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David Shaywitz
Come for the tech, stay for the culture.
That seems to be the hope of most digital champions inside large pharma companies. These executives hope to instill in their organizations not only important new capabilities, but also a “Silicon Valley” mindset, an innovative spirit characteristically associated with tech entrepreneurs.
The reality, of course, is more complicated; pharma executives – and to some degree, all of us, perhaps – tend to imagine ourselves as more audacious, more creative, more risk-embracing than in the end we actually are.
It’s not just a big pharma phenomenon; when I was in venture capital, I saw the same tendency emerge whenever a startup on whose board I served conducted a search for a new executive. Typically, the headhunter would be asked to think expansively, and identify a broad range of talent, including less traditional candidates. Yet in the end, the consensus generally landed on someone who felt comfortable and familiar, a leader who was perhaps less interesting than some candidates, but also viewed as less risky, and more of a known quantity. Flirt with risk, marry stability.
The challenge facing innovators who want to bring change to pharma was captured nicely by Craig Lipset, a digital health pioneer at Pfizer. On a recent Tech Tonics episode, Lipset told Lisa Suennen and me that the three unofficial rules for anyone pitching digital health inside the company was that it needed to be safe for patients (of course); not threaten anyone’s job; and not threaten to land the company in court.
Venture capitalist Josh Kopelman of First Round Capital (early investors in Uber, Square, Flatiron Health) captured this tendency perfectly on an April episode of Patrick O’Shaugnessy’s always excellent podcast, noting that one of the best opportunities for startups is to leverage (arbitrage) the intrinsic risk aversion of large corporations.
Kopelman described an experience he had early in his career, after he sold a company he started to eBay, and he got to know the big online marketplace. eBay, he said, noticed that payments on its platform were being consummated by the startup, PayPal, and eBay wanted to handle those transactions itself, so that PayPal wouldn’t be able to take a cut.
So eBay set up a joint venture with Wells Fargo called Billpoint, in theory a formidable partnership between a top bank and the top online market. But the reality, Kopelman said, was that at the initial product meetings there were nearly as many lawyers in the room as there were product managers. Digital payments were a fairly new space. There was a lot of grey area. Wells Fargo in particular couldn’t afford to jeopardize its business by skating too close to the regulatory line.
PayPal, on the other hand, embraced the risk; when PayPal filed its S-1 form as it prepared to go public, Kopelman says, the company disclosed it was under investigation by a slew of state attorneys general. PayPal’s willingness to take on this risk – and do so successfully – were key to its ultimate success (including its post-IPO acquisition by eBay for $1.5 billion).
Kopelman also cites the example of Uber, specifically calling out controversial founder Travis Kalanick for his fearless approach to regulatory grey areas.
It’s amusing to contemplate how innovators like Kalanick and the PayPal leaders would fare within big pharma, an industry that is highly regulated to begin with, and then has arguably exacerbated these challenges through a culture that reflexively resists innovation through a deep, shared belief that “regulators will object.”
Moreover, these concerns are not unfounded; as much as FDA leaders such as former Commissioner Scott Gottlieb, current Principal Deputy Commissioner Amy Abernethy, and the head of the Oncology Center of Excellence Richard Pazdur have passionately championed innovation and flexibility, this attitude is still not universally embraced (to say the least) by the reviewers responsible for most of the heavy lifting inside the agency.
Other qualities of startup founders described by Kopelman might also struggle in the context of a large pharma. For example, Kopelman highlights the value of betting on people rather than a specific idea – he views a founder’s initial product proposal as more of lens to understand how the founder makes decisions and processes signals than it is a detailed plan describing what’s actually going to happen. Similarly, Kopelman says his firm tends not to be “thematic” investors, contending that by the time something bubbles up as a discrete theme, it is effectively too obvious, and something everyone is doing. (I entirely agree; however, most VCs, and virtually all corporate VCs, are explicitly thematic.)
Again, anyone who’s tried to get buy-in to anything in a large pharma appreciates immediately the contrast; extensive and excruciatingly deliberative processes generate themes and areas of focus (leading invariably to oncology, immunology, and rare disease these days), and even individual early-stage projects that hope to be resourced must be described and mapped out in exaggerated, if not comical, precision. (Then again, I’ve heard the same said from academic researchers applying for NIH research grants.)
Several attributes of successful founders cited by Kopelman can and — I’ve often insisted — should be adopted by pharmas. For example, Kopelman emphasizes that you can’t build a great platform without first having a killer app; while he was making an even deeper point, one simplistic way to think about this is that pharmas contemplating data science would do well to consider what very specific and concrete problems they hope to solve, and then focus on developing a pragmatic solution that clearly works.
Instead, there’s an unfortunate tendency to spend huge amounts of time and resources investing in and developing a massive data and analytics platform in hopes that it will someday prove useful – despite considerable experience to the contrary. Startups are often critiqued for creating an elegant solution in search of a problem. The related mistake large companies tend to make is architecting a vague, expansive solution they hope will solve every problem, presumably reflecting the promises required to secure funding in complex, matrixed organizations.
Kopelman also emphasizes the importance of getting product feedback early and often – an idea long-advocated by “Lean Startup” guru Steve Blank. If instead, you decide you know from the outset exactly what’s needed and work head-down until you’ve perfected your product, the product you emerge with may be elegant but totally off base.
Bottom line: A large, legacy pharma is never going to have the agility of a startup, and compelling new ideas will always struggle for traction given the intrinsic risk-aversion of massive multinational corporations. Many (I assume most) new health technology concepts will have to be developed and proven out in a less constrained environment first. The innate skepticism towards tech solutions by most people in the trenches at big pharmas remains exceptionally high, and the meticulously-structured, rigidly-articulated way most work is done in pharmas (and other large companies) tends to be poorly aligned with the agility and improvisation new tech product development often requires. The most exciting and most innovative opportunities at the interface of health and tech almost certainly remain in the startup space.
Yet pharmas desperately need better technology, and promising technologies can benefit from the scale, experiences, and established relationships of a large pharma.
To succeed, pharmas need to scope projects in a fashion that’s relentlessly focused on tangible outcomes that matter, results that are palpably experienced by users. Uber was adopted because you press a button and a ride shows up; Google was adopted because you type a query and the answer shows up; Amazon was adopted because you place an order and your purchase shows up. Simple. And effective.
A successful technology in pharma doesn’t need to be all things to all people. Paradoxically, it’s this very need to gain the approval of multiple stakeholders that often results in poorly-scoped, ill-fated projects. Instead, at least initially, the tech solution should brilliantly meet the substantive needs of an individual stakeholder, and accelerate an important process. In actually delivering on this promise – in delivering tangible delight and utility for somebody in the organization — a technology champion in pharma can do more to change a company’s culture and attitude than all the Successories posters, inspirational corporate messaging, and aspirationally hip (tucka-tucka) corporate hackathons combined.
Ruth Etzioni, Full Member, Division of Public Health Sciences, Fred Hutch Cancer Center
When I was in college, everyone wanted to major in psychology. I signed up, but switched out after only a few weeks.
Why? Well, the more I read, the less I seemed to know. Psychology, after all, is an inexact science.
I sought refuge in the exact worlds of computer science and mathematics. Those courses led me to build a career in statistics, the science of uncertainty.
For the past 20 years, I have partnered with colleagues in the Surveillance Program at the National Cancer Institute to explain why cancer rates go up and down from one year to the next. We can do this work because we know how many cancers cases – and deaths – there are every year. Our analysis is grounded in hard data that is reliably and consistently collected.
For years, an information infrastructure has existed to funnel data from pathology laboratories to local cancer registry offices, who interface with hospitals and doctors’ offices to catalog each cancer case.
I always appreciated the NCI’s Surveillance Program for its tireless work to bring us the numbers and double-check to make sure they are right. Reliable data is the bedrock of our analysis.
I appreciate the fundamental, unglamorous data-checking and cleaning work even more as I look at the state of COVID-19 surveillance. I wonder about the data we are relying on to track cases and deaths, to prepare for the future, and to make critical policy decisions.
It seems to be a house of cards.
We know that the reported daily tally of cases is hopelessly wrong. Cases can only be confirmed if they are tested by one of the reliable RT-PCR diagnostic tests that uses samples from nasal swabs. From the beginning, the US has struggled with a shortage of these tests. So the number of cases reported on any given day is determined not only by the spread of the virus itself, but also by the availability of tests. Many people don’t know that they have the virus, and of those that exhibit symptoms, many who want a test can’t get one. Access to reliable diagnostic testing varies widely over time and across locations. So the meaning of “number of confirmed cases” differs depending on the date and where you are.
The number of cases simply can’t be interpreted without understanding the state of testing. But, even if we knew how many tests were being done each day, this would not be enough. Just figuring out how many symptomatic cases there are would require how many of these people actually present themselves to a healthcare provider, asking for a test. We don’t have the data to understand this, but it surely varies depending on the date and where you are. And this doesn’t even get at how to account for asymptomatic cases.
New antibody studies can provide us valuable snapshots in time, if conducted with a reliable blood test, and with a rigorous random sample of the population – not just people who volunteer because they think they might have COVID-19. These studies may help us to reconstruct how many surviving individuals had the virus, whether they know it or not, and this could potentially help correct our daily tally of cases, retroactively. But, results of these studies are subject to debate and cannot be taken at face value.
As an example, an antibody study conducted in Santa Clara county was roundly criticized, because the underlying test produced false positive results that could have accounted for many of those told they had antibodies. Still, as these studies accumulate, we will likely gain a better idea of the foothold the virus has established in the population.
Given that we are in a pickle when it comes to counting cases, we might turn to harder data, like the numbers of hospitalizations or deaths. Hospitalizations are limited by system factors that have nothing to do with disease burden. But deaths? Surely deaths are more reliable. You are either alive or not, there’s no squishy subjective judgment at work, and no faulty test to wonder about. Right?
It’s not quite that simple. Until recently, it seemed that most people trusted the counts of COVID-19 deaths reported around the world. Even as China kept changing its definition of what constituted a coronavirus case, its death tally was not questioned. On Mar. 19, breathless headlines declared a “grim milestone” – Italy’s COVID-19 death toll of 3,405 had exceeded China’s reported death toll of 3,249. Reported deaths from China and Europe became the basis for models that predicted the scale of the epidemic in the US and informed social distancing policies across the country. I have written in these pages about the models and warned about how they are being miscommunicated, but I never mentioned my concerns about the death data which drives them.
I can’t remember when I first became skeptical about the deaths. But it was definitely before Mar. 19 because I recall reading the grim milestone headlines on that day and wondering why everybody believed the official number from China. Maybe it was after I personally asked a Chinese statistician colleague now living the US who said that in her opinion the numbers from China were made up so as to imply a fatality rate that was between one and two percent.
Still, I told myself, our surveillance systems in the US would never allow this to happen here.
Recently, important data has emerged that strongly suggests that we are undercounting COVID-19 deaths in this county – by tens of thousands. The basis for this is in the numbers; the official count of deaths due to the virus is far below the excess in the overall number of deaths compared to what would be expected at this time of the years based on data from the last few years. On May 13, Nicholas Kristof of The New York Times reviewed the numbers and concluded the COVID-19 death toll had already exceeded 100,000.
The counting of excess deaths to shed light on cause-specific mortality is not new. We do it to assess our progress against cancer all the time. Sometimes it is hard to know whether a person with a history of cancer died of, or with, their disease.
Suppose a breast cancer patient dies of a heart attack. Was that death due to cardiovascular disease or to the chemotherapy drug she was given and that is known to weaken the heart? Death certificates can only do so much to tell us, and generally focus on what we call the proximal cause of death, which in this case would be cardiac arrest and not cancer. To avoid undercounting deaths among patients with a specific cancer, we can tally the excess deaths among individuals with a history of that cancer and stack the result against the deaths among comparable individuals (e.g. same age and race) in the population. This technique, developed in the 1950s, is called relative survival. It has been shown to work really quite well for many cancers.
In the case of COVID-19, which can cause death via a diverse array of awful disease symptoms, this makes a lot of sense. Death certificates list first the proximal cause of death – what actually caused you to die.
We know COVID-19 can kill you by suffocating you, giving you a stroke, causing your heart to stop beating or your kidneys to fail. This is what gets listed first. If COVID-19 is known or suspected, this is recorded as a second, third or even fourth cause.
My cousin, an all-knowing MD and research scientist, who directs a critical care unit in Denver, tells me that even when patients die of respiratory failure, the best known COVID-19 cause of death, the proximal cause is listed as Acute Hypoxemic Respiratory Failure (AHRF) and the next cause is the condition, Acute Respiratory Distress Syndrome (ARDS). COVID-19 infection only appears third – so long as the patient is known to have the virus.
Patients not tested, who don’t make it to the hospital, or whose deaths masquerade as being from strokes or heart attacks may not even have COVID-19 listed as an underlying cause in the death certificate.
So it makes sense to look beyond the cause-specific tally to the overall mortality data.
I think we can trust the overall number of deaths. It is possible that heart attack or stroke deaths may have gone up a bit this year even in the absence of COVID-19. And we certainly don’t want to count deaths that were truly due to these causes as COVID-19 deaths just because a person had a confirmed diagnosis and then had a fatal heart attack or stroke.
But, on balance, if we look at overall all-cause mortality rather than cause-specific deaths, we are left with the inescapable conclusion that the official tally of COVID-19 deaths in the US is way low. When you look at all-cause mortality, and make a direct comparison of March 2020 to March 2019, or April 2020 to April 2019, you will see an unmistakable increase in death rates. This is despite various conspiracy theories to the contrary to which I won’t devote any airtime. Let their proponents debate our National Center for Health Statistics.
At this point I hope we are all on the same page about the need to look beyond the official COVID-19 death toll to the cases who don’t get to have the virus listed on their death certificate. But what is happening in some states now is worse; they are changing their definition of a COVID-19 death to only count those for whom the virus is coded as a proximal cause.
I know that this is happening in Colorado because my cousin shared his frustrations about his patients’ causes of death being wrongly recorded by the state. Colorado coroners are objecting, according to a piece run by CBS4 in Denver. A new Scientific American article out this morning cites the Colorado issue.
In Florida, the state forced medical examiners to stop releasing their counts of COVID-19 deaths which were at odds with official state figures, and fired the creator of the state’s COVID-19 data portal, who claims she was terminated for refusing to manipulate the numbers. And in states like Georgia, where COVID-19 can only be listed in as a cause of death in confirmed cases, reducing the number of tests performed will automatically trigger a decline in deaths. Of note: Georgia is no longer releasing data on testing numbers.
We tend to think of numbers as facts and data as absolute; it feels safer that way. Unfortunately, when it comes to COVID-19, it seems that there is no safety in the numbers. When we wake up each morning and check the dashboards of cases and deaths in our local papers or cable TV news, we need to bring a healthy dose of curiosity – and perhaps skepticism – to the table.
If we don’t, we may jeopardize our understanding of the true burden of COVID-19 and compromise our ability to navigate our way out of it.
David Shaywitz
I was recently speaking with a friend of mine, a pulmonologist at a large academic medical center in the Midwest, about his COVID-19 experience. I was especially interested, in the context of iterative experimentation, to learn how his hospital was working on improving the care of COVID-19 patients, especially those in the ICU, which he oversees.
It’s real problem, he said. On the one hand, there are specific initiatives he’s trying to evaluate, in a classic, controlled fashion, so he can figure out if the intervention is effective and should become part of the standard of care.
That’s the goal.
In reality, however, here’s what he says is actually happening: most of the front-line doctors are hearing about the very latest approaches, generally from social media (such as Twitter or medical podcasts), and are trying to immediately apply these methods to their patients. As a result, the care patients receive depends (to some degree) on the specific physician involved, as well as the extent to which that physician has been influenced by other opinionated doctors.
At a recent Boston innovation conference (discussed here), Dr. Paul Biddinger, an emergency medicine physician who leads emergency preparedness at the Massachusetts General Hospital, made a remarkably similar observation. He praised the “unprecedented information sharing” associated with the COVID crisis. But he also expressed concern about the “practicing by anecdote,” and more generally the “temptation to fall off what have been the time-proven methodologies of science.”
The tension here captures an especially distinctive aspect of American medicine, a characteristic beloved by some and lamented by others.
Intrinsically, doctors value their independence, and the opportunity and obligation to be masters of their own domain. This is how U.S. medicine generally works: once doctors are trained and licensed, they more or less can treat patients as they see fit, within a fairly wide band of professional expectations. Care generally isn’t cookie-cutter, and doctors are typically free to offer a range of potential approaches, constrained mostly by what the patient’s insurance is likely to accommodate or reject (and by the hassle of navigating that process).
To be sure, physicians are supposed to stay up to date, and not commit blatant malpractice like treat a strep infection with a blood thinner, say, but there’s a lot of room for individual interpretation and improvisation, which many doctors have embraced, believing it acknowledges the individualized nature of each patient/doctor encounter. Call this the “libertarian” view of medicine.
Contrast this approach with what might be called the “systemic” or “operations” view of healthcare, described eloquently nearly a decade ago by Dr. Atul Gawande in his classic “Cheesecake Factory” New Yorker essay. In this view, while doctors are the ones actually laying on hands, the expectation as well as the mindset is that these providers should be more focused on consistency than individuality; care should adhere clearly to “best practice” guidelines, and while modest customization is permitted, significant deviations should be evaluated deliberately and programmatically, not ad-hoc.
In this view, much of what’s wrong with American medicine is precisely the individual physician’s insistence on acting, well, individually, leading to dramatic variances in care, and often, it is said, the suboptimal treatment of patients. Medicine practiced in this way tends to view physicians as providing the “customer service,” but adhering to master pathways and algorithms. Not surprisingly, many (but not all) doctors in systems like this tend to view themselves as interchangeable cogs and data entry clerks, rather than empowered inquisitive physicians in the Judah Folkman tradition.
The uncomfortable question raised by advocates of a systems approach is whether it promises better care of patients but lacks traction because it challenges the self-esteem of doctors.
The COVID-19 crisis highlights the dilemma. In the unlucky event you were hospitalized with COVID-19, would you want your care driven by a standardized algorithm, rigorously followed, or would you want your doctor to improvise, and potentially apply the latest and greatest – although it might not be so great, and perhaps may reflect little data and instead just the strongly-held opinion of a persuasive, social-media-savvy clinician? Or, it might incorporate a valuable emerging insight, the sort of adjustment that could take a relatively long time to incorporate into a standardized protocol.
On the one hand, most physicians wouldn’t want to practice, and don’t like practicing, in a climate of rigid pathways and defined approaches – that’s not why most doctors went into medicine. Moreover, the physicians who self-select for environments with great autonomy may be more likely to have the imagination or creative insight that the clinicians in more rigid systems lack.
But it’s also possible – especially as more care becomes templated and algorithmic – that the consistency and transparency provided by these systems offers not only a higher average level of care, but also enables a degree of continuous, iterative improvement in care that is far more difficult to achieve in less structured environments.
One worry is that in such a command-and-control framework, you’re potentially relying on centralized planning – on detached, “enlightened” supervisors to suggest modifications, rather than benefiting from the experience and insights of front-line providers, doctors whose imagination and creativity could well be crushed in a system that valorizes provider conformity, and expects providers to perform their job consistently and empathetically, but looks elsewhere for insight and originality.
Historically, the physicians so many of us have looked up to are the brilliant, iconoclastic individuals who figured out on their own a new way to do something. It will be interesting to see if there are future heroes who distinguish themselves by their ability to apply deliberate, iterative experimentation to raise the standards of a system.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Luke Timmerman, founder & editor, Timmerman Report
[This week, I’m re-publishing this column written Nov. 9, 2016. It’s probably more important to read now.—Luke]
I’ve been dreading this moment since June. That’s when I started telling people: Trump was going to win. I could feel it in my bones, because of where I’m from.
We’ve heard enough by now that the elites have let us down. The elites in politics, business, and the media couldn’t see what Donald Trump was tapping into. Most of these successful people (including you) live in islands of prosperity, coastal cities full of highly educated folks doing interesting work. The economy is improving in those places. The future looks bright, right?
The electoral map tells us a different story. Vast geographic stretches of people voted red, for a guy who ran as an authoritarian candidate, not a traditional Republican. It’s a powerful statement against the establishment.
I know these voters well. I spent the first 18 years of my life growing up on an 80-acre family farm in Grant County, southwestern Wisconsin. I grew up driving tractors, shoveling pig shit, and spreading it as fertilizer on corn fields.
All around me were people who owned guns, went deer hunting, did manual labor, and told off-color jokes. Most of these people were interested in family and traditional values. They weren’t that interested in advancing the causes of historically disadvantaged groups—women, minorities, gays. While I was fortunate to grow up in a stable, loving, two-parent family, I recognize the environment painted by J.D. Vance in his excellent memoir “Hillbilly Elegy.”
When I went to college in the liberal haven of Madison, Wisconsin, and pursued a career in journalism, I left most of that world behind. I stayed in touch with my family and a small group of high-school friends. But, essentially, I emigrated from working class, blue collar, rural America to wealthy, elite America.
It’s VERY rare for someone from my socioeconomic background to travel the journey I’ve traveled. Almost nobody I know in journalism or biotech grew up on a farm, qualified for reduced-price lunches at school, or came from a blue-collar family like me. They came mainly from the suburbs, from more privileged backgrounds.
These days, I spend my time in a very privileged zone. Running this newsletter, writing for Forbes, and hosting the Signal podcast means interacting with people who graduated from Ivy League schools, CEOs of companies, and high-level government officials. After a while, it gets comfortable. Normal. It’s easy to forget where you come from.
Even for me, living in urban, liberal Seattle, it’s easy to quickly become blind to vast swaths of America.
Until this past summer, when I had a deep, two-hour conversation with a friend I’ve known since middle school in Platteville, Wisconsin. I’ll call him J.
He is in his early 40s, with two teenage kids, living in a western state. He’s a skilled tradesman who installs sports equipment for schools and churches. He makes a decent middle-class living, and he travels the country on jobs. He also does a little driving on the side for Uber. He’s alone a lot while traveling, and he listens to a lot of conservative talk radio.
J sat in my living room and talked at length, in matter-of-fact tones, about why he was supporting Trump. I told him I strongly disagreed, but I didn’t try to talk him out of it. I decided this was a time for me to listen, and for him to talk.
“The system is broken. Corrupt.”
“We need to blow the whole thing up. Push the reset button.”
“It can’t get any worse.”
“Trump’s not perfect, but he’s not beholden to anyone.”
This kind of apocalyptic view didn’t seem to square with his economic experience. J doesn’t have a college degree, but he’s done well financially for himself and his family. We’ve both flown to Pasadena to watch our beloved Wisconsin Badgers play in the Rose Bowl more than once. J’s experience tells me Trump’s appeal is cultural more than economic.
Despite J’s economic success, he has some serious anxiety and resentment beneath the surface. He rails against the popular notion that “everybody must get a college education” to get ahead, that the economy should be only knowledge-based. This has been an uplifting message of both political parties for a long time. That cultural value system, and programs to advance that policy objective, have created a lot of opportunity for people who previously had limited educational opportunity.
It also has created a downside: People like my friend J feel like second-class citizens because of a lack of college education. He feels condescended to in the media, and laughed at in sit-coms and movies. Conservative talk radio fans the flames. Think about how many people who work in construction, at the post office, in the trash hauling business, feel the same way. They want a president who takes them seriously.
It would be easy to write off my friend J as narrow-minded and simple. That’s where too many elites go wrong. He may not be formally educated, but he’s one of the most curious people I know – much more curious about biotech than most college-educated people. J always wants to hear about the exciting advances I’m writing about in biotech. He pulls out his iPhone and avidly listens to the Signal podcast.
After one show on the rise of superbugs, he wrote:
I really wish that kind of topic would make more news. People really have no clue how much damage can be done to themselves and others. It’s good that the medical community is getting on top of it, but the public really needs to be educated. My biggest complaint with your podcast is there is not enough of them.
These are the words of someone who cares about his country, cares about issues, just like I do. He’s not a wingnut.
There certainly are angry people out there, and many of them have reason to be angry at the establishment. When I drove my family hundreds of miles across the American West this summer to vacation in Yellowstone National Park, I saw some troubling things. There were destitute run-down buildings in Montana, where heroin and oxycodone was easy to spot.
In eastern Idaho, I saw a giant Confederate flag hoisted above the American flag. Further down that same junk-strewn highway, when I stopped for lunch with my African-American wife and daughter, a man driving a sport-utility vehicle gave me a 30-second, intimidating staredown.
Message: Your kind isn’t welcome here.
These people are being left behind, and that’s not right.
Today, after the Trump victory, my friend J was cautiously optimistic. “At the very least, it is a massive shake up to our political system, that definitely needs the shaking,” he wrote.
The pharmaceutical industry may be breathing easy today, knowing that Clinton’s drive to corral drug prices has been squashed. Thoughtful people in this industry are working on solutions focused on people in red America, but there aren’t enough.
This industry would be wise to remember that it serves the whole country, the whole world. It’s easy to get comfortable with the tiny slice of elite investors, elite media, elite physicians, and elite scientists we know personally. It’s easy to forget everyone else.
As people re-assess the pharma industry’s social contract, it’s important to remember just how big a place the world is.
Story of the Week
This, in my view, was the single most disturbing scientific report of the week. Turns out kids aren’t bulletproof to COVID19, after all. This new cohort study from Italy reinforces a similarly mysterious case series of massive inflammation and multi-organ failure in kids in New York City, which was closely followed by corroborating reports from doctors in France.
This toxic shock syndrome in kids is deeply worrying to parents. It could also be an eye-opener for the large and vocal faction in the US that has been arguing that we should shrug off the pandemic partly because “oh, it’s just old people dying.” We can’t shrug off the virus and turn the clock back to 2019. That’s not going to happen. People are dying. Many more will die because of our inaction and incompetent federal leadership. As a result, we have to come to terms with a new way of life.
It’s up to us how we reinvent the world.
The Wild West
Compare that with the NYT caseload chart for Wisconsin. The rate of new cases in Wisconsin is slowing. Good. But the bear hasn’t yet been wrestled to the ground. The virus is nowhere close to contained.
It’s way too early to declare victory and hit the bars. Based on what we know about the epidemiology, you can set your calendar for an increase in cases in Wisconsin in 2-3 weeks. Part of me wants to scream at the people who are jamming themselves in, elbow-to-elbow into the bars without masks. Many probably don’t know anyone with COVID19. Many probably think the media elites are manufacturing fear and controversy. Many want to “own the libs.” Many take delight in thumbing their noses at Gov. Tony Evers, a Democrat who had extended the state’s stay-home order, until it was struck down by the conservative majority on the Wisconsin Supreme Court.
Many of these protesting citizens also know 85,000 are dead, the death toll grows every day, and that’s terrible.
But people do seem to forget many relevant facts. Such as:
It’s a lot to ask members of a free society to stay up-to-the-minute on all the fast-moving science news. Especially when so many have been coached to distrust everyone and everything. But now that quite a few people seem to think they’ve “sacrificed enough” and it’s time to hit the bars, we have to brace ourselves for a lot more sacrifice.
Science
Science Features
Testing
Treatments
Investigations
Policy & Politics
Strategy
Vaccines
The Dysfunctional US Health Care System
Manufacturing and Access
Thinking Big
Illumina and Genomics England are teaming up on a study across the UK’s National Health Service. They’re doing whole genome sequencing on 20,000 people currently or previously in an intensive care unit with SARS-CoV-2, plus another 15,000 people with mild or moderate symptoms.
Personnel File
Dr. Michelle McMurry-Heath was named the new president and CEO of the Biotechnology Innovation Organization. She replaces Jim Greenwood on June 1. Dr. McMurry-Heath represents quite a turn in direction at the industry trade group. She has outstanding credentials as a physician-scientist. She has experience at the FDA and in regulatory affairs at Johnson & Johnson. She’s African-American. She speaks about social justice. All of this makes for a strikingly different background than her predecessor, who came to BIO primarily because of his political relationships and knowledge from the years when he was a Republican member of Congress from Pennsylvania. I don’t know Dr. McMurry-Heath. But I am happy to see a black person get the top job at BIO, and am eager to see what she does in this role. See STAT’s coverage of the new BIO leader.
Moncef Slaoui was tapped to head up the vaccine effort for Operation Warp Speed, the US federal government response. He’s a partner with Medicxi Capital, and a former head of GSK’s vaccines division.
Mike Varney is stepping down from one of biopharma’s most scientifically influential jobs as head of Genentech Research and Early Development (gRED). He’s leaving at the end of July. He’s being replaced by Aviv Regev, a faculty star at the Broad Institute, and a leader of the Human Cell Atlas. (See Dr. Regev’s comments for a December 2019 TR article on the emergence of single-cell sequencing).
Atul Gawande, the celebrated surgeon and author, stepped down from his role as CEO of Haven, the Amazon-JPMorgan-Berkshire Hathaway backed company. He said he plans to focus more on COVID-19.
Cambridge, Mass.-based Celsius Therapeutics, a company leveraging single-cell sequencing techniques for the treatment of cancer and autoimmunity, hired Jeanne Magram as chief scientific officer. She replaces Christoph Lengauer, a partner at Third Rock Ventures who co-founded the company, and who will remain as an advisor and board member to the startup. Rene Russo, CEO of Xilio Therapeutics, also agreed to join the Celsius board.
Waltham, Mass.-based AMAG Pharmaceuticals cut 30 percent of its workforce, or 140 workers.
Financings
Deals
Cambridge, Mass.-based Bluebird Bio and its partner, Bristol-Myers Squibb, were dealt a whopper of a setback at the FDA. The regulatory action said it can’t yet begin to review the application submitted to review ide-cel (bb2121), a BCMA-directed CAR-T immunotherapy for patients with multiple myeloma. The agency said more detail is required in the chemistry, manufacturing and control section of the application – and it can’t begin a formal review of the application until that work is done.
That’s a screw-up. The same day it announced this unforced error, Bluebird announced that it had renegotiated its partnership. BMS agreed to pay $200 million now so it doesn’t have to pay Bluebird milestones and royalties in the future on sales generated outside the US for both ide-cel and a second-generation BCMA-directed cell therapy. The companies will continue to split sales equally in the US. Bluebird stock traded as high as $63.55 the day before the announcement, and closed May 14 at $54.06.
Boehringer Ingelheim agreed to acquire Northern Biologics, a developer of drugs aimed at the tumor microenvironment. Terms weren’t disclosed.
Kirkland, Wash.-based Prevencio agreed to work with Seattle Children’s Research Institute to repurpose the Prevencio blood testing platform to detect signs of Kawasaki syndrome, a rare and very dangerous inflammatory reaction similar to the kind of inflammation seen in children with SARS-CoV-2 infections.
Data That Mattered
Brisbane, Calif.-based Myokardia said it hit all primary and secondary endpoints in a Phase III study of its mavacamten treatment for hypertrophic cardiomyopathy. The company issued a standard top-line press release with statistically significant p-values, showing the favorable result was not the result of chance. Like many companies in this enviable spot, MyoKardia held back the more meaningful details on the magnitude of clinical benefit seen in patients on the drug compared with the placebo. That will come later at a medical meeting, the company said. Immediately after announcing success, MyoKardia cashed in on the momentum in its stock price. It raised $551 million by selling 5.25 million new shares at $105 apiece on May 12. Shareholders won’t mind the minor dilution, as shares rocketed from $61.09 prior to the announcement all the way to $118 on May 14.
Regulatory Action
AstraZeneca and Merck won FDA clearance to market the PARP inhibitor olaparib (Lynparza) as a maintenance therapy for patients with advanced ovarian cancer, in combination with Roche/Genentech’s VEGF inhibitor bevacizumab (Avastin). The approval is for patients with homologous recombination deficiency, an umbrella term that includes patients with a BRCA gene deletion, suspected BRCA gene mutation, or genomic instability. The drug was found to extend survival by a median of 20 months in combo with the VEGF inhibitor, compared with the VEGF inhibitor alone.
Eli Lilly won FDA approval for selpercatinib (Retevmo) for patients with lung and thyroid cancers driven by RET gene mutations or fusions. This is one of the drugs Lilly obtained through its $8 billion acquisition of Loxo Oncology.
Abbott Laboratories won an FDA Emergency Use Authorization of a new COVID19 antibody blood test that runs on its Alinity i System. It has 99.6 percent specificity and 100 percent sensitivity, the company said. The new test is part of Abbott’s plan to ship 30 million antibody tests worldwide in May.
RUCDR Infinite Biologics, a bioprocessing lab affiliated with Rutgers University, won FDA clearance for the first saliva-based at-home test to detect SARS-CoV-2 infections. The test was developed in collaboration with Spectrum Solutions and Accurate Diagnostic Labs.
Quidel won FDA Emergency Use Authorization for a SARS-CoV-2 antigen test that can be run in 15 minutes. It detects active infection in samples collected from nasopharyngeal swabs, like the existing PT-PCR tests. It’s not as accurate as RT-PCR tests, but can be performed in point-of-care settings that have Quidel’s benchtop Sofia 2 analyzer.
Tweetworthy
Today’s guest on The Long Run is Larry Corey.
Larry is one of the nation’s best-known virologists and vaccine developers. Much of his research over the years has been on HIV, herpes simplex viruses, and viruses associated with cancer.
Larry Corey, MD; President and Director Emeritus; Member,
Vaccine and Infectious Disease Division, Fred Hutch; Principal Investigator, HIV Vaccine Trials Network
He’s the founding director and principal investigator of the HIV Vaccine Trials Network – a collaborative group to study vaccine candidates at 30 sites around the world. He’s based in Seattle at the Fred Hutchinson Cancer Research Center. He served as president and director of that institution in the early 2010s, but now is back to running his own virology lab.
Larry has spent 50 years thinking hard about viruses and how to combat them, dating back to a stint at the CDC during the Vietnam War days. Early in his career at Burroughs-Wellcome, working with future Nobel laureate Dr. Gertrude Elion, he developed acyclovir as the first effective therapy for genital herpes. As director of the AIDS Clinical Trials Group, he led the organization that proved combination antiretroviral treatments could control HIV. The team later demonstrated that these drugs could reduce transmission of HIV from mothers to their infants.
This whole set of experiences has shown him what each major player in the scientific enterprise brings to the table – academia, government, and industry.
All of this makes him a great person to talk to now about vaccine strategy for COVID-19. Just before we recorded this episode May 12, he published a perspective piece in Science with Tony Fauci, John Mascola and Francis Collins of the NIH. They wrote about how to think about spinning up an unprecedented global vaccine effort against the pandemic. See that strategy paper here.
This is a timely and frank conversation about one of the most important aspects of the pandemic response.
Please join me and Larry Corey on The Long Run.
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JessicaSagers, PhD; head of engagement, RA Capital
Last week ICER released a report concluding that Vertex’s groundbreaking triple-combination cystic fibrosis (CF) drug, Trikafta, is too expensive for the value it provides to patients.
By all scientific and clinical standards—including ICER’s own—Trikafta, a novel combination of a CFTR potentiator and two correctors, is a transformative drug. It compensates for a mutation present in 90% of all CF patients, turning a disease that has long been a death sentence into a manageable chronic condition. Following stellar Phase 3 data, the FDA approved Trikafta five months ahead of schedule. The patient, physician, and research communities exploded in exuberance when it was approved. NIH director Francis Collins, who helped discover the CFTR gene in 1989, whipped out his guitar and sang on stage in celebration.
ICER awarded Trikafta an “A” – its highest grade – for “certainty that Trikafta provides a substantial net health benefit over standard of care.” However, the magnitude of this achievement did not translate to a favorable review on price. Trikafta is priced comparably to similar drugs for rare conditions, at just under $24,000 per month in the US. And that’s a list price – insurance plans and Medicaid pay a lower but undisclosed net price, so after typical discounts and rebates (~15%), Trikafta’s net price is likely closer to $20,000 per month.
Once a patient starts on the drug, they have to stay on it to manage their disease. That’s not unusual for small molecule drugs or injectable biologics. But Trikafta works better for CF than most drugs work for their respective rare diseases. Even so, in ICER’s words: “Despite [Vertex’s CF drugs] being transformative therapies, the prices set by the manufacturer – costing many millions of dollars over the lifetime of an average patient – are out of proportion to their substantial benefits.”
This assessment caused an outcry among patients and foundations. They argued that the drug is a life-changer, and that ICER’s analysis didn’t include important variables that matter to patients. In a sentence that shocked CF families, ICER argued that even if Trikafta were able to generate a total functional cure such that patients never experienced any complications related to their disease, the drug would still not be worth paying for at the price set by Vertex:
“As an extreme scenario analysis, we evaluated Trikafta as a curative therapy and found that the cost-effectiveness ratio of lifetime therapy with Trikafta continued to far exceed commonly used cost-effectiveness thresholds even under the assumption that it maintained individuals with CF in normal health such that they never experienced any symptoms or complications of CF.” (emphasis added)
The callousness of this response aside, it isn’t that a drug—or even a cure—can never be overpriced. That’s conceivable, especially in the absence of any competition. But ICER tries to make the point that Trikafta is overpriced while leaving a lot of math on the table that does not suit its argument.
It’s worth exploring those overlooked variables and the societal norms that underlie value-based pricing analyses, which CF patients have cited in their defense of this vital medicine. It’s especially important to take this broader view considering how those norms might change following the COVID-19 pandemic. Let’s explore more accurate ways to model cost-effectiveness so that we don’t risk talking ourselves out of inventing what we really need.
Healthcare costs in the United States are on the rise and will continue to increase. This is because paying for the time and expertise of trained medical professionals, keeping hospitals and clinics clean and operational, and maintaining the huge administrative burden of our medical system is expensive and will remain so. These costs are like an ever-rising rent that we as a society will always have to pay.
But drug costs are mortgages, not rents. Drugs are the only element of the healthcare system that not only pay for themselves but save our system money in the long run. How? They go generic. After a new drug enjoys a finite branded period, patents expire, competitors enter the market, prices drop by 85-90%, and that advancement belongs to society as a low-priced generic forever. By law, Trikafta will go this route one day, too, most likely within about 15 years from its launch, as nearly all small-molecule drugs do. Vertex’s monopoly is temporary, not permanent, by design.
But ICER’s methodology does not take into account the fact that any drug will go generic. Instead, they model the drug’s launch price as its price each year for the entire lifespan of each patient, wildly overestimating its total lifetime cost.
For the sake of argument, let’s assume an average CF patient starts taking Trikafta at age 10 and gets the patented drug for 15 years. If the patient remains in steady health, as would reasonably be assumed based on the drug’s profile, that 25-year-old patient in the year 2035 can expect many more years of healthy living on this drug at a less expensive generic price, not today’s premium branded one. ICER isn’t unaware of this flaw; rather, they expressly refuse to address it.
When called out on this point multiple times by CF patients and foundations, ICER punts:
“As is consistent with best practices at international HTA agencies and with the great preponderance of academic work in health economics, ICER’s cost-effectiveness analyses do not routinely make estimates of price changes across comparator treatments linked to patent and exclusivity time horizons, especially given the unpredictability of these changes in the US health care market.”
Yet the fact that a small molecule drug like Trikafta will go generic is one of the few predictable things about healthcare. One can model the possibility that some patent gamesmanship may result in a few years’ delay of a generic launch (inappropriate though it may be), but when modeling value on the scale of decades, these uncertainties hardly alter the fact that Trikafta’s genericization is inevitable. ICER argues that uncertainty in the timing of genericization and whether the price will drop by 80%, 85%, or 90% precludes modeling it at all. This is a disingenuous strategy, to say the least, and ignores a simple modeling assumption that can and should be factored in.
Economists who have modeled the impact of genericization have pointed out that doing so reveals a drug to be two- to three-fold more cost-effective than misrepresenting its mortgage cost as rent. Payers, regulators, and the biotech community should spurn ICER’s analyses if they continue to neglect drugs’ core value proposition. At this point, continuing to refuse to account for genericization is tantamount to perpetuating disinformation.
What would it be worth to you to know that if you contracted COVID-19, there would be a safe, effective treatment to get you back on your feet?
What would that peace of mind do for you when deciding whether to allow family members to go back to work or school?
What would such reassurance do for the global economy?
The COVID-19 pandemic illustrates that another vital benefit that drugs provide (and value-based pricing analyses fail to capture) is peace of mind: the freedom to act, plan, and work without the threat of a disease hijacking your life.
The mother of a CF patient captures this intangible benefit in her exchange with ICER:
CF Mother: ICER’s report fundamentally fails to capture the monumental progress my son has achieved thanks to this triple-combination therapy. Increased pulmonary function is important, but it is the freedom to prepare for a fruitful future rather than to prepare for death that matters most. The larger point here is that the improvements that matter most to patients are not at the center of ICER’s cost-effectiveness analysis.
ICER: We modeled Trikafta as a cure and it still did not meet societal norms for cost relative to benefit.
What ICER dismisses is that “societal norms for cost relative to benefit” are ours to set. ICER’s “societal norms” reflect the norms of its own staff, and certainly the publicly stated sensibilities of its major backer, billionaire John Arnold. But they do not represent those of the majority of Americans, who view healthcare as a human right. America excels in nurturing the kind of innovation that advances its goals. It is within our country’s means and abilities to improve our health and that of the world.
With the capabilities of biomedical innovation now on display and the world calling for more COVID-19 investment from all of society’s pockets – government, insurance, non-profit, and private sector – the pockets that everyone acknowledges we must not reach into are those of patients. Patients need affordable drugs, and America can make that possible not just for most, as it does now, but for all with proper insurance reform. That means ensuring that all Americans are insured and minimizing barriers to access for essential medications (i.e. by reducing out-of-pocket costs). Then we can collectively incentivize and fuel innovation to solve our unmet needs. We can do that by paying branded prices that, while seemingly high per patient, are finite and, in the long run, represent better value than continuing to suffer from the diseases that plague us.
Right now in the US, because of Trikafta, about 30,000 patients have a new, hopeful outlook on life. Every one of them is surrounded by family members that can now worry less about managing the disease and start thinking more about pursuing their own dreams. There is substantial human potential that can be unleashed whenever a powerful new drug like Trikafta comes along.
Until we achieve insurance reform for everyone, we can put some patches in place to pay for this advance. The COVID-19 pandemic has already shown us that this is doable: for example, by capping insulin copayments at $35 for everyone regardless of insurance status and offering many medicines for low fixed costs to tens of millions of the uninsured. If drugmakers and insurers can do this for patients now, they can do it in the future.
It’s time we recognize that value can’t be captured by a single organization’s formula – especially one with the gall to insist a launch price lasts forever and that disregards the value of curing a devastating disease for ourselves and future generations. It’s hard to think of a societal norm more American than investing towards an accomplishment as immense as conquering CF, taking pride as a nation in getting the job done, and celebrating the heroes who did it.
RA Capital is a registered investment adviser. This material is not intended, and should not be construed as, investment advice or recommendation to invest in any security. Likewise, this material is not intended as a solicitation to invest in any RA Capital product or service.
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Luke Timmerman, founder & editor, Timmerman Report
We’re suffering from a social disease. It ranks up there with COVID-19.
It’s boundless cynicism.
We need to tamp this down. Just like we need to wrestle the new coronavirus to the ground.
I’m not willing to accept “shit happens” as the national motto. This is a country of can-do problem-solvers. We can do so much better.
You can see the frightening level of callousness and self-centeredness, running like toxic rivers through our communications central nervous system.
First it was “oh it’s just old people dying.”
Then it was “oh, it’s just prisoners dying.”
Then it was “oh, it’s just some low-wage workers in meat-packing plants.”
Then it was “oh, it’s only 76,000 dead, and 2,000 more dead per day. It could have been worse.” Shit happens. Nothing you do about it.
Who cares?
I do. I care about people suffering and dying. I care about millions of people being out of work. We can reduce the toll of death and suffering while we also carefully re-open the economy. We can walk and chew gum. We have to. A long-term national lockdown can’t be sustained.
We have incredible capacity for problem solving. The United States of America is loaded with wealth and creative brainpower and people of good faith. We have talented women and men working day and night. In academia. In industry. In our state and local governments. And yes, across the federal government – at agencies like NIH, CDC, FDA, and the DOD.
People of good faith need to double-down in our efforts to combat the viral pandemic. And to combat the helplessness and carelessness fostered by this cynicism. Especially at this tense time, as antsy citizens everywhere start mixing and mingling while the virus is still spreading.
It will be a long, hard slog. There’s no doubt what it will take. Testing and tracing at scale. Well-designed randomized drug trials. A handful of bets on a portfolio of vaccine candidates. All of us wearing masks and limiting social contacts for longer than we’d like. Being kind and patient and empathetic.
We shouldn’t delude ourselves that this problem will magically fade away in August like one prominent model seems to predict. We shouldn’t tell ourselves that a Big Hairy Audacious Goal of a vaccine by end of 2020 or early 2021 is some kind of realistic expectation.
It will be immensely hard. It will take stamina. There will be setbacks. While this work carries on, we’ll have to tolerate the merchants of bad faith and their legions of followers doubting every one. We will have to turn the other cheek from time to time, as Internet and TV provocateurs traffic in the cynicism that butters their bread, and enables them to drown out the voices of reason. People will be encouraged, and tempted, to throw up their hands in despair.
We will not let the bastards get us down. We will remain steady and focused.
We will all need an occasional pick-me-up along the way.
This week, I’m leaving you with a couple things to lift your spirits.
One is the 1989 hit “I Won’t Back Down.” Watch Tom Petty belt out this anthem for steely entrepreneurs everywhere, and chuckle at the hair (which may be coming back into style, at least for this editor whose last haircut was in early January).
The other is the 1993 ESPY award speech by former North Carolina State University basketball coach Jim Valvano. He was dying from cancer. He said: “Don’t Give Up.”
Now, on to the highlights of the week in biotech.
Science
Science News and Features
Epidemiology
Humanity
Access
Policy & Politics
Investigations
Communication
TR Coverage of the Week
Treatments
Cambridge, Mass.-based Evelo Biosciences, with Rutgers University and Robert Wood Johnson Hospital in New Jersey, started up a Phase II trial of Evelo’s oral therapy for patients hospitalized with COVID19. The Evelo drug candidate, EDP1815, is a “monoclonal microbial” that has shown an ability to suppress production of multiple inflammatory cytokines – IL-6, IL-8, TNF, IL-1beta — that can spin out of control into dangerous cytokine storms. The drug showed that effect in a previous Phase Ib psoriasis study and in preclinical models. There’s a real therapeutic rationale, given the observation that many severely ill COVID19 patients suffer from cytokine storms. Take that rationale, combined with a randomized, placebo-controlled study design, moving at pandemic speed, and you have a model for how things ought to be done. Data on safety and efficacy are expected in the second half of 2020. (Disclosure: Evelo CEO Simba Gill was on my Kilimanjaro Climb to Fight Cancer team last summer in Tanzania. I did a little fist pump for him and his team when I saw this trial).
Testing
Adaptive Biotechnologies announced a plan to start a 1,000-participant study called ImmuneRACE, which will look at antibodies to develop more fine-tuned diagnostics for COVID-19. The company, developer of an immune sequencing platform, is supported by its big cloud computing and analysis partner, Microsoft, and LabCorp of America, which will handle collection of blood and nose/throat swab samples that patients can take without having to leave home. (Read Adaptive CEO Chad Robins explanation of the study, and his thoughts on managing in this hard time on TR).
Deals
Moderna, the mRNA vaccine and therapeutics company, struck a deal with Lonza, the contract biologics manufacturer, to manufacture as much as 1 billion doses of its mRNA vaccine candidate. That’s a big number of doses, which everyone wants to see in a pandemic. But you have to read the release. It assumes the lower dose being tested now in a brand-new Phase II trial – a 2-shot prime-boost regimen of 50 micrograms, 28 days apart — will be the dose that provides a sufficient immune response. The other dose being tested in Phase II is 250 micrograms. Clearly, if that’s necessary, something will have to happen to boost manufacturing capacity to get to 1 billion doses.
VIR Biotechnology and Alnylam Pharmaceuticals said, after just three months of specific collaboration on RNA interference drug discovery for COVID19, that they’ve nominated a lead candidate for clinical trials, scheduled to begin around year-end 2020. Of the 350 candidates synthesized by Alnylam, multiple candidates were shown to deliver a three-log (three orders of magnitude) reduction in viral replication in a live virus assay in the petri dish experiments conducted by VIR. The lead candidate is being made into an inhalable formulation to get good distribution into the lungs.
Alexion Pharmaceuticals agreed to pay $1.3 billion in cash, $18 a share, to acquire Portola Pharmaceuticals, the hematology drug developer.
Magenta Therapeutics and AVROBIO, a couple of development-stage biotech companies in the Boston cluster, struck an unusual innovative smallco + innovative smallco partnership (as opposed to the usual innovative smallco + rich largeco deal). In this case, Magenta brings its antibody-drug conjugate to the table to enhance the conditioning of AVROBIO’s lentiviral gene therapies. Both of these companies have their roots in the Atlas Venture portfolio, so the players know each other well enough to entertain this sort of unusual alliance.
New York-based Stemline Therapeutics agreed to be acquired by Italy-based Menarini for total consideration of up to $677 million.
South Plainfield, NJ-based PTC Therapeutics agreed to acquire Censa Therapeutics, the developer of treatments for orphan metabolic diseases such as phenylketonuria (PKU). PTC is paying $10 million cash upfront and 850,000 shares of PTC stock (market value: $46.91 a share on Thursday), plus potentially $217 million in milestones.
Eli Lilly agreed to work with Shanghai-based Junshi Biosciences to develop neutralizing antibody therapies against SARS-CoV-2.
San Rafael, Calif.-based BioMarin Pharmaceutical struck a partnership with DiNAQOR to develop gene therapies for rare cardiomyopathies.
Financings
Waltham, Mass. and Montreal-based Ventus Therapeutics secured a $60 million Series A financing led by Versant Ventures and joined by GV. Cash will be used to advance three pipeline programs based on structural immunology insights on how to make small molecules versus hard targets of the innate immune system.
Cambridge, Mass.-based Praxis Precision Medicine announced its debut with $100 million in financing from inception, led by founding investor Blackstone Life Sciences. It’s working on rare brain diseases.
Grail, the early cancer detection company in Menlo Park, Calif., raised $390 million in a Series D financing. That’s a lot of money. It’s also a lot less than the company raised in prior venture rounds. See TR coverage from Grail’s founding in January 2016.
Bridgewater, NJ-based Insmed fetched $259 million in a public offering of 11 million shares at $23.25 apiece.
Redwood City, Calif.-based Pulmonx raised $66 million to further develop its minimally invasive valve for treatment of severe emphysema. Ally Bridge Group led.
Lyra Therapeutics raised $56 million in an IPO at $16 a share to advance its ear-nose-throat programs. Sorry, I missed this one from Apr. 30.
Vapotherm, an Exeter, NH-based med tech company focused on respiratory distress, raised $87.5 million through a public offering of 3.35 million shares at $26.
Carlsbad, Calif.-based GenMark Diagnostics raised $70 million in an offering of 7.2 million shares at $9.65 apiece.
San Diego-based Kura Oncology raised $125 million in a stock offering of 9.1 million shares at $13.75.
Sunnyvale, Calif.-based Silk Road Medical, a company working on stroke risk reduction, raised $75 million in a stock offering.
Personnel File
Alex Aravanis, the co-founder and chief scientific officer at Grail, is returning to Illumina to be the chief technology officer at the DNA sequencing market leader. Mostafa Ronaghi, the longtime CTO at Illumina, will move over to a new role as SVP of Entrepreneurial Development at Illumina. Ronaghi also joined the board of Grail, which spun out from Illumina four years ago to work on early detection of cancer.
Brian Di Donato was hired as chief financial officer and head of strategy for Immunocore, the UK-based company developing T-cell receptor therapies for cancer. He was previously CFO at Achillion Pharmaceuticals.
Stephen Webster joined the board of TCR2 Therapeutics, a cancer immunotherapy company working on T-cell engineering. He’s the former CFO of Spark Therapeutics.
New York-based Lodo Therapeutics hired Donald Marvin as chief financial officer.
Seattle-based Impel Neuropharma said that chairman Adrian Adams will be taking over day-to-day leadership as chairman and CEO, effective immediately, and that previous CEO Jon Congleton will be leaving the company.
Sutrovax named Andrew Guggenhime as chief financial and chief business officer.
New York-based Schrodinger, a computational drug discovery company, named Jeffrey Chodakewitz and Gary Ginsberg to its board of directors.
Burlingame, Calif.-based ALX Oncology named Rekha Hemrajani to its board of directors.
Data That Mattered
Regeneron Pharmaceuticals and Sanofi said the PD-1 inhibitor cemiplimab (Libtayo) passed a pivotal study of patients getting their second round of therapy with locally advanced basal cell carcinoma.
Roche offered a preview of presentations it plans to release at the ASCO virtual meeting in late May, including results from a Phase II study of tiragolumab, Roche’s novel cancer immunotherapy designed to bind to TIGIT, being tested in combo with its PD-L1 inhibitor for non-small lung cancer.
Cambridge, Mass.-based Akebia Therapeutics said it passed the first of two Phase III clinical trials with its vadadustat, an experimental treatment for anemia in patients on kidney dialysis.
Regulatory Action
Gilead Sciences, on May 1, secured an FDA Emergency Use Authorization for remdesivir, the first antiviral treatment for hospitalized COVID-19 patients. The company said it would donate all its supplies to the US government, which will now handle distribution to hospitals. Days later, regulators in Japan cleared the drug for use there. See FDA Fact Sheet for patients and caregivers.
Roche won FDA Emergency Use Authorization for a serology test (antibody test) with an impressive 99.8 percent specificity rate and 100 percent sensitivity rate. The healthcare giant said it would provide “high double-digit millions of tests” per month, starting in May. These are the kind of tests that will be crucial to give people confidence to go back out and about as countries around the world have to gradually lift their physical-distancing restrictions.
The FDA, after being accused of foot-dragging on approvals of PCR diagnostic tests in the early days of the pandemic, was accused of going into a dangerously laissez faire Wild West mode with the next round of tests – serology tests to assess antibody production against the virus. On May 4, the agency pumped the brakes, ordering manufacturers of antibody tests that lack data to cough up data on test accuracy in the next 10 days or else get yanked off the market.
AstraZeneca won FDA clearance for dapagliflozin (Farxiga) to reduce the cardiovascular death and hospitalization in patients with heart failure. This approval opens up a large new patient population for this oral, once-daily SGLT2 inhibitor. The drug was originally developed for Type 2 diabetes and continues to be marketed for that indication as well.
Novartis got the FDA green light to start marketing its MET inhibitor, capmatinib (Tabrecta) metastatic non-small cell lung cancer (NSCLC) whose tumors have a mutation that leads to MET exon 14 skipping (METex14). Foundation Medicine provides the FDA-approved companion diagnostic to identify the 4,000-5,000 patients in the US who are thought to be good candidates for this drug.
Cambridge, Mass.-based Sherlock Biosciences won an FDA Emergency Use Authorization for a simplified CRISPR-based diagnostic test for COVID-19. The company’s scientific co-founders include Feng Zhang of the Broad Institute, David Walt at Mass General Hospital (founder of Illumina), and Jim Collins of MIT. The hope is this will be a quick and cheap test that will allow for testing capacity to increase. (See NYT coverage by Carl Zimmer). Further scientific background at STOPCovid.
Johnson & Johnson and Genmab won FDA clearance for daratumumab hyaluronidase-fihj (Darzalex Faspro) as a new subcutaneous injectable form of the drug for multiple myeloma.
Tweetworthy
Much is being said about a spirit of collaboration in industry. That’s good. What’s better are hard and fast and lasting changes to the way clinical trials are done. See comments by Andy Plump of Takeda. h/t Pearl Freier.
Worth a Watch
NIH Director Francis Collins, in his inimitable and lovably nerdy way, plays this adapted tribute song to frontline healthcare workers in the COVID19 pandemic, to the tune of “Imagine” by John Lennon. Watch this for 4 minutes and it will brighten your day.
David Shaywitz
The value of randomized controlled trials (RCTs) in healthcare delivery was highlighted earlier this year with the publication in the New England Journal of Medicine (NEJM) of a paper that rigorously evaluated a deeply appealing hypothesis: that you can improve care and reduce costs by focusing on “superutilizers” – the patients who consume the most healthcare resources.
I discussed this paper, and some associated issues, at a recent Harvard Department of Biomedical Informatics (DBMI) faculty journal club, and thought a few highlights might be of particular interest to TR readers.
The story of the trial is captured magnificently by the Tradeoffs podcast – you can listen here, and read a helpful summary here.
The protagonist is a New Jersey physician named Jeffrey Brenner, who became interested in better serving patients in Camden, New Jersey. It’s a city with 74,000 people across from Philadelphia. About 42 percent of the population is African-American, and about 37 percent of the population lives in poverty, according to the US Census Bureau. After reviewing hospital data, Brenner realized that hospital use, and more generally, healthcare costs, weren’t evenly distributed.
In this population, like others, a small percentage of patients (about 5%) accounted for the vast majority of healthcare costs (~ 50%). This group of people has been dubbed the “5/50’s.” Many of these “superutilizers” are patients facing a remarkably complex group of social and economic challenges that can make life, and health, disproportionately difficult for them.
Brenner’s hypothesis was that a key challenge these patients face is engaging effectively with the healthcare system, and by providing them with a team of guides (sort of like sherpas), to help coordinate their care, the patients’ health would improve, and hospital utilization would decline. Initial work seemed to bear this out – healthcare costs and utilization seemed to go down for the first several dozen patients treated in this program.
It all seemed to make a lot of logical sense.
Brenner’s star really began to rise after his efforts were profiled by Atul Gawande in an inspirational New Yorker article, “The Hot Spotters,” in 2011; Brenner received a MacArthur genius award in 2013, and his program was widely hailed as a success, which many sought to emulate.
Yet Brenner, it turns out, encountered skeptics at health conferences. To his exceptional credit, he recognized the need to further test his hypothesis, and really pressure-test his program, through a randomized control study.
This trial was led by an independent, trusted group from MIT, led by noted economist Amy Finkelstein. Brenner himself left to join United Healthcare Group in 2017, attracted, he said, by the opportunity to apply some of his learnings from an even larger platform – that of the world’s largest insurer.
The MIT results, published in the NEJM in January 2020, were disappointing. There was no difference between control and treatment arms in the number of hospital readmissions within 180 days – the primary endpoint. Moreover, both groups showed a decline in utilization, suggesting that the previously-observed decrease seen in the first group of patients may well have represented simply an example of the well-described phenomenon of “regression to the mean.”
There are several relevant lessons we might learn here.
First, the study highlights that even – perhaps especially – when there’s a compelling narrative, it’s critically important to perform the rigorous study to be sure that what you might so desperately want to believe is actually true. There are so many ways we can fool ourselves, and so many potential confounders; RCTs – while not without their own issues, in particular, generalizability – help minimize the effect of bias, which is why they’re appropriately considered the gold standard.
The value of randomized controlled trials (RCTs) is perhaps most acutely felt in situations where the truth feels self-evident, to the point where actually doing a study can strike some as unethical.
Prominent examples from the history of medicine are the use of an anti-arrhythmia drug to reduce sudden cardiac death after heart attacks (the intervention seemed intuitive, yet the CAST study revealed the drug actually made things worse); the routine use of pulmonary artery catheterization in critically ill patients (collecting more data intuitively seemed better, yet RCTs revealed no evidence for improvement; a wag even penned an obituary for the device); and perhaps most famously, the use of hematopoietic stem cell transplant for the treatment of breast cancer (the trial was derided by some as unethical given the assumed benefit, yet the approach was found not to improve survival significantly).
The need for careful study is particularly important, and particularly challenging, in areas characterized by what tech entrepreneur Jim Manzi (Tech Tonics interview here; TR discussion in context of AI here) has called high “causal density.”
This is a term referring to “the number and complexity of potential causes to the outcome of interest.” It’s a factor in biological experiments, of course, and an even greater factor, Manzi argues, in areas of social science. If a vaccine works in one population, he says, he’s reasonably confident it will work in another. But if an educational intervention works in one setting, he’s far less confident it will be generalizable, because of all the factors that could be involved.
Perhaps not surprisingly, when many policy measures are actually evaluated by RCTs, most fail. A study from Arnold Ventures revealed that of “13 instances in which the federal government commissioned large randomized controlled trials to evaluate the effectiveness of entire, Congressionally-authorized federal programs,” 11 essentially failed, one yielded modest/marginal benefit, and only one clearly and repeatedly seemed to work: the Department of Defense’s Guard Youth ChalleNGe, intensive, residential youth development program for high school dropouts.
A frustratingly common observation is that initially promising data often fail to stand up to the test of time. As I discussed in a recent Wall Street Journal review of their book, The Power of Experiments, Harvard Business School professors Michael Luca and Max Bazerman share the story of a thoughtful behavioral intervention developed by University of Pennsylvania faculty Katherine Milkman and Angela Duckworth. While initial results looked promising, the effects soon receded – prompting Duckworth (of Grit fame) to observe, “Behavior changes are really *#$@ing hard!”
Yet all may not be lost.
In 2014, a White House Social and Behavioral Sciences Team (SBST) tried to reduce the over-prescription of addictive medicines (Schedule II controlled substances) by sending out a letter informing these doctors they prescribed far more of these medicines than their peers; this type of approach (as I discussed in the Journal) was demonstrably successful in another context — increasing delinquent tax payments, for example.
Yet here, a RCT evaluating this approach failed to demonstrate an impact on prescriptions.
Instead of giving up, however, the team refined their approach, modifying both the targeting of their letter (now focusing on primary care doctors who were unusually heavy prescribers of quetiapine [Seroquel], specifically) and the language used (in addition to peer comparison, the letter noted the doctor was under review by the Centers for Medicare & Medicaid Services [CMS]), and performed another RCT. This time, it seems, the approach worked well; prescribing was reduced by over 11%, a statistically significant effect that persisted for at least two years.
According to experts like Manzi, success in environments of high causal density require just this sort of iterative approach.
“Run enough tests,” he advises, “and you can find predictive rules that are sufficiently nuanced to be of practical use in the very complex environment of real-world human decision making.”
Testing at this scale, Manzi says, requires “integration with operational data systems and standardization of test design,” approaches that are already adopted by a number of organizations within the business world.
Examples, as I discussed in the Journal, include not just tech giants like Google, Microsoft, and Amazon, but also companies like Nike and State Farm, the insurance company. I’ve also discussed the value of “high velocity incrementalism” to use Harvard Business School Professor Stefan Thomke’s term, in TR, here, and in the context of COVID, here.
Strikingly, “run enough tests” turns out to be the advice of Amy Finkelstein, the MIT economist leading the Camden RCT, as well. In an April 2020 Perspective piece in the NEJM, Finkelstein argued that the key to improving healthcare delivery was conducting more RCTs, noting “the increased availability and use of administrative data have made implementing RCTs easier and less expensive than it once was.”
She noted that improved data systems (versus what were available two decades prior) capturing hospital discharge data enabled the Camden RCT study to be done “at substantially lower cost and effort and with less risk of nonresponsive bias” that would have been possible in an era that relied upon survey data collection.
Finkelstein added that “administrative data also enable use of RCTs for low-cost, rapid testing of repeatedly fine-tuned interventions,” citing a 2019 NEJM study from NYU Langone Health, led by my med school colleague Leora Horwitz, reporting the completion of “ten randomized, rapid-cycle quality-improvement projects in one year.”
We’ve seen the ability of deliberate experimentation at scale to impact website traffic and hone the appeal of political messages to voters.
How exciting to contemplate the integrated — and, I hope, routine — use of this process to improve the delivery of care to patients.
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Ruth Etzioni, Full Member, Division of Public Health Sciences, Fred Hutch Cancer Center
As someone who has spent a career building and studying disease models, primarily for cancer, the latest update from Chris Murray and the IHME model makes me cringe.
The IHME model, readers will recall, has been frequently cited by the White House coronavirus task force. On May 4, the IHME called a press conference to release the results of their COVID-19 model update which showed a staggering departure from their prior predictions of about 60,000 deaths through the end of August.
Obviously, this earlier model had to be updated – and fast: the official US death toll was already at more than 68,000 at the time of the May 4 press conference.
The new prediction from IHME through August estimates 134,000 deaths – more than double the previous model’s estimate. Murray, the institute’s director, told reporters that the death toll was significantly increased because the latest update had taken changes in mobility into account. Indeed, travel patterns now show an uptick in movement in states that are beginning the re-opening process, and increased mobility means increased opportunity for infection.
Murray, in a May 4 interview on CNN with Anderson Cooper, said the earlier model was built on an assumption of statewide social distancing measures remaining in effect through May in order to suppress transmission. Now that states are lifting the orders, the model had to be revised to incorporate the fact that “more people are getting out and about.”
While I am in total agreement that premature relaxation of social distancing will lead to an explosion of new cases and deaths, you don’t need a model to know that. That’s how epidemics work when a population is as far away as the US is from herd immunity. And models everywhere are showing the same thing.
Where I live in Washington State, Gov. Jay Inslee and his advisors looked at models that predicted dramatic growth of infections if the state were to relax the Stay Home, Stay Healthy order prematurely. Those models were part of the rationale for extending the stay-home order until the end of May.
It makes a nice story, to tell the world that the reason your model’s predictions have changed is because the population’s behavior has changed. The implication is that it’s not the model’s fault, it’s the politicians and the people’s shifting behavior. Indeed, that was the same explanation given by IHME for their model revising its early death toll of about 90,000 dramatically downward to about 60,000 in early April. At that time, Murray explained that the change in predictions showed that social distancing had been a wild success – better than we could ever have imagined.
The lowering of the death estimate, in turn, led to howls of protest that we had over-reacted by shutting down and staying home. Those howls put pressure on elected officials to relax social distancing. Clearly, models do matter.
On Apr. 14, I wrote in these pages that that the interpretation regarding social distancing success was wrong and misleading and placed far too much credibility in the early predictions. The early model results were based on an oversimplified empirical model. It extrapolated death curves from the earlier experience in China, Italy, and eventually Spain. It assumed that social distancing would work as well as in those settings, and that the pattern of deaths after the peak would be a mirror image of the pattern before it. Revisions of the model tried to soften these assumptions, making many other assumptions along the way. It is likely that these revisions, rather than social distancing success, drove the dive in the deaths predicted in that April revision.
The same thing is happening now. A quick skim of the IHME’s model updated site leads one to an eye-glazing list of changes, including some that have nothing to do with mobility and everything to do with improving how well the model matches the data on cases and deaths recorded up until this point.
When Murray spoke about mobility patterns causing an update to the model, he neglected to say in the same breath that the team had made fundamental changes to its model-building approach in order to arrive at its current set of predictions. IHME is now more like a hybrid of empirical and mechanistic approaches. What we aren’t seeing from IHME is a clear and transparent statement on the truly humbling “back to the drawing board” nature of what it has just done by rebuilding its model.
Here is one change that truly raised my eyebrows:
“Since our initial release, we have increased the number of multi-Gaussian distribution weights that inform our death model’s predictions for epidemic peaks and downward trends. As of today’s release, we are including 29 elements… this expansion now allows for longer epidemic peaks and tails, such that daily COVID-19 deaths are not predicted to fall as steeply as in previous releases.”
This change alters the shape of the assumed mortality curve so it does not go down as fast; it alone could explain a substantial portion of the inflation in the revised mortality predictions.
The proof is in the Washington State pudding. The IHME is no longer predicting that we will have less than one case per million on May 28 and can therefore safely reopen, as it did in its previous incarnation. But little has changed here on the policy front and in residents’ mobility patterns, according to Google Mobility reports, through April.
I am not aiming my comments at the IHME modeling team, which I imagine is sincerely doing its best to deliver results that match the data and produce ever-more-complex predictions of the future. They are working overtime to fit the rapidly evolving and imperfect data, marching to a drumbeat of deadlines from everyone that wants the impossible – crystal clear and precisely accurate forecasts. To their credit, the last part of the May 4 update does note that both model changes and increased mobility projections could account for the change in predictions. But that never made it into the headlines. And that is a problem of transparency.
Transparency begins in the sincere effort by those who communicate models to make sure that they are properly interpreted by the policymakers and public that are using them. The IHME pays lip service to transparency by documenting their model’s updates on their website. But their pages-long description is chock full of technical fine print and is hard to understand, even for a seasoned modeler like myself.
A key part of transparency is acknowledging your model’s limitations and uncertainties. This is never front and center in the IHME’s updates. It needs to be.
It is ironic to me that I am being this critical when I agree so strongly with the message that is being broadcast as a result of this update. Make no mistake – if some states that are opening prematurely, or some that are considering doing so, change their minds as a result of this update, it will a very good thing.
We have to remember that this epidemic took root and grew massively in every state from miniscule beginnings. We should all be sobered by our real-time experience of exponential growth. If there is an ambient prevalence of more than a handful of cases in any state, then anything that increases the potential for transmission will lead to a re-growth. We do not need a model to be able to predict that. But, as we plan for how to reopen in each state of our union, we need to know what extent of growth in new infections we can manage. And models can help us with that.
When and how much we can reopen will depend on the surveillance and containment infrastructure that we put in place to control upticks and outbreaks. I am convinced that models can help us think clearly about complex policy questions – such as finding the balance between changes that increase transmission and measures to contain it. Models, along with other data and evidence, can guide us towards making sensible policy decisions. I have seen this happen time and time again in my work advising national cancer screening policy panels.
But as modelers, we have a responsibility. We have to be humble. We must make sure that the key caveats and uncertainties that are the nature of our work find their way into the headlines and are not relegated to the fine print.
If we don’t, we will give modeling, and modelers everywhere, a bad name.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Luke Timmerman, founder & editor, Timmerman Report
This is a fragile moment.
It’s May 1. Some of us have been in social isolation for two solid months. Everyone’s at some point on the continuum of stir crazy. More than 30 million people are out of work. Tempers are flaring. Protestors are carrying guns. It’s obvious we can’t sustain a maximalist social-distancing policy much longer.
Today, we have half of the 50 states doing some kind of partial lifting of stay-home orders, some variations on gradual re-opening of their economies – even though only 14 states are reporting declines in new cases. Masks, regular deep cleaning, shift work, and physical spacing in normally crowded spaces are all being tried out to mitigate the spread.
This virus is so befuddling, it’s hard to say much of anything about it with certainty. But it seems safe to say that some places will be more successful than others at keeping infection rates down with a careful turning of the dial.
The curves are deeply disappointing. We’re in what looks like a long plateau of steady infection and death. We now have more than 1 million confirmed cases of COVID19, and more than 63,000 confirmed deaths. More than 2,000 people are dying per day.
Our failure to run adequate diagnostic testing leaves us flying blind, unable to execute on the classic test/trace/isolate strategy that everyone agrees is essential, and which South Korea and others have shown works.
We had the tiniest glimmer of encouraging news this week about an antiviral medicine, remdesivir. It was shown in a rigorous NIH-sponsored study to reduce hospitalization time by four days. It’s not much in the grand scheme of things. An improvement in survival rates would be a bigger deal. Still, the result counts for something, because it can relieve some pressure on hospitals.
Really good news, in the near-term, would be the US getting its act together on testing, tracing and isolation. If we do that, then it should be possible for as little as 7 percent or so of the population to be isolated at any one time, allowing the rest of us to go about our business. Betz Halloran, an outbreak modeler at Fred Hutch working with collaborators at Northeastern University, made that remark in a panel discussion I moderated for Life Science Washington a week ago.
How much work needs to be done to get to adequate testing? As of May 1, we have done 6.5 million tests in the US. Grand total since late January. A Harvard group says we need to do 5 million tests A DAY by early June, and 20 million A DAY by midsummer.
We have our work cut out in more ways than one. We can’t duck the testing issue, because vaccines or seriously good treatments in the form of neutralizing antibodies will almost certainly not magically appear before the second wave.
Which brings me to my final point.
Our society needs to take a look in the mirror about how we treat each other, because we’re going to be in this betwixt-and-between mode, with partial re-opening and partial re-tightening, for a while. It’s a psychological tension we will all have to manage for longer than any of us would like.
Pathological selfishness, cruelty, and callousness has been coursing through our information ecosystem for years. Bad faith has been ascendant. A 24/7 information war has been raging, driving millions of people to extreme views that were unthinkable not that long ago.
The virus has struck us at a dark time.
The infowar has depleted our society’s empathy reservoir. You see it in popular Internet memes, like “Boomer Remover.” You see a guy in the Michigan state capitol, taunting National Guardsmen by breathing in their face, as if to blow smoke from a cigarette. You do see acts of kindness and empathy and courage on the news, but they are offset by this ugly behavior. It’s like a stain on our soul.
This is a test for our society.
This moment reminds me of something passed down from my Dad. He was idealistic at first, and then disillusioned, like many Vietnam veterans. He didn’t want his son to enlist in the Army. And yet, he was deeply patriotic. He instilled that spirit in me. It’s still there with me every day. I believe in our institutions like NIH, CDC, FDA. In our universities. In our entrepreneurial spirit. In our form of democratic self-governance – of the people, by the people, for the people. In our Bill of Rights. In our checks and balances that protect us from monarchy and tyranny.
It’s painful to see people traffic in abject cynicism, thumbing their noses at CDC guidance, clamoring for hydroxychloroquine without evidence, and injecting bleach. The erosion of support for and belief in science — as the best rational means for understanding the world — is a devastating indictment of life in the 21st century.
Now we can see how this cynicism about our institutions and our fellow citizens compounds.
We see it in sharp relief in a pandemic that disproportionately harms the most vulnerable. The elderly. Veterans. Prisoners. Black and brown people who can’t flip the switch and work from home. Low-wage workers in meat-packing plants. Native Americans on reservations.
I remember another thing my Dad taught me.
“A society is judged by how it treats the most vulnerable,” he said.
This quote, or variations of it, have been attributed commonly to Fyodor Dostoevsky, to Mahatma Ghandi, and Harry Truman.
We should remember those wise words, and act on them as best we can.
If we can foster some more humanity toward our fellow citizens, we might just come out the other side of this in a more perfect union. If we can resist the urge to call people names, even when they do things like stick hair dryers up their noses or go to the grocery store without masks, we can begin the process of turning down the cruelty and viciousness and ignorance and extremism. There are plenty of other things to do. Donate to your local food bank. Send a kind letter to an old friend from the other side of the aisle.
We can’t swing a sledgehammer to eliminate the cruelty. We have to radiate kindness.
What are you doing every day to uplift people?
Now, on to the rest of the week in biotech.
The Big Data Readout
The NIH reported results from a randomized study of 1,063 hospitalized patients with COVID19 who got Gilead Sciences’ antiviral drug remdesivir or a placebo. The median time to recovery from illness was 11 days for patients on the drug, and 15 days on the placebo – a 31 percent improvement, which was statistically significant. The drug didn’t show a statistically significant benefit on survival rates, although there was a slight trend in the right direction. Tony Fauci, director of the National Institute of Allergy and Infectious Diseases, called it “quite good news” and the kind of data that will create a new standard of care.
Gilead Sciences separately reported that another study showed that a 5-day course of treatment was about as good as a 10-day course of treatment. That’s meaningful because it means Gilead will be able to treat more patients with whatever supplies it can manufacture.
Testing
Vaccines
Science Features/Commentary
Science
Epidemiology
Investigations
Policy
Communication
Worth a Listen
Non-Covid Science
Feasibility of Blood Testing, Combined with PET-CT, to Screen for Cancer and Guide Early Intervention. Science. Apr. 28. (Bert Vogelstein et al)
Data That Mattered
Regeneron and Sanofi reported a not-so-encouraging update on the IL-6 inhibitor, sarilumab (Kevzara). A Data Safety Monitoring Committee recommended a halt to enrollment in an ongoing Phase III of COVID-19 patients with “severe” disease, but recommended continuing enrollment of the cohort with “critical” disease. The companies will also quit giving the low dose, and give everyone the higher dose.
Regeneron and Sanofi had better news from a trial of their PD-1 inhibitor cemiplimab (Libtayo). The drug reduced the risk of death by 32.4 percent in a study, compared with chemotherapy, when evaluated in patients getting their first round of therapy for locally advanced or metastatic non-small cell lung cancer, and with greater than 50 percent of their tumor cells positive for the PD-L1 protein. The finding was so strikingly positive that a Data Safety Monitoring Committee recommended the study be halted early so all patients could get the drug. The companies said they will take the data to US and EU regulators in 2020.
Roche reported that orally administered liquid risdiplam, a survival motor neuron-2 (SMN2) splicing modifier, passed a Phase II clinical trial for infants ages 1 to 7 months with Type 1 spinal muscular atrophy. Researchers reported a significant increase in motor function after 12 months of therapy. If approved by regulators, it would be an alternative to Novartis’ Zolgensma gene therapy, and Biogen’s Spinraza. For this product, Roche leads clinical development, in collaboration with the SMA Foundation and PTC Therapeutics.
Financings
Cambridge, Mass.-based Rome Therapeutics raised $50 million in a Series A financing from GV, Arch Venture Partners and Partners Innovation Fund. The plan is to make drugs for cancer and autoimmunity based on knowledge of repeat sequences of DNA, aka “the repeatome.”
San Diego-based Erasca Therapeutics, a targeted cancer drug developer, raised $200 million in a Series B financing. Arch Venture Partners and Cormorant Asset Management co-led. Jonathan Lim, former CEO of Halozyme and Ignyta, is the co-founder and CEO.
Shanghai-based Mabwell Biotech raised $280 million in a Series A financing. It’s reportedly a rollup of nine R&D and production companies in China.
Oakland, Calif.-based Dascena, a machine learning for diagnostics company, said it raised $50 million in a Series B led by Frazier Healthcare Partners. The company also announced a publication in the BMJ of an algorithm it made to help doctors treat severe sepsis.
Seattle-based Avalyn Pharma raised $35.5 million in a Series B to continue work on pulmonary fibrosis and chronic lung allograft dysfunction. Norwest Venture Partners led. Bruce Montgomery is CEO.
Dallas-based Taysha Gene Therapies raised $30 million in a seed financing co-led by PBM Capital and a fund led by former AveXis CEO Sean Nolan. The company said it’s working on 15 AAV gene therapy programs.
Personnel File
Nathanael Gray and Priscilla Yang, star chemical biologists, are moving from the Harvard/Longwood Medical universe to Stanford University. See the fist pump below from Stanford’s Carolyn Bertozzi. (See was a guest on The Long Run in 2019).
Sue Desmond-Hellmann joined GV as an advisor. She’s the former CEO of the Bill & Melinda Gates Foundation, chancellor at UCSF, and president of product development at Genentech. See the fist pump below from GV partner David Schenkein, who worked with Sue at Genentech.
New York-based Health Reveal, a clinical AI company, hired Julie Stern as chief technology officer.
Waltham, Mass.-based Xilio Therapeutics, a cancer immunotherapy company, hired Martin Huber as chief medical officer.
Rosana Kapeller was named CEO of Cambridge, Mass.-based Rome Therapeutics (see above). She’s the former chief scientific officer of Nimbus Therapeutics.
Deals
Vertex Pharmaceuticals struck a research collaboration with Waltham, Mass.-based Affinia Therapeutics to work on novel adeno-associated virus (AAV) capsids for gene therapy. Initial focus will be on Duchenne muscular dystrophy, myotonic dystrophy type 1 and cystic fibrosis. Affinia will get up to $80 million in upfront and milestone payments during the research term.
Just Evotec, a leading biologics manufacturer, agreed to work with Ology Bioservices on antibodies for coronavirus. Ology is supported by a defense contract, and is tapping Just as a subcontractor. Terms weren’t disclosed. (See Just Evotec EVP Jim Thomas, on scaling antibodies and vaccines for COVID-19, in this Apr. 16 editorial on TR).
UK-based AstraZeneca and the University of Oxford, also in the UK, announced plans to collaborate on a recombinant vaccine candidate for SARS-CoV-2. Academics bring the discovery work, while industry brings development, manufacturing and distribution capabilities to the table. The first Phase I trial started last week. Terms weren’t disclosed.
Catalent, a contract drug and biologics manufacturer, agreed to work with Johnson & Johnson on manufacturing scale up for the company’s lead COVID19 vaccine candidate. Catalent said it will hire 300 workers to do the job.
Regulatory Action
San Diego-based Neurocrine Biosciences won FDA clearance to market opicapone (Ongentys) as a once-daily oral pill in addition to levodopa/carbidopa in patients with Parkinson’s disease experiencing “off” episodes.
GSK secured the FDA green light to start marketing its PARP inhibitor niraparib (Zejula) as monotherapy maintenance treatment for women with advanced epithelial ovarian, fallopian tube, or primary peritoneal cancer who are in a complete or partial response to first-line platinum-based chemotherapy, regardless of biomarker status. This is one of those anticipated label expansions that GSK anticipated would make its acquisition of Tesaro pay off.
Today’s guest on The Long Run is Emma Hodcroft.
Emma Hodcroft, molecular epidemiologist, University of Basel; co-developer, NextStrain.
Photo: Oliver Hochstrasser / www.oliverhochstrasser.ch
Emma is a molecular epidemiologist at the University of Basel, and the co-developer of Nextstrain.
NextStrain is the open-source toolkit built for real-time tracking of viral outbreaks. In the early days, teams led by Trevor Bedford at Fred Hutch and Richard Neher in Basel used it to track viral evolution of Ebola and Zika. Over time, the resource has been adapted to study flu, and now – of course — SARS-CoV-2.
Lots of questions remain about this virus. It’s brand new to science. But a fair bit of what we do know from the early days can be attributed to Nextstrain.
This resource provides real-time information on where community transmission of the virus is occurring, where certain variations are coming from, the estimated size and scope of the outbreak, and more.
It’s a treasure trove. The whole world is watching.
In this episode, Emma provides clear, simple explanations of the basics of viral family trees, what we can learn from them, and what kinds of things we hope to learn later this year.
The Long Run is sponsored by RareCyte.
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Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
