It’s time for biopharma to embrace public health

This piece first appeared in the Timmerman Report.

Some years ago when I was working for a large biopharma, I heard a story. It seems a senior scientific executive had visited and given a seminar in which he described the company’s portfolio of drugs for type 2 diabetes. The company was projecting great uptake and profits. A member of our site raised his hand and said, “But if people just ate less and exercised a little more, they could prevent type 2 diabetes and the market would disappear.”

The answer: “Yeah, but they won’t.”

Harsh! But that executive was right. The Institute for Health Metrics and Evaluation (IHME) recently published a paper in JAMA describing how much different health conditions contribute to private and public health spending in the US. Number one? Diabetes. Following that were heart disease and chronic pain. These are chronic lifestyle diseases with big environmental and behavioral components, and the data make me wonder if there’s an opportunity here for the industry to zig and do some things that, in the long run, may make drug development more sustainable.

I think it’s time for biopharma to get involved in public health. Continue reading

How Brexit changed the way I look at biopharma’s reputation problem

This piece originally appeared in the Timmerman Report.

You may have heard something recently about Britain, the European Union (EU), some vote or other, chaos, turmoil, blah, blah, blah…You might also have heard how the presumptive Republican nominee for President of the United States has gotten to that position by identifying a strong thread of anti-establishment, populist sentiment in the US. And you may have heard that biotech and pharma is suffering from a reputation problem.

One of these things is not like the other, right?

I’m not so sure.

That biopharma has a reputation problem isn’t in doubt. The question, though, is how the industry got here. I want to know this because, thinking like many drug developers, I believe that by knowing the cause of a condition a fix can more easily be found.

There have been numerous candidate reasons, and I’m open to the idea that the cause is multifaceted just like it is for many chronic diseases. In the past year alone we’ve had the Martin Shkreli circus, admonishments about drug pricing from political candidates, analyses of how yearly increases in pricing often outstrip inflation, Pfizer pursuing quizzical acquisitions to avoid paying taxes, and companies suing the FDA to prevent generic competition. Biopharma’s problems go further back, as well, and examples of less than exemplary behavior abound. Hey, I was working at Merck when Vioxx was happening.

But Brexit points to something else. While it makes sense to look for behaviors by biopharma for causes for the reputation problem, business doesn’t happen in a vacuum. Political and social trends over the past few years suggest a rejection of elite opinion and earned expertise that is touching many parts of society and culture. Derek Lowe at In the Pipeline had a recent fascinating post on this phenomenon in the context of Right to Try laws (and also delving into Trump and Brexit). As he points out, Right to Try laws sit in that thorny spot where technological knowledge of drug development and Libertarian impulses collide. I can come up with a half dozen reasons why I think Right to Try laws are in general a bad idea, and none of them will sway someone who wants access to an experimental therapy for their dying child. You can see this playing out in the debate about whether eteplirsen should be approved for Duchenne Muscular Dystrophy.

Where did this suspicious, and sometimes hostile, reaction to elites and expert opinion come from? MSNBC anchor Chris Hayes, among others, has posited that over the past several years many people have suffered the effects of broken promises and crippled expectations. If the social contract between elites and the rest of the population is that if the elites (whether they are Democrats or Republicans) are given power, everyone will benefit, then breaking that contract leads to disillusionment and, eventually, rejection. A similar analysis from another part of the political spectrum was made by Charles Murray (H/T to @ScottGottliebMD). One can also point to growing partisanship as, if not causal, at least maintaining and contributing to the diminishment of expert and elite opinion. Unfortunately, there is no precision discrediting. When one calls to question the statements of scientists on specific topics such as global warming or vaccinations, one tars with a broad brush and the whole scientific edifice takes a hit. It’s like those kids with the paint rollers in Splatoon.

From this perspective, the poor reputation of biopharma stems at least in part from larger societal trends in how people perceive expertise. Healthcare is highly complicated and technical, and it’s not a stretch to say it’s associated with the expert and the elite. Taking this perspective has some good and some bad implications for biopharma. On the good side, one can say it’s not (all) the fault of the biopharma companies’ specific actions that the industry’s reputation has suffered. But on the bad side, this makes it that much harder to fix the problem. Better general overall behaviors by companies are a prerequisite for improving biopharma’s rep, but not the final cure.

However, if biopharma is serious about its reputation, and buys into this theory, it could use this perspective in a few ways.

First, it can look at the one industry that is highly expert driven and still has a good reputation: high technology, as represented by companies like Apple and Amazon, among others. I would conjecture that these companies, by taking a very consumer-focused approach and a real dedication to innovation, simply show people repeatedly, several times a day, that they are trustworthy and worth the money. Now, this is hard to do in biopharma where product development cycles are pretty much the diametric opposite of the fail fast, hard and often ethos found in Silicon Valley companies. But the industry can do a better job of explaining its innovative and impactful products, and being honest about when new products have neither—and pricing them accordingly.

The second thing is biopharma could start taking a longer, more societally focused view in how it uses its considerable lobbying muscle. To take one example, many in the US (and Europe) feel betrayed by the obvious effects of globalization on unemployment in some job sectors. Those in favor of globalization routinely argue that everyone benefits from cheaper prices on manufactured goods and also that hundreds of millions of people in the developing world are seeing a substantial increase in their living standards. This is measurably true. It’s also an argument that doesn’t resonate at all with someone who trained and worked as a machinist for fifteen years and lost her job due to outsourcing. There’s an asymmetry in perceived benefit versus experienced insult and loss

Biopharma could push for greater investments in job retraining, in both the public and private sectors, as well as for extensions to programs such as unemployment benefits to allow people the time to get retrained. You might say that this is outside the scope of what biopharma is responsible for, but that’s a self-imposed limit. One of the arguments for why elites and experts have lost their status is that so many organizations seem to be concerned solely with narrowly defined self-interest and shareholder value; not with the workers, customers and society within which they operate.

It’s a problem, figuring out the best way to rehabilitate biopharma’s rep, but it’s a necessary one to solve for the industry’s long term health. The Trump and Sanders campaigns have demonstrated that there are large reservoirs of resentment out there that shouldn’t be ignored. And it’s not hopeless either. Large scale societal change in attitudes can be done. Canada, unlike much of the developed world, has created a culture welcoming of immigrants, and this was accomplished via a long standing, coordinated effort by the Canadian government and others to make openness a core Canadian trait. They persisted and took the long view. If biopharma can spend decades and billions of dollars in dogged pursuit of specific targets (I’m looking at you, amyloid beta), then perhaps it can do the same to try and change the environment in which we all live and work.

 

How Distributed R&D Could Spark Entrepreneurship in Biopharma

This piece originally appeared in the Timmerman Report.

Remember the patent cliff and the general lack of new and innovative medicines in the industry pipeline? That was the big story of the past decade in biopharma. It caused a lot of searching for the next best way to organize R&D to improve productivity. One doesn’t hear that quite as often today. There are more innovative drugs both recently approved and moving forward through the pipelines of several biopharma.

The conversation these days has shifted toward drug pricing, and how the public is going to pay for some of these new, exciting drugs (the answer, in some cases, is maybe it can’t).

I don’t think the industry out of the woods yet. One of the main reasons drug prices have become such an issue is because even though there are new, innovative drugs, there aren’t enough of them. At the same time many of the drugs being approved are incrementally better but nevertheless being priced at a premium. And good reporting has made the public more aware of how many of our existing drugs are rising in price on a yearly basis. Especially in a time of little inflation, prices of most goods have not been going up at nearly the rate of pharmaceuticals.

Biopharma sits in a tough place. Analyses suggest the cost of developing a new drug has generally been doubling every nine years, which may be a by-product of some combination of the complexity of biology, our inability to predict which drugs will work, and the “better than the Beatles” problem. The question then is how to overcome these issues and increase the efficiency of developing new, innovative drugs. Without some kind of change, the industry is looking at a very difficult future in which price hikes run headlong into the wall of payers who finally say enough. Then what? Continue reading

One way to improve clinical trial reporting: a Yelp-style rating system

This piece originally appeared in the Timmerman Report.

STAT recently published an in-depth report about the many research centers that don’t bother to publicly disclose the results of their clinical trials, even though they are required to do so. This follows on a New England Journal of Medicine article back in March that had a similar analysis of the lack of reporting and publication of clinical trial data to clinicaltrials.gov.

Most observers of biomedical research would agree that getting clinical trial data out about what happened in a trial is pretty important, whether the trial succeeded or failed. After all, biomedical translational research is most meaningful when done on human subjects and negative information can be quite informative and useful. Animal models are nice, but translation of results from animals to humans is a spotty proposition at best. We need to know what’s working, and what’s not, to know how to best allocate our research resources and how to treat patients.

The lack of reporting is an embarrassment for research. It’s also understandable, because so far the FDA hasn’t used its authority to punish anyone for delayed reporting. Nobody appears to have lost any research funding because they failed to post trial results in a timely manner. Universities told STAT their researchers were “too busy,” given other constraints on their time, to report their results. So what really seems to be going on is that reporting is prioritized below most other activities in clinical research.

It was interesting and eye-opening that industry fared better than academia in both the STAT story and the NEJM article with respect to how many studies have been reported. Having seen the industry process first-hand, I’d speculate that (at least for positive trials) there’s a much stronger incentive to get data out in public. Successful trial results can create buzz among clinicians and patients, revving up trial enrollment which can then help get a new drug on the market faster, and convince people to use it when it’s available. It may be that in academia the effort of getting trial results in the required format for clinicaltrials.gov is perceived as too much work, relative to the rewards. Academics are naturally going to spend more energy on directly rewarded activities like writing grant proposals and writing peer-reviewed scientific publications that help them win even more grants, promotions, and other accolades. Well okay. If this is the case, then figuring out new incentives may be key.

So what would work? Anyone who participates in a clinical trial is providing time, may be subject to risks and often is asked to provide samples that are biobanked to support future exploratory and translational research. It’s like when people donate to food banks. I’m pretty sure they mean that food to be eaten and not to sit on a shelf. These participants in clinical trials deserve to have their volunteerism rewarded.

This got me thinking about how to empower patients to get more of what they want. Patient-centered research is a buzzword these days, and for good reason. Patients have at times been an afterthought in the biomedical research enterprise. I thought of services like Yelp and Uber and Angie’s List and other peer-to-peer systems that allow users to get information, provide feedback and give ratings to specific providers. And I wondered: could this be a way to apply pressure to clinical trial researchers to improve their reporting? Continue reading

Should Basic Lab Experiments Be Blinded to Chip Away at the Reproducibility Problem?

An earlier version of this piece appeared on the Timmerman Report.

Note added 23Feb2016: Also realized that I was highly influenced by Regina Nuzzo’s piece on biases in scientific research (and solutions) in Nature, which has been nicely translated to comic form here.

Some people believe biology is facing a “Reproducibility Crisis.” Reports out of industry and academia have pointed to difficulty in replicating published experiments, and scholars of science have even suggested it may be expected that a majority of published studies might not be true. Even if you don’t think the lack of study replication has risen to the crisis point, what is clear is that lots of experiments and analyses in the literature are hard or sometimes impossible to repeat. I tend to take the view that in general people try their best and that biology is just inherently messy, with lots of variables we can’t control for because we don’t even know they exist. Or, we perform experiments that have been so carefully calibrated for a specific environment that they’re successful only in that time and place, and sometimes even just with that set of hands. Not to mention, on top of that, possible holes in how we train scientists, external pressures to publish or perish, and ever-changing technology.

Still, to keep biomedical research pushing ahead, we need to think about how to bring greater experimental consistency and rigor to the scientific enterprise. A number of people have made thoughtful proposals. Some have called for a clearer and much more rewarding pathway for reporting negative results. Others have created replication consortia to attempt confirmation of key experiments in an orderly and efficient way. I’m impressed by the folks at Retraction Watch and PubPeer who, respectively, call attention to retracted work, and provide a forum for commenting on published work. That encourages rigorous, continual review of the published literature. The idea that publication doesn’t immunize research from further scrutiny appeals to me. Still others have called for teaching scientists how to use statistics with greater skill and appropriateness and nuance. To paraphrase Inigo Montoya in The Princess Bride, “You keep using a p-value cutoff of 0.05. I do not think it means what you think it means.”

To these ideas, I’d like to throw out another thought rooted in behavioral economics and our growing understanding of cognitive biases. Would it help basic research take a lesson from clinical trials and introduce blinding in our experiments? Continue reading

Baseball, regression to the mean, and avoiding potential clinical trial biases

This post originally appeared on The Timmerman Report. You should check out the TR.

It’s baseball season. Which means it’s fantasy baseball season. Which means I have to keep reminding myself that, even though it’s already been a month and a half, that’s still a pretty short time in the long rhythm of the season and every performance has to be viewed with skepticism. Ryan Zimmerman sporting a 0.293 On Base Percentage (OBP)? He’s not likely to end up there. On the other hand, Jake Odorizzi with an Earned Run Average (ERA) less than 2.10? He’s good, but not that good. I try to avoid making trades in the first few months (although with several players on my team on the Disabled List, I may have to break my own rule) because I know that in small samples, big fluctuations in statistical performance in the end  are not really telling us much about actual player talent.

One of the big lessons I’ve learned from following baseball and the revolution in sports analytics is that one of the most powerful forces in player performance is regression to the mean. This is the tendency for most outliers, over the course of repeated measurements, to move toward the mean of both individual and population-wide performance levels. There’s nothing magical, just simple statistical truth.

And as I lift my head up from ESPN sports and look around, I’ve started to wonder if regression to the mean might be affecting another interest of mine, and not for the better. I wonder if a lack of understanding of regression to the mean might be a problem in our search for ways to reach better health.
Continue reading

Baseball, Bayes, Fisher and the problem of the well-trained mind

One of the neat things about the people in the baseball research community is how willing many of them are to continually question the status quo. Maybe it’s because sabermetrics is itself a relatively new field, and so there’s a humility there. Assumptions always, always need to be questioned.

Case in point: a great post by Ken Arneson entitled “10 things I believe about baseball without evidence.” He uses the latest failure of the Oakland A’s in the recent MLB playoffs to highlight areas of baseball we still don’t understand, and for which we may not even be asking the right questions. Why, for example, haven’t the A’s advanced to the World Series for decades despite fielding good and often great teams? Yes there’s luck and randomness, but at some point the weight of the evidence encourages you to take a second look. Otherwise, you become as dogmatic as those who still point to RBIs as the measure of the quality of a baseball batter. Which they are not.

One of the thought-provoking things Arneson brings up is the question of whether the tools we use shape the way we study phenomena–really, the way we think–and therefore unconsciously limit the kinds of questions we choose to ask. His example is the use of SQL in creating queries and the inherent assumptions of that datatype that objects within a SQL database are individual events with no precedence or dependence upon others. And yet, as he points out, the act of hitting a baseball is an ongoing dialog between pitcher and batter. Prior events, we believe, have a strong influence on the outcome. Arneson draws an analogy to linguistic relativity, the hypothesis that the language a person speaks influences aspects of her cognition.

So let me examine this concept in the context of another area of inquiry–biological research–and ask whether something similar might be affecting (and limiting) the kinds of experiments we do and the questions we ask.

Continue reading