How Can Big Pharma Restore A Reputation?
A picture taken on September 13, 2012 in Paris shows pills. According to a book written by Necker institute director Philippe Even and Paris MP Bernard Debre, one prescription in two is useless, and costs the French social security 15 billion euros. (Image credit: AFP/Getty Images via @daylife)
According to this Washington Post longread by Peter Whoriskey, the bald truth about industry-funded clinical trials for new drugs is not pretty. As Whoriskey tells it, no one’s quite sure how to give industry-funded trial results a makeover so that the good studies don’t suffer the reputation of the bad ones:
According to a survey published this fall in NEJM (New England Journal of Medicine), doctors are about half as willing to prescribe a drug described in an industry-funded trial. That’s unfortunate, doctors say, because a good portion of the industry-funded research is done well.
“On the one hand, there are a lot of important industry-funded studies that are accurate, relevant and useful,” said Jerry Avorn, a Harvard professor who has specialized in spotting adverse events from drug use. “There is also a multi-year history of abuse and distortion.”
This history of “abuse and distortion,” even if the relative number of cases is limited, leaves consumers wondering how they can tell what’s trustworthy. As a consumer and a scientist who has wondered that myself, I’ve got no easy answers, and obviously, MDs remain skeptical, too. It’s not reasonable or even supportable to argue, wholesale, that any trial with industry funding or researchers with industry-related conflicts of interest is a suspect trial. But some companies appear to have engaged in suppression of data showing a drug is dangerous or ineffective, sometimes with deadly results. And the math suggests that an industry-funded study is far more likely to yield results favoring a drug’s effectiveness than a study conducted outside the industry wallet. That kind of arithmetic points to a strong bias, at the very least, in industry-linked studies.
What’s a consumer to do? What any consumer should always do: Caveat emptor. We can do no more than that as consumers. Many car buyers wait for a second- or third-generation of a model of interest before buying to give the makers a chance to smooth out undetected problems. Perhaps we’d do well to do the same with The Latest Greatest Drug that pops up in magazine ads or as samples at the doctor’s office. If there’s an existing, time-tested therapy available, waiting for time to test new ones before trying them might be an option for some.
But for people whose therapy choices are limited to new arrivals, whose decisions are about life or prolongation of life versus impending death, not only is waiting a luxury they cannot afford, they may well be the ones whom time tests. They’ll be the ones who translate through serious adverse effects or death into the statistics that tell us a drug isn’t the miracle we’d hoped it was. What can be done to prevent using unwitting consumers in dire straits as guinea pigs?
The debacles of Avandia and Vioxx suggest that greater transparency throughout the clinical trials process and designing trials that actually address side effect concerns might help keep drugs off the market whose costs outweigh their benefits. Indeed, according to the Post article, one proposed step to greater transparency is to “compel drug companies to release all of the data from trials of drugs that are on the market.” It’s a nice idea, but how will anyone know that all the data have been released and that none remain concealed or destroyed? Regardless, drug companies generally don’t seem inclined to play along, Whoriskey writes, something that research seems to support. [ETA: For a look at how industry responds to critique on the other side of the pond, see this exchange with Ben Goldacre, author of Bad Pharma.]
And the question remains, What would anyone do with those data? Throwing a bunch of information onto the Web won’t solve the problem of industry manipulation of trial design or published data analysis and interpretation. It’s closing the barn door after the horse has bolted. What we need is a construct with teeth, an established network of industry-independent researchers (not contractors) equipped to evaluate trial design, statistical power, data analysis, and interpretation, not as regulators but as contributors to final research publications. It would be a sort of Congressional Budget Office for clinical trial results.
For the best outcome and restoration of trust, this completely independent group of researchers would analyze data (and preferably design) from an industry-linked clinical trial. The resulting publications would then reflect the independent findings, effacing risk of bias (and possibly building up consumer trust). The expense of conducting clinical trials would stay with industry–which is one of the main reasons industry now leads the U.S. government in clinical research investment–but place analysis and interpretation in the hands of those without a dog in the hunt. Some movement in the U.S. toward consideration of better trial design and analysis is has been afoot, but not a mechanism for offering independent analysis for inclusion in published reports. And no mention of ethics, the giant pharmaceutical elephant in the room.
I’m not one of those who thinks that “Big Pharma” is a monolith of evil trying to make a buck, regardless of human costs. The thousands of researchers in industry are not members of a secret cabal obsessed only with immense wealth. But if industry wants to shine up a reputation dimmed by suspect behaviors of some of its own, voluntarily turning to independent evaluation and reporting of transparent data sets is one step toward polishing away some of that tarnish.