Last week, Pharmacogenomics Reporter reported that the blockbuster era was giving way to a new age of the “niche-buster” [see PGx Reporter 03-28-07].
 
The term was popularized by Wired magazine editor-in-chief Chris Anderson’s book The Long Tail, which proposes that culture and the economy are shifting away from relying on a small number of “hits” or “blockbusters” at the head of the demand curve and toward a much larger number of niche markets in the tail.
 
Although Anderson did not respond to Pharmacogenomics Reporter’s requests for interviews last week, he did discuss the Long Tail theory in relation to the pharma industry in his blog.
 
“Many have asked whether there is a Long Tail of medicine. The analogies seem pretty apt: you’ve got blockbuster drugs at one end of the curve and orphan drugs for rare diseases at the other,” Anderson wrote.
 
“Personalized medicine, where individual genetic profiles are used to target one-size-fits-one therapies to individual patients is the obvious application of Long Tail theory, although it's not going to happen overnight.”

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