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Peyton Greenside is today’s guest on The Long Run.
Peyton Greenside, co-founder and CEO, BigHat Biosciences
Peyton is the co-founder and CEO of San Mateo, Calif.-based BigHat Biosciences. The company was started in 2019 to build on advances in synthetic biology and machine learning to design antibody drugs with a variety of different properties, faster.
The company has gone on to raise more than $100 million in venture capital and struck partnerships with a handful of large pharma companies, including AbbVie, Johnson & Johnson, Amgen, Merck, and most recently Eli Lilly.
BigHat’s drug candidates are all in preclinical development. Its focus is on cancer and inflammatory and immune disorders. Like anything else in biotech, the proof of the value of the technology platform will be determined by results from these medicines in clinical trials.
Now, please join me and Peyton Greenside on The Long Run.
David Shaywitz
Consumer health and wellness is experiencing a flurry of activity.
The lab testing company Function (motto: “It’s time to own your health”) acquired Ezra, a whole body MRI company promising “the world’s most advanced longevity scan.”
Oura, maker of the popular smart ring, recently added an integration for continuous glucose measurement as well as the ability to calculate meal nutrition based on a photo. Oura also hired Dr. Ricky Bloomfield as its first Chief Medical Officer; Dr. Bloomfield had previously served as Clinical and Health Informatics Lead at Apple, and is known for his expertise in health data interoperability.
Meanwhile, Oura competitor Whoop, maker of a smart band, just announced the latest versions of its device, with the ability to monitor blood pressure, ECG, and to assess what it describes as a measure of biological age, which it calls “Whoop Age.” Whoop now says it seeks to “unlock human performance and healthspan,” enticing users with the pitch, “Get a complete picture of your health.”
Notice a pattern yet?
What unites these approaches and so many others, as the industry newsletter Fitt Insider (FI) recently observed, is they reflect an attempt to generate a “personal health OS,” intended to “give individuals agency over their well-being,” and more generally, wrest control back from a health system that’s often perceived (especially by young adults) as somewhere between useless and obstructive.
Citing a recent Edelman survey, FI reports,
…nearly half of young adults believe well-informed people can be as knowledgeable as doctors, two-thirds see lived experience as expertise, and 61% view institutions as barriers to care.
Fed up with reactive care, many already collect data across wearables, lifestyle apps, DTC diagnostics, and more, but most are siloed. Rolling up, Function is architecting a unified platform capable of generating clinically relevant insights from raw inputs.
FI points to the proliferation of companies like Bright OS, Gyroscope, and Guava Health focused on “day-to-day data management,” as well as startups like Superpower (“Delivering concierge-level metrics minus the PCP”) and Mito Health (a “pocket-sized AI doctor” that “generates comprehensive digital health profiles by merging labs, medical records, family history, lifestyle info, and more.”)
AI seems poised to play an increasingly central role in many of these companies.
FI speculates,
A step further, end-to-end LLMs could close the loop, linking cause and effect, turning insights into actions, syncing with PCPs, and laying the foundation for an AI-powered medical future.
This is a good time to take a deep breath – as well as a closer, more critical look at this vision of consumer-empowered, data-fortified health.
Unquestionably, there’s a lot to embrace here, including in particular:
A tech-enabled approach to health where you have more abundant data about you, that are explicitly in your control, and which could lead to healthier behaviors represents the sort of progress that deserves to be celebrated.
At the same time, when I look at many of these approaches to health, I see two broad categories of concerns.
The first, perhaps more concrete worry, is that, to paraphrase comedian Dennis Miller, “two of [crap] is [crap],” and simply the collection of a lot of data, much of which may be fragile, isn’t sure to translate into brilliant insight, even if the magical power of AI is fervently invoked.
In an especially incisive “Ground Truths” blog post focused on “The business of promoting longevity and healthspan,” Dr. Eric Topol writes that “getting hundreds of biomarker results and imaging tests in an individual greatly increases the likelihood of false-positive results,” a concerning possibility.
I’ve discussed the challenge of false positives here, and get into some of the details around Bayes Theorem (which informs the assessment) here. The OG reference in this space may be this 2006 paper by Zak Kohane and colleagues, in which they introduce the term “incidentalome.”
To be fair, at least some of the proponents of extensive testing recognize the challenge of false positives but feel that the opportunity to collect dense data on individuals over time enables important inflections to be observed, a point Dr. Peter Attia explicitly emphasizes in Outlive; I discuss his “risk-management” mindset here.
Similarly, Nathan Price, a professor at the Buck Institute and the CSO of Thorne, has argued that close inspection (assisted by AI) of rich individual data could identify (for example) opportunities for supplement intervention. These interventions may not make much of a difference on the population level (hence the paucity of persuasive clinical trial data for supplements, as Dr. Topol notes in his latest book, Super Agers – my WSJ review here), but could in selected individuals. (I also discuss Price here, here).
Proponents of the “personal health OS” also might emphasize the presence of tailwinds – the likelihood of improved predictions as measurement technologies continue to get better, denser data become available, and the AI tools become ever-more capable. Perhaps we’re not quite at the point of realizing the future we imagine, advocates might argue, but we’re close enough to start to see what it might look like.
What’s arguably a deeper concern about the model of health we seem to be moving towards is the degree to which it seems to be informed by a rigidly reductive mindset. In this limited, classically managerial (or consultant) view, health becomes simply metrics on a dashboard, an ever-expanding series of parameters that must constantly be measured, quantified, optimized.
A recent, beautiful essay about our evolving understanding of and approach to happiness in the New York Times Magazine by Kwame Anthony Appiah reminds us what we may be missing.
Around the start of the new Millenium, Appiah writes, we entered
the life-hacking, self-quantifying, habit-stacking era of optimization gurus like Tim Ferriss, whose first book, published in 2007, was “The 4-Hour Workweek” — “a toolkit,” in his words, “for maximizing per-hour output.”
Consequently, Appiah continues, the concept of flourishing was decomposed into “modular upgrades” as we refine our “personal operating system.”
Yet it’s essential to recognize, Appiah writes, that “happiness is not an optimization problem,” but something deeper and more substantial.
I reached for a similar point in 2018, in a piece entitled, “We Are Not a Dashboard.”
Observing that the “dashboard has become a potent symbol of our age,” I wrote that “the ideology of big data has taken on a life of its own, assuming a sense of both inevitability and self-justification.”
I continued, “From measurement in service of people, we increasingly seem to be measuring in service of data, setting up systems and organizations where constant measurement often appears to be an end in itself.”
I’m reminded of a favorite phrase from Kate Crawford’s Atlas of AI (my WSJ review here): “The affordances of the tools become the horizon of truth,” a reminder, in this context, that even if we’re awash in tools enabling the measurement and analysis of health data, we must ensure our understanding of health transcends the limits of these tools.
Of course, the point isn’t to go the other way, and reject metrics completely.
As Professor Jerry Muller, author of the brilliant book Tyranny of Metrics, explains, “I can’t see how competent experts could ignore metrics. The question is their ability to evaluate the significance of the metrics, and to recognize the role of the unmeasured.” (emphasis added).
I also spoke to this need in a 2011 piece entitled “What Silicon Valley Doesn’t Understand About Medicine,” writing, ”a novel technology platform that overlooks the integrated needs of patients or underestimates or fails to account for the complexity and messiness of illness as it actually occurs and is experienced by patients (and those closest to them) will inevitably fall short.”
To most effectively meet the needs of patients – including the vitally important goal of preventing or preempting disease so people don’t become patients – it’s essential to embrace the power and promise of emerging technologies, including those enabling the conceptualization of “personal health OS,” while not mistaking this map for the territory (as Alfred Korzybski famously instructed).
It will be essential to establish priorities – in partnership with each patient – and identify a handful of key health parameters on which to focus on; Drs. David Blumenthal and J. Michael McGinnis discuss the topic of “core metrics” thoughtfully in this 2015 JAMA “Viewpoint.”
At the same time, we must hold fast to a vision of health and wellness that expands far beyond the confinement of a dashboard and aspires to something beyond the recursive optimization of metrics (as I recently discussed here). Our approach must be capacious enough to include, authentically value, and meaningfully cultivate other components of a healthy, flourishing life, which might include intellectual captivation, the pursuit of purpose, and social engagement with family, friends, and community.
(Martin Seligman’s PERMA model — positive emotion/joy, engagement/flow, relationships/connection with others, meaning/purpose, and accomplishment — represents a potentially useful framework [see here, here] for expanding our thinking.)
Despite the difficulty, if not utter impossibility, of reducing some of the most important and profound components of health to an easily digested number, we must continue to value and pursue them.
Even as we diligently leverage emerging technology to construct and refine health dashboards, let’s resolve to work towards a more expansive, durable, and meaningful vision of health that exists beyond the sterile syntax of rows, columns, and digits.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $199 per year, you reward quality independent biotech reporting, and encourage more.
David Shaywitz
For at least a decade, nearly every tech company has promoted their product as facilitating the “democratization” of something – perhaps “data driven medicine,” or “genetic information” or “access to clinical trials” or “digital health” (all real examples).
Like “mission-driven,” “results-oriented,” and “disruptive,” the term “democratization” has become so overused by the tech community that it’s now more of an obligatory buzzword than a meaningful, resonant concept.
However, just when we may have been inclined to tune out, two prominent recent examples remind us of the extraordinary power of technology to empower individuals and drive bottom-up change – hopefully (but not inevitably) for the better.
While experts fretted about the accuracy of the medical information that might be proffered by genAI chatbots like ChatGPT, patients (as journalist and author Carey Goldberg presciently observed) had another thought: “Just give me access!”
As Goldberg wrote in The AI Revolution: ChatGPT-4 and Beyond, anticipating the initial release of an advanced ChatGPT model,
health-related web searches are second only to porn searches, by some counts. Surveys find roughly three-quarters of American adults look for health information online. It’s not hard to predict a massive migration from WebMD and old-style search to new large language models that let patients have a back-and forth for as long as they want with an AI that can analyze personal medical information and seems almost medically omniscient.
This was a savvy observation, applying not only to medicine but also to many other domains, where chatbots like ChatGPT are increasingly an essential source of critical information.
For instance, when I was struggling recently with a connectivity issue involving my exercise bike, the company’s tech support was less than helpful, and painfully slow. Yet ChatGPT provided immediate, insightful suggestions and ultimately an effective solution.
Similarly, when Dr. Benjamin Davis encountered difficulty with a kitchen appliance (an ice machine), he described the problem to ChatGPT. According to Davis, the chatbot “told me what to buy (some sort of thingy). How to fix. Boom I’m a refrigerator tech and we have ice.”
The rapid adoption of tech that’s both useful and ubiquitous, like AI, echoes our recent experience with the phone camera. When it was initially introduced, experts ridiculed the the camera’s (admittedly poor) quality, and confidently predicted it would never replace traditional photography. Yet, the extraordinary convenience of the techology, and its rapidly improving quality over time, resulted in the wholescale disruption of the photography industry, and turned everyone with a mobile phone (which is to say, essentially everyone) into a photographer and potential journalist.
One question, of course, is how this will change the practice of medicine; many doctors were irritated when patients started showing with information from “Dr. Google.” Now, patients can arrive with a far greater level of knowledge and specificity about what’s ailing them. Sure, this may be off base (especially if user prompts have led the AI down a rabbit hole infused with misinformation), but chances are that it’s reasonably well informed, in some cases (many cases?) perhaps even more informed that the treating physician.
Traditionally, the expertise and authority of physicians was based on their exceptional knowledge (as well as, of course, deep experience, and hopefully interpersonal skills supporting a beneficial therapeutic relationship). It’s difficult not to see physician authority challenged by the emergence of savvy AI, particularly as digitally native patients increasingly rely upon it.
But it’s not just physicians whose lives are likely to be changed by ever more sophisticated AI chatbots. Many individuals are finding themselves drawn into extended conversations and interactions with chatbots – exactly as both Harvard’s Zak Kohane and even more so, Microsoft’s Peter Lee both described in The AI Revolution.
The chatbots, for their part, have deliberately encouraged this, not least by a mode of engagement that can be so solicitous that ChatGPT recently had to dial it back, and essentially issue an apology for the degree of “sycophancy.”
It’s fascinating to contemplate that in the not too distant future, we may reflect back fondly, and wistfully to the time we were all immersed in texting and social media, rather than individually absorbed in chats with exceptionally attentive AIs.
But (to borrow Commentary Executive Editor Abe Greenwald’s already iconic phrase), it’s worse than that.
Some companies, including Meta, are taking digital companionship to the next level, developing chatbots that Mark Zuckerberg believes will be “the future of social media,” according to a recent Wall Street Journal article, and which have been endowed with “the capacity for fantasy sex.” (Because TR is a family publication, I’ve omitted disturbing details included in the Journal article.)
To avoid this dystopian future, Kohane says we’ll need “align AI to make us want more interactions with fellow humans.” He acknowledges that it’s “all too easy to align [AI’s] with atomized, consumerized society,” a phenomenon he describes as “inceleration” (a portmanteau of “incel” and “acceleration”), and which traces its intellectual origins, he notes, to Asimov’s The Naked Sun.
Today’s Wall Street Journal features a fascinating example of a bottom-up approach driving meaningful change. The story, by Jesse Newman, describes how the remarkable popular adoption of the “healthy food” evaluation app, Yuka, is apparently driving change from food companies, a degree of responsiveness (or at least awareness) that had previously seemed elusive.
Yuka, Newman writes, enables users to scan the bar codes of food items, and reports back “a score from one to 100 based on nutritional quality, additives and whether it is organic.”
Health and Human Services Secretary Robert F. Kennedy Jr., Newman reports, is a fan of the app, saying that both he and his wife use it.
Large food companies like Conagra have taken notice:
Conagra Chief Executive Sean Connolly said that no one app is the authority over nutrition. “There are a lot of opinions out there,” he said, adding that the opinions that matter most to Conagra are those of its consumers.
But Conagra’s consumers use Yuka, too. Thousands have complained about additives found in the company’s products, using a feature on the app that enables shoppers to shoot off a predrafted message via email or social media asking food makers to remove additives.
Startups and smaller companies have been impacted directly as well:
Jack McNamara, CEO of seltzer maker Tru, said he first learned about Yuka while handing out samples at a Los Angeles Costco. Shoppers began pulling out their phones and scanning Tru’s bar code.
Yuka gives Tru drinks a score of 43 or 48 out of 100—“poor”—in part because they contain stevia and erythritol, sweeteners that Yuka says carry risks. McNamara said he doesn’t fully agree with Yuka’s methodology, which deducts points for drinks that aren’t water, but he takes the app’s input seriously.
“Platforms like [Yuka] are going to have massive repercussions,” McNamara said.
Tru, which he said rates better than many competitors, is trialing new versions of its drinks that would fetch higher scores, using less or none of the sweeteners.
The power of apps like Yuka – like so many other technologies– is a double-edged sword, positive to the extent its evaluation scheme aligns with your own priorities, but worrisome to the extent it might drive substantial change based on popular vibes (demonization of non-organic food, say) rather than rigorous scientific evidence.
David Shaywitz
A recent piece by Nathan Price captures our collective hope for AI in health with unusual clarity, even as there remains impassioned disagreement regarding how close these ambitions are to meaningful realization.
For context, Price is Professor and Co-Director of the Center for Human Healthspan at the Buck Institute for Research on Aging and CSO of Thorne, a company best known for its supplements, and which is now expanding into testing. He’s also the co-author, with Lee Hood, of the 2023 book, Age of Scientific Wellness.
Writing in MedCityNews, Price argues that AI represents a key enabler of “precision wellness.”
AI now makes true biological personalization possible by analyzing an individual’s unique genetic variants, microbiome composition, and blood markers to create lifestyle and nutrition recommendations that traditional one-size-fits-all approaches cannot match. Where conventional wisdom offers standardized solutions, your biology demands precision….
The complexity of the vast number of biological interactions creates a virtually impossible puzzle for individuals to track independently. This is precisely where AI excels — processing vast amounts of personalized data to identify which natural product combinations could work with your unique biological system.
AI enables personalization at scale, delivering both cost-effectiveness and depth of analysis….
The result transforms overwhelming complexity into simple, actionable recommendations tailored to your body’s specific needs, limitations, and opportunities.
These three conceptualizations of AI – its promise as a (1) critical complexity-management tool; (2) vital integrator of ever-larger datasets available through improved measurements techniques including digital/wearables; and (3) personalization machine — are manifesting as key themes across many health domains.
Besides wellness, recent examples include:
Nutrition: “Precision nutrition for cardiometabolic disease,” by Guasch-Ferre et al, in a recent issue of Nature Medicine.
Geromedicine: “From geroscience to precision geromedicine: Understanding and managing aging,” by Kroemer et al, in a recent issue of Cell.
Clinical Development in Biopharma: “AI: An essential tool for managing the burgeoning complexity of clinical development in pharmaceutical R&D,” which Pfizer’s Subha Madhavan and I published in Drug Discovery Today.
As Madhavan and I write,
Profound advances in biomedical science have created abundant opportunities for drug developers, who are now privileged with the responsibility of sifting through an ever-increasing number of therapeutic targets, treatment modalities, and measurement techniques in effort to deliver transformative medicines to patients. Digital technologies, particularly AI, represent a promising approach to managing the burgeoning complexity of clinical development.
There are remarkably similar themes articulated in each of these papers – namely that today, we tend to make consequential decisions in each of these domains based on heuristics, instinct, and our ability to process some fraction of the available data (which represents a tiny fraction of the theoretically obtainable data). The expectation is that we could make better decisions if we could responsibly access and thoughtfully analyze a far greater volume of every type of data, ideally collected longitudinally. The hope is that AI can profoundly enable this analysis and perhaps is already starting to do so.
Many tech optimists believe success in health is inevitable, and even on our doorstep. Deep Mind CEO Demis Hassabis recently told reporter Scott Pelley on 60 Minutes that the end of disease may be “within reach. Maybe within the next decade or so, I don’t see why not.”
In contrast, biopharma veterans tend to be more skeptical. This comes through in chemist and blogger Derek Lowe’s thoughtful response to the Hassabis interview. Our knowledge of biology’s interlocking systems is “completely inadequate to cure disease within ten years,” he writes. “And unfortunately, it’s going to be inadequate at the end of that ten years, too – I will put that marker down, although it doesn’t make me happy to do it.”
Lowe continues,
That’s because we don’t have enough pieces on the table to solve this puzzle. We don’t even have enough in most of these areas to know quite what kind of puzzle we’re even working on. Nowhere near. And AI/ML can be really, really good at rearranging the pieces we do have, in the limited little areas where we have some ground-truth knowledge about the real-world effects when you do that. But it will not just start filling in all those blank spots. That’s up to us humans. My most optimistic take on these technologies is that if things go really, really well they might be able to help guide us towards more productive research than we might otherwise have been doing, but we are going to have a lot of data to gather, a lot of answers to run down, and a lot of twists and turns and utter surprises to deal with along the way. We’re going to need a terrifying amount of new knowledge before we can actually turn to any AI/ML systems and ask them the kinds of big questions I mention above.
The dimension of the challenges we’re wistfully hoping AI can somehow solve is perhaps most easily appreciated in the domain of wellness, with its goal of staying healthy and preempting illness.
On the one hand, we all recognize the limitations of the familiar heuristics – eat healthily, exercise, engage with others. These can feel superficial and non-specific, the guidance not particularly customized.
Yet if you decide to make the relentless optimization of health your personal “objective function,” with every life choice adjudicated based on whether it’s likely to maximally enhance your health, you can easily lose your mind as you disappear down the rabbit hole of endless ramifications and never-ending tradeoffs.
In this context, the appeal of an algorithm that can effortlessly manage this optimization for you, personalizing and prioritizing your endless choices in an evidence-driven fashion seems enormously attractive. If only data existed to enable such assessments; at the moment, like Lowe, I’m skeptical.
Realistically, in all of the health domains we’ve discussed, the critical question isn’t so much whether we will “cure all disease” (or not), or “optimize personal wellness” (or not), but rather what are the “pockets of reducibility” (to borrow Stephen Wolfram’s term). Where will we have the requisite data – and, as Andreas Bender has discussed, a problem posed with suitable constraints — to fully leverage the power and promise of AI to move the needle in a domain of health.
Legendary Harvard physician-anthropologist Arthur Kleinman, who delivered his Last Lecture at Harvard this past week, introduced the concept of the “explanatory model” in medicine.
As I described it a few years back, the “basic idea is that different people have different views of illness and disease, and the physician or healer needs to understand and acknowledge the patient’s model to optimize the therapeutic relationship.”
At the time, I was writing about how legendary geneticist Francis Collins was famously motivated to change his diet and exercise routine after a genetic test reportedly suggested he might be at increased risk for diabetes.
This seemed striking to me, because, as I noted,
from a medical perspective, the logic is lacking, or at least soft; most people would presumably benefit from a healthier lifestyle, whether genetic testing reveals a particular predisposition or not. Collins, a physician-scientist, shouldn’t have needed genetic testing to motivate lifestyle changes. Yet apparently, it took genetic testing because that deeply resonated with his explanatory model of illness.
The notion of explanatory models applies to our discussion of AI in health in at least two ways.
First, in the same way that Collins was motivated to adopt healthier behavior on the basis of genetic data, I can easily imagine others who might be similarly motivated because an algorithm supposedly powered by a superintelligence spits out a very specific, ostensibly precisely customized lifestyle plan.
The second application of explanatory models to AI may apply not to patients but to investors. Many tech investors are convinced that biology is poised to be disrupted by technology and technologists.
Consider these comments from noted investor (and contrarian) Peter Thiel, in the context of a 2019 interview:
Biology, I continue to think we could be doing a lot more, we could be making a lot more progress. And you know, the pessimistic version is that no, biology is just, is much harder than physics, and therefore it’s been slower going.
The more optimistic one is that the culture is just broken. We’ve had very talented people go into physics. You go into biology if you’re less talented. You can sort of think of it in Darwinian terms. You can think of biology as a selection for people with bad math genes. You know, if you’re good at math, go to math, or physics, or at least chemistry, and biology we sort of selected for all of these people who are somewhat less talented. So, that might be a cultural explanation for why it’s been been slower progress.
In other words, biology, and biomedical research has apparently been slowed by the comparatively inferior minds who’ve been attracted to it, versus the prodigies drawn to more quantitative disciplines.
The corresponding hope among many tech investors is that with the arrival of quants and their technology, including in particular AI, biomedical science can be rescued from the plodders.
Not surprisingly, many companies promoting revolutionary AI solutions to biopharma R&D have raised significant capital, especially impressive — not to mention useful — in this otherwise dour biotech market.
Recently, I saw a representative deck from one of these companies; what was striking was how the entire process of drug development had been completely reframed in a way that seemed likely to align perfectly with a tech-first view of the world.
This marketing strategy was apparently successful, since the company in question has raised considerable capital.
Yet, when I cut through all the jargon, what I saw was essentially a tried-and-true strategy – in-license, develop through value inflection, sell. Sure, maybe AI is improving this process somehow, but my suspicion is that the main function of AI in this company is serving as an attractant for a huge amount of money, which talented and seasoned drug developers (including a very experienced drug picker) can then serially deploy, with multiple shots on goal.
It’s arguably similar (as I’ve described here) to Millenium Pharmaceutical’s experience of raising lots of money through the promise of genetics and molecular profiling, and then succeeding largely on the strength of using this money to acquire LeukoSite, including (unbeknownst to them at the time of the transaction) the compound that would ultimately become the blockbuster Velcade.
In short: the idea of cleverly applying AI to pharma R&D resonates with many deep-pocketed tech investors, articulating in effect their own “explanatory model” of where the next big breakthrough may come from. Savvy biotech startups have leveraged their understanding of this investor mindset to raise significant capital and pursue what (sans AI) might be considered reasonable if fairly prosaic approaches – only now with considerable resources to put behind these efforts.
I’ve previously highlighted the Acquired podcast (what “the smartest people in the world are all listening to,” according to a 2024 Wall Street Journal “Science of Success” column by the wonderful Ben Cohen) in the context of GLP-1 and an episode they did on Novo Nordisk.
Now, the Acquired team applies their exceptional talents to unpack the story of Epic, the electronic medical records behemoth physicians love to hate (my own contributions to this dialog here, here, both co-authored with Tory Wolff of Recon Strategy). I remembered how surprised I was in 2018 when the New York Times published an adoring account of the company, and thinking, “gosh, were they taken in.”
Yet it turns out the Times may have been prescient. The Acquired episode on Epic – focusing in particular on founder and CEO Judy Faulkner as a (phenomenally successful) tech entrepreneur – was even more effusive. While the dissatisfaction among providers was noted in passing, the clear emphasis was on how brilliantly and relentlessly the company delivers for its customers.
As the hosts explicitly emphasize, Epic’s customers are manifestly not the providers whose souls (some have said) are drained by Epic, but rather by the top executives — specifically the CEO, CIO, and CFO — of academic medical centers and other healthcare companies who choose to deploy Epic.
The episode – inspiring at times, maddening at others – is nevertheless an essential listen.
Luke Timmerman, founder & editor, Timmerman Report
We did it together.
The Timmerman Traverse for Damon Runyon Cancer Research Foundation completed a splendid expedition to Everest Base Camp on Apr. 23, 2025.
This trip succeeded on every count.
All 17 members of the team made it to the mountaineering camp at 17,600 feet / 5,364 meters.
We exceeded our $700,000 fundraising goal for high-risk / high-reward cancer research with $734,508 as of May 2. More gifts are in the pipeline, so our final tally should eclipse $800,000.
The experience was magnificent from beginning to end.
The views of the Himalayas were awe-inspiring, up close and far away.
The physical and emotional challenge was no small thing. We covered a little more than 40 miles over rugged, uneven, uphill and downhill terrain. When individuals struggled with altitude symptoms, our group rallied in support with anything that mattered in the moment — a sip of water or a hug.
The camaraderie was delightful. There’s something innately human about getting outside, with a group, with a shared goal, and pushing ourselves hard mentally and physically. We relaxed after these efforts by telling stories, playing cards, cracking jokes.
We shared the simple joys. A cup of ginger lemon tea. A handmade souvenir. A hot shower at 14,000 feet. The nourishing slurp of warm garlic soup.
We paid attention, and gave respect, to our wonderful Nepalese hosts.
The bonds formed were strong. At the end of an immersive experience like this, these are the people who will show up at your wedding or your memorial service.
Please enjoy a few photos from this transcendent experience.
Thanks to the 2025 Timmerman Traverse for Damon Runyon team.
Special thanks to lead guide Eric Murphy of Murphy Expeditions and our Nepalese support team led by Jiban Ghimire of Shangri-La Nepal Trek.
(Guest) Editor Note: Martin Gaynor, the Lester A. Hamburg University Professor of Economics and Public Policy at Carnegie Mellon University, was recently honored with the Victor R. Fuchs Award for Lifetime Contributions to the Field of Health Economics by the American Society of Health Economists. His response (shared with his permission) was both striking and magnificent, emphasizing the contingency of his career path, and acknowledging the many different ways things might have turned out. I’ve previously discussed in TR both contingency and success narratives (see also here), and I am delighted to share Professor Gaynor’s perspective with TR readers. – David Shaywitz
Martin Gaynor, Lester A. Hamburg University Professor of Economics and Public Policy at Carnegie Mellon University
Obviously, I’m very pleased at this recognition, but I’m sharing this for other reasons.
First, many have the impression that people who have been successful professionally have walked a straight path – got the right degree, right first job, succeeded right away…. That’s true of some, but many have traveled a far more circuitous route – that’s certainly true of me.
I left grad school in 1981 with my dissertation unfinished, and held 5 jobs in the next 7 years, including getting fired from one for not having my dissertation done. After 5 years I was out of academia, with only one publication in a minor scientific journal.
It took me a long time to mature as a researcher and to figure things out professionally. I got some lucky breaks and was fortunate to connect with smart, supportive people in the places I was and things eventually came together.
The point is that not everyone is successful right away, and some people get off to a slow start, but that doesn’t determine eventual professional achievement.
Second, there are a lot of ways to have a successful professional career. I’ve greatly enjoyed academia, but I could have been very happy and fulfilled working in government or for a research or consulting firm. I’ve worked in those settings and there are really smart, dedicated people doing important work there that makes a difference in real time (unlike most of what is done in academia).
When I was finishing grad school and going on the job market what I really wanted was a job at the Rand Corporation in Santa Monica. They had folks doing awesome research and people played volleyball on the beach at lunch (I think the latter may have been most of the source of my interest). If I’d gotten a job offer from them I might still be there, and be very happy about it.
Third, the most important achievements any of us will have are our relationships with other people. Family, friends, community – those relationships are more meaningful and have much longer lasting impacts than what we do professionally.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $199 per year, you reward quality independent biotech reporting, and encourage more.
David Shaywitz
Can you improve your health without obsessing about it?
I’ve been, well, obsessing about this question as I continue to spend more time and mindshare in the world of healthy aging evangelists, enthusiasts, and entrepreneurs, longevity champions keen to guide you, and often test you, towards their conceptions of healthier aging.
(See this piece on the longevity boom, and this on the role of GLP-1RAs.)
There seem to be two general flavors of longevity champions.
First are those who were always athletes, and who have long been interested in improving performance. Examples here include Australian Pete Hull, founder of the rapidly growing fitness chain Fitstop (interesting podcast interview here) and Will Ahmed, founder of Whoop, a wearable company. Hull was a competitive Motocross rider and later a personal trainer before he found his way to entrepreneurship; his gym focuses on “performance-based functional fitness.” Ahmed was a squash phenom at Harvard, and developed Whoop based on an interest in “understanding his body better.” The company’s tagline is “Power your performance with 24/7 data.”
But not all champions were passionate about health and longevity from a young age; some arrive at this epiphany after a personal revelation. Examples here include champions like Nick Norwitz and Dr. Peter Attia. Norwitz writes that his interest in metabolism derived from his struggles with severe inflammatory bowel disease; his successful management of this condition with a ketogenic diet after conventional approaches failed sparked his curiosity about nutrition and metabolism.
Attia, while apparently always athletic, traces his epiphany to a specific date — September 8, 2009, as he describes in Outlive – on which he recognized (spurred, he writes, by a comment from his wife) that he had become “not thin Peter,” and metabolically unhealthy. Consequently, he, also, “quickly became obsessed with understanding nutrition and metabolism.”
Attia’s obsession (which seems unquestionably the correct term here) is readily apparent from his book, as he describes the many components of healthy eating, movement, breathing, and sleeping. Each topic (like movement) ramifies into subtopics (cardiovascular, strength, balance), each with their own subtopics (VO2 max, Zone 2 exercise, lactate threshold, etc). His podcasts can get into even more granular detail, such as this discussion with researcher and Olympic cycling coach Inigo San-Millan about the intricacies of Zone 2.
This approach to longevity – focused on measurement and optimization of multiple parameters in effort to improve “performance” in many individual areas, and ultimately overall, obviously has a familiar ring to it. Ask the CEOs of Fortune 500 companies how they operationally drive improvements, and they’ll likely tell you something similar, explaining how they deconstruct a corporate mission into constituent activities, set relevant goals, measure performance and evaluate progress.
While this approach may help improve the bottom line of established corporations and help good athletes become great, I’m less sure this approach is actually likely to help the people who have the most to gain: those who are not at particularly focused on wellness, for whom the greatest challenge is getting started.
(In a similar way, perhaps, it’s generally unhelpful for a startup to fixate on operational efficiencies while it’s still searching for product-market fit.)
But even for those who are already interested in wellness, the amount of information on offer from longevity gurus is utterly overwhelming.
To pick a (real) example, a longevity champion might discuss the health benefits of saunas on one day, of fermented foods on the next, and of saffron the day after that. The issue isn’t necessarily the quality of the advice (the examples above actually include relevant references from the biomedical literature, although many champions are less rigorous). Rather, the problem is that of all the many things someone could potentially focus on to improve health, in the face of so much incoming information, how is someone supposed to even begin?
This dilemma reminds me very much of the challenge facing already busy physicians who are confronted with continuously expanding lists of mandated topics for each visit; while in theory it might be helpful to address all, in practice, this isn’t feasible – as the late Bill Gardner so thoughtfully discussed a decade ago, and as I discussed in The Bulwark in the context of COVID, here.
Gardner was inspired by the example of the “flood” of mandates facing military officials, leading to “ethical fading,” where corners inevitably are cut, rationalizations are “rampant,” and culture is corroded. To avoid this, as Dr. David Blumenthal advocated, you need to ruthlessly prioritize, and establish core priorities (or metrics) upon which to focus.
Similarly, many who might benefit from the pursuit of selective wellness advice are likely finding themselves overwhelmed and paralyzed by the volume (and lately, velocity) of well-intended advice.
In the future, AI might help us navigate this flood of information and data. As the always-eloquent Nathan Price (a professor at the Buck Institute for Research on Aging, CSO of Thorne, and co-author, with Lee Hood, of the 2023 book, The Age of Scientific Wellness) argues in a fascinating talk at the Buck, AI could provide a mechanism to integrate extensive personal data (include data collected by ever-more powerful wearables, as Subha Madhavan and I recently discussed) with the latest scientific research to deliver personalized health recommendations.
But today, what’s desperately needed is a fundamentally different approach to wellness, an approach that doesn’t seek to enumerate, measure, and optimize the vast number of factors and parameters that might have some effect on your health – where most longevity programs seem focused. Rather, we should emphasize a few critical high-value goals, where success could have the most significant impact on health.
Given both the prevalence of obesity and associated metabolic dysfunction — which seems to impact all the major diseases of aging (the “Four Horseman,” to use Attia’s phrasing) — and the remarkably efficacy of GLP-1RA medicines, this seems like a particularly promising place to start. As I’ve argued, success here is likely to generate an “agentic dividend” which could then be utilized to begin to motivate other health-promoting activities, kicking off a virtuous cycle. Initiating any sort of regular movement seems like a great goal to pursue next.
I’d argue that even beyond the value of motivating the many who don’t yet pursue health very actively, it’s also critical to create opportunities that speak to the many people who are keenly interested in health but are quite reasonably turned off by the narcissistic obsession with performance that seems to characterize longevity champions and enthusiasts.
There needs to be room for people who want to be healthier, but do not want the pursuit of health and obsession with health metrics and health blogs and health podcasts and health influencers to occupy a major portion of their lives — a degree of balance and wisdom of prioritization that in itself seems … rather healthy.
I envision a health enablement program that supports rather than overwhelms, meeting people where they are and illuminating the highest value opportunities for health improvement (like GLP-1RAs, for many, also low impact exercise to start with). Ideally this would be coupled with content that generally is not about health, fitness, or performance.
Instead, the program would focus on:
I see a particular need and opportunity for such an approach among the “Vanguard” 50+ highly agentic generation I described here.
This would be a great place to wrap, but I feel obliged to present a bit of a devil’s advocate response as well – inevitably informed by my own experiences. And what I’ve seen (as I’ve described in part here and here) is that the lifestyle changes that improved health may require are inherently disruptive — which of course is also the point.
For example, to transition durably – even with the help of GLP-1RAs – from a typical western diet to a lower calorie diet (ideally healthier as well) can require a profound shift from habits and customs developed over a lifetime. This is an underappreciated challenge. Moreover, when you are eating deliberately, and avoiding alcohol on most occasions, you’re probably a lot less fun socially, and can be a bit of a wet blanket if everyone is drinking beer and tearing into chips, and you’re drinking water while nibbling on celery.
In addition, as much as I love my exercise routine – which includes cardiovascular (I’m partial to outdoor jogging when it’s nice and Peloton when it’s not), strength, and balance (including twice-weekly pilates) – it’s a significant amount of time, about an hour a day, and I’m typically waking up at 4:30am to get through it before my regular day begins. This also means that when possible, I tend to go to bed fairly early to ensure a solid evening of sleep, another vital health priority.
While these practices may be extremely disciplined, it also means a lot of my life is structured around a significant commitment to diet, exercise, and sleep, which is unlikely to be ideal for many.
My hope is that it’s possible to make progress towards improved health without committing to everything, at least not all at once. Ideally (as I’ve described), progress on the eating front, likely abetted by GLP-1RAs, can create the seeds of success elsewhere.
But I also recognize – having observed this in others and experienced it on my own – how easy it is to fool yourself. We’ve all seen people who devour cake yet comfort themselves by choosing to wash it down with a diet coke, for example, or decide that a walk from the car to the door constitutes meaningful exercise.
While I’d like to say “at least that’s a good start,” I’m not sure it usually is; I suspect there’s a threshold effect, and if you don’t commit to a degree of change that involves activities that are at least somewhat unfamiliar, and probably uncomfortable, it might not be enough.
Bottom line is that while healthy aging may not require the obsession and immersion exemplified by many of its greatest champions, it requires more than good intentions, pro forma effort, or a magic jab alone. The challenge, inevitably, is discovering the right balance, and finding a way to age healthily while ensuring we’re using our precious time for something more meaningful than simply the continued pursuit of more of it.
Kevin Parker is today’s guest on The Long Run.
Kevin Parker, co-founder and CEO, Cartography Biosciences
Kevin is the co-founder and CEO of South San Francisco-based Cartography Biosciences. The company is using multi-omic tools to map out which targets are specifically expressed on cancer cells. The idea is to find new, precise targets that antibody drugs can aim for.
Cartography got started during the pandemic, raised a $57 million Series A round in the summer of 2022, and last year formed a partnership with Gilead Sciences.
Now, please join me and Kevin Parker on The Long Run.
Sam Rodriques, co-founder and CEO, FutureHouse
Monday was my last day as a group leader at The Francis Crick Institute.
I got my job at the Crick in 2020, almost exactly 5 years ago, right as COVID was beginning. I had finished my PhD in 2019, and had always told myself that I would only ever be an academic if I could find a place where I didn’t have to write grants, didn’t have to teach, and wasn’t on a tenure clock.
The Crick is one of a very small number of research institutes that affords its academics such privileges. It is endowed with extraordinary facilities, right in the heart of London. The offer for early-career researchers is almost too good to be true: almost $1 million a year in core support in personnel, reagents, and core facility usage, plus a generous startup equipment budget.
The Crick delivered on its promises, but European science faces some extraordinary headwinds. The general lack of funding has been well-documented. Red tape is far beyond anything that American academics have to deal with. But the biggest challenge of all is cultural. It’s less visible and far more pernicious.
Consider this example. About six months in, I was sitting in a meeting with some other faculty and core facility leaders, arguing that we needed to build out an ambitious screening platform similar to those at the Broad Institute of MIT and Harvard. Heads bobbed up and down. I thought we were getting somewhere.
As people were filing out, one of the group leaders hung around behind.
“Sam, you really have a lot of that American energy.”
I chuckled.
“Don’t worry,” she said, “Stay here for three years, and we’ll beat it out of you.”
It was sardonic humor. I later came to understand what she meant.
Another time, I showed up at the sequencing core facility at 3 pm on Friday with a library of samples ready to load for a batch run. I was eager to come back a day or two later with lots of data to sort through and analyze.
If only things moved that fast. I was told that I could submit a request form that would be processed the week after next (not next week, of course, because the person responsible was on annual leave). Then, when the person was back from leave, they would reach out to schedule a time to discuss my requirements in more detail. I asked if I could simply load the library on a benchtop Illumina Miseq machine that was sitting, idle, in plain view. This request was met with bewilderment.
Forget about it.
Then there was the time health and safety regulators were called to inspect my lab because I had stacked two stackable hybridization ovens without a proper risk assessment on file.
Worst of all, I felt the gnawing sense of falling behind in the global scientific competition, as one promising student or postdoc after another would decline an offer to go to San Francisco or Boston. Usually, that was because they were excited about the work we were doing, and wanted to be where the action was, where there was a critical mass of potential collaborators with complementary skills.
This is only part of the story, though. The UK abounds in excellent researchers. The Crick, in particular, is a remarkable institution. Paul Nurse, the Crick’s visionary leader, has attracted some of the most talented early-career group leaders in the world, like Pontus Skoglund, David Bauer, and many others. Paul has also cultivated a “can-do” attitude among his executive team: whenever I needed something, I knew that Paul or Richard Treisman or Sam Barrell or Steve Gamblin or another executive would back me up.
If the UK wants to maximize its scientific output, it needs to double down on funding for the Crick and its other top-performing institutions.
The UK has also been at the forefront of new experiments in ways to do science. ARIA, the UK’s Advanced Research & Invention Agency, has done a spectacular job in moving fast and supporting contrarian research through its programs and through new structures like Focused Research Organizations (FROs). Pillar VC’s new Encode fellowship (also ARIA-supported) is one of the best ideas I have seen for how to bring AI talent to hard science problems.
Nevertheless, there is only so much you can do against a cultural background that penalizes ambition. The further you got at the Crick away from the top executives, the more you would encounter the traditional European “second place is OK as long as you gave it a good shot,” kind of attitude.
The group leader’s sardonic warning was right: I did not last for three years. I was burning with ambition to seize the moment with AI to answer biological questions. It took me about a year to recognize that the UK would not be a long-term home, and another year and a half to found FutureHouse, in the second half of 2023.
I have lived in San Francisco since then. I haven’t regretted that decision for a minute. I have found talented students and postdocs who want to solve big problems. I have found investors willing to take risks. I have found a supportive community of entrepreneurs. It was the right move to pursue an ambitious research agenda, and pursue entrepreneurial dreams, in America.
At the elite levels, Europe has an extreme brain drain problem. The most ambitious people are mostly in the US, and so the most ambitious people continue to come here.
The US’s position as a talent magnet is not something we can take for granted; I am sure that with the correct combination of policies, we could eventually drive people elsewhere.
But it is also not a position that will be easily lost. There simply is nowhere else in the world that is anywhere near as attractive for talent. As long as the most ambitious and determined people can still find ways to get here, they will.
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David Li, co-founder and CEO, Meliora Therapeutics
We have entered a new era in biotech.
Turmoil at the FDA has introduced new uncertainty. NIH funding cuts and grant delays have led to academic institutions to hold off on job offers to young scientists. The Trump Administration’s reset of trade relations with the world caused a financial market meltdown, and wild rebound.
All of these things are contributing factors making the biotech downturn longer and more intense than almost anybody imagined. The XBI biotech stock index is at its lowest point in three years.
Amidst all the gloom and uncertainty, the National Security Commission on Emerging Biotechnology, a bipartisan committee created by Congress, released a report warning of imminent danger. The US biotech industry could lose its once formidable biotechnology advantage over China, the authors write.
By now, many have commented on China’s rise in biotech (see my initial post in January), and the trend has only continued. After my guest editorial was published, another five out-licensing deals from China were announced during the JP Morgan Healthcare Conference. Large pharma is continuing to invest in China (see AstraZeneca’s newly announced $2.5 billion investment in R&D).
While the report often comes across as hawk-ish as it portrays China as dangerous and nothing but a strategic competitor, my view is that the report falls short of suggesting actions that will meaningfully change the trajectory of the US biotech industry.
Recommendations in the report include:
The report starts with a strong call to action but ends up severely short on details. It misses a number of foundational factors that would make US biotech more competitive.
What should be part of the national strategy?
Currently there is a lack of a credible funding for incremental de-risking of science.
While cost efficiency is certainly important for any startup, the pendulum in today’s market has swung too far in the risk-averse direction. In many instances, startups are expected to have first-in-human data in their first round of funding! As a response, startups are raising more capital than ever to fund all the way through clinical value inflection points if possible.
This is simply incompatible with exploration of novel biology that requires incremental de-risking.
In a more balanced, less bearish financing environment, high-risk / high-reward concepts are first tested in vitro to generate proof of concept. That then unlocks preclinical model experiments, which then unlock financing for bringing a molecule into the clinic.
One large financing round upfront to cover all these steps isn’t a prudent use of capital, and isn’t friendly for founders and management teams.
Suggestion: Address the early-stage funding gap through multiple paths
The currency of our land is clinical data.
It is usually the key value inflection for therapeutic assets, the key piece of evidence that persuades investors to invest. But the cost of gathering the required preclinical evidence, before even entering the clinic, is too high in the US.
The comparatively high cost of preclinical work in the US makes reaching human clinical data for a single program — let alone multiple programs — quite a high bar. Many investors now look to other countries, where it’s possible to gather the data faster, and at a lower cost, before taking the next step.
To be globally competitive, US biotechs must efficiently and expediently reach the clinical value inflection point. This is especially true as Chinese biotechs are now on the order of 5-10x cheaper and likely twice as fast. The data produced is often of a high quality, even when compared directly to US biotechs. US biotechs must confront this reality and act accordingly.
Suggestions: Strive for efficiencies through
This means doubling down on novel biology, mechanisms, and modalities, rather than only focusing on clinic ready assets derived from incrementally novel targets.
Chinese biotechs have long looked to US for true scientific innovation leadership. Many have built businesses on the fast-follower model.
That’s changing. The China biotech ecosystem is learning and evolving – and quickly. Over the last several quarters, novel targets are being funded in the early stages.
Why is this happening? China has 5,000 startups and growing. The biotechs in the China ecosystem are striving for novelty in order to establish differentiation from each other in a cutthroat competition for funding, business development attention, and more. The bleeding edge of Chinese biotech startups are now exploring more and more new targets out of necessity for survival.
However, the US still holds a comparable advantage in deconvoluting novel mechanisms, better understanding pathways for disease, applying novel pharmacology approaches and matching them with the appropriate patient populations. It is precisely in these uncharted grounds of novel biology that the US derives its significant advantage, and where China and others are still lacking.
Suggestion: Sensible funding of basic and translational sciences
The US should continue to fund basic and translational sciences via the NIH, NSF, and other government agencies. While not immediately impacting venture funding and startup creation per se, the structural advantage of being the birthplace of novel biology exploration pays compounding dividends for the US ecosystem over time. Over a long enough time period, this research investment is the ultimate driver for global competitiveness.
It’s clear that we are entering a new era for our industry. Patient demand for good medicines is unrelenting. A patient in need does not care much if the medicine comes from the US biopharma industry, or somewhere else.
The US system must evolve with the times in order to capitalize on its strengths in pioneering true innovation, otherwise risk losing its pole position in global biotech.
The runway to do so is shrinking quickly.
Larry Corey, MD
I grew up in an era of Superman comic books.
Superman captivated the imagination of a generation of kids like me. It told stories of an otherwise ordinary human who could achieve extraordinary feats of speed and strength, leaping tall buildings with a single bound, to defeat the bad guys. Miracles could happen on a foundation of truth and justice, and that this was “the American way.”
Superman, of course, was a work of fiction. Kryptonite isn’t in the periodic table. But the optimistic narrative proved true over the course of my career in science. I have seen numerous medical miracles in my life, many of them starting in a lab.
CAR T cells to fight blood cancers; anti-cholesterol drugs for prevention of heart disease; ways to dissolve clots from strokes; gene therapies for genetic diseases; antisense RNA for treatment of eye and liver disease; and yes, mRNA vaccines for COVID. One of the greatest miracle technologies in the last few years has been the rapid expansion of mRNA vaccines and treatments.
Using mRNA to deliver a therapy to a cell or to produce an antigen to show the immune system what to defend the body against—a bounding leap of scientific advancement—has, largely to our dismay, been accompanied by an anti-science backlash.
Proposals are bubbling up around the country—Montana, Florida, Idaho, and Texas—to ban or restrict use of the technology, including some products already FDA approved. Scientists seeking grants to support their research are being advised to scrub the language “mRNA” from their grant proposals.
These ideas ignore a mountain of evidence supporting mRNA’s potential for medical advances in a wide variety of diseases. These gains were made through the federal government’s enormous investment in basic research. Scientists have been working painstakingly on the mRNA molecule since its discovery in the 1960s.
The journey for mRNA vaccines started in the early 1990s and culminated in the successful COVID-19 vaccines of 2020. Katalin Karikó and Drew Weissman won the Nobel Prize in 2023 for work that paved the way for the mRNA vaccines. Three to four billion doses were administered worldwide and these vaccines are widely acknowledged to have saved over a million lives in our country.
It’s true that viral escape has resulted in the reduction of efficacy against symptomatic disease. But in the elderly population most vulnerable to COVID, mRNA COVID-19 booster vaccines have low side effects and continue to reduce the risk of Emergency Room visits, hospitalization and death. The extension of mRNA technology to other respiratory diseases and viral infections such as cytomegalovirus and herpes simplex viruses are under investigation.
The mRNA technology is uniquely promising for developing new vaccines because of how quickly it can be designed and scaled up. Previous technologies would have taken too much time or money to effectively defend people against a fast-moving infectious disease.
The beauty of RNA is its price, its simplicity, its ability to be duplicated, and its iterative potential.
In my field of HIV vaccines, where we use mRNA in structure-based design, it’s a game changer. One can produce an mRNA vaccine for a Phase I clinical trial, to evaluate safety at a variety of doses, for about $1 million. That modest budget allows us to use rigorous protocols for GMP (Good Manufacturing Practices), and still have a candidate vaccine ready in four to six months, or even as fast as 70 days in a pandemic.
To train the immune system against this notoriously wily virus, we need four separate vaccinations, and we have two or three choices as to what might be the best structure for each vaccine prototype. The ability to quickly design and iterate mRNA gives us the options we need to keep making tweaks to come up with the optimal combination of structures and sequence of shots.
We have also used protein-based vaccines extensively, but making a protein vaccine usually takes three times as long and triple the budget. More than $4 million is needed to produce a small batch for early vaccine trials, and it usually takes 12 to 15 months to manufacture.
About 30 to 40 percent of the time, after all this time and expense on manufacturing runs, we come away empty handed and unable to run the trials. That’s because the protein cannot always be predicted to fold exactly or be well stabilized when manufactured.
Protein-based vaccines, when properly conceived and folded, can have advantages over mRNA for population-based control because they have a long shelf life and only require basic refrigeration. But those advantages only kick in once you know what to make and how you are making it.
We need mRNA for the research enterprise. That does not mean it will always emerge as the technology used in the global rollout of a product like a vaccine. One could use mRNA in discovery to identify the right protein components, then switch to a conventional protein subunit vaccine.
The speed and modularity of mRNA for vaccine research is also useful for research into cancer and autoimmune disease. The long list of potential indications includes malignant melanoma, brain cancer, liver disease, colon cancer, interstitial lung disease; and many genetic diseases. One of the most impressive late-stage developments is mRNA for use in personalized cancer vaccines to prevent the cancer from spreading.
A new generation of startups have emerged to develop second-, third-, and fourth-generation mRNA vaccine products—to make the lipid nanoparticles specific for a target organ; to get rid of the lipid nanoparticle; to decrease the amount of toxicity; to improve the transcription of RNA so there’s greater potency; and just to develop immunotherapies to deliver intracellularly what before now has not been possible. It’s as if the mRNA vaccine allowed the mRNA technology to reach a threshold to expand its use exponentially—a potentially transformative tool in health care worldwide.
Why are we seeing such a strong backlash? From both a health-care perspective and an economic standpoint, it makes no sense. The gap is wide between the scientific publications and what is pushed out on the dark web. There’s a cynicism that says everything in the research sector is wrong. Why has this gone so far? Why can’t we easily explain that mRNA doesn’t alter your DNA? It stays in the cytoplasm and doesn’t get into the nucleus. God designed it so it couldn’t get to your DNA.
How can the business community, which has so much invested in this, not challenge the political tsunami threatening to overwhelm the achievements of science?
Why aren’t they out there telling the science side? Are they working “behind the scenes” out of fear of retribution? What’s the fear?
Shouldn’t the greater fear be that we don’t deliver what we know we can? That people will die or have incredible morbidity by not having access to a discovery that can alter their lives?
Fear remains our greatest foe in this American tale. What’s happened to truth, justice, and the American way?
Looks like we need an mRNA champion with a red cape.
George Eastwood, executive director, Emily Whitehead Foundation
Leading a nonprofit that helps kids and families with terrible diseases requires a certain ability to roll with the punches.
That feeling hit last week when I heard about Peter Marks’ forced resignation as Director of the FDA’s Center for Biologics Evaluation and Research (CBER). Here was a scientific champion of innovative cell and gene therapies at the FDA. He was respected by many in the rare disease community as someone seeking to do what’s best for patients with little or no treatment options. Seeing him unceremoniously pushed out felt like a punch in the gut.
I called Sharon King, a rare disease advocate, valued Emily Whitehead Foundation board member and friend. Her daughter was diagnosed in 2006 with CLN1 Batten Disease, a rare, inherited, and always fatal neurodegenerative disease.
“Ever since my daughter’s diagnosis, I’ve always needed to look for the silver lining,” Sharon told me through tears. “But with Peter leaving, that’s incredibly difficult. He has been a consistent champion for the rare disease community, willing to embrace new ideas to help us find a way forward. His leaving is no small loss for our community.”
That sentiment is widely shared in the rare disease community. In the years of collaborating with Peter and watching him work, I’ve observed three qualities that made his leadership transformative.
First was his unique ability to connect an entire ecosystem.
Peter Marks, former director, Center for Biologics Evaluation and Research, FDA
At numerous meetings, Peter directly engaged with pharma executives, technology innovators and clinicians, always exhibiting the same level of thoughtful attention. He wasn’t concerned with people’s status. He was more concerned with how the person he was speaking with could contribute toward solving the problem.
Last fall, I saw that when he flew to Philadelphia on a Friday night to deliver a compassionate speech at the Emily Whitehead Foundation’s Believe Ball. It was a celebration of 25 patient Warriors and their families. These Warriors, representing various diseases and modalities, were able to be treated because of his work evaluating the risks and benefits of cell and gene therapies. Everyone in the room felt that spirit of hope, and shared purpose that Peter helped enable.
His second key leadership trait was his transparency. When secondary malignancy concerns emerged with CAR-T therapies after several years of being available on the market, the FDA initially issued black boxed warnings across the entire class. This created fear, uncertainty and tension with clinicians and developers. Rather than doubling down on an across-the-board warning that could curb access to patients who might benefit, Peter assured all the relevant audiences – physicians, drug developers, patients, and payers – that the FDA would take a balanced position based on the best available evidence of safety and efficacy for each product.
“We are in the process right now of reevaluating the need for the current labeling on these products. You may see some actions, in some cases, removing warnings, in some cases, adding warnings, changing warnings,” Peter said at the time. This straightforward communication reassured both industry and patient communities.
Finally, his courage in making difficult decisions stood out.
His decision to overrule the FDA advisory committee and approve Sarepta Therapeutics’ Elevidys, a gene therapy for Duchenne Muscular Dystrophy, required courage. It demonstrated his willingness to stand firmly behind innovative treatments that could transform lives. It underscored his willingness to not only consider the totality of data for a new treatment, but also to listen to patient voices about the difference a new medicine can make.
Peter Marks’ legacy at the FDA includes many concrete achievements: numerous biologics license approvals, groundbreaking gene therapies for previously untreatable rare diseases, and innovative programs like START and the Rare Disease Innovation Hub. His commitment to integrating advances in science and technology into the regulatory process enhanced the availability of safe and effective medical products for countless patients.
The FDA now has a leadership gap in this important job. We urge the Administration to act swiftly in appointing a long-term successor who understands the delicate balance between rigorous evaluation and urgent patient needs. This is not just about continuity but about preserving Peter’s patient-centric approach.
When I commiserated with Sharon again after processing this sad news, we tried to find the silver lining.
Perhaps it exists in what Peter leaves behind: a regulatory framework that values patient input, transparency and innovation. Our responsibility now is to ensure his pioneering approach continues, inspiring the next generation of FDA leadership to bring life-saving therapies to those who need them most.
Luke Timmerman, founder & editor, Timmerman Report
The 5th annual Timmerman Traverse for Life Science Cares is fired up and ready for outdoor adventure in 2025.
We’re on a mission to raise $1 million to fight poverty.
This year’s team is preparing for a pair of challenging hikes in the Pacific Northwest, Aug. 18-19. We’ll cover 20 miles of trails, ascend 7,000 vertical feet, and savor some of the most spectacular scenery in North America.
We’ll enjoy fresh air and exercise. We’ll make new friends. Together, we are giving back to our communities.
We are off to a strong start this year with $200,000 already in the bank. Each hiker is required to raise at least $35,000. Many will go above and beyond.
The money we raise will flow through a network of nonprofits in the five cities where Life Science Cares operates – Boston, San Francisco, San Diego, Philadelphia and New York.
These nonprofits are on the ground in each city, tackling a variety of needs. Some cover basic, immediate needs like food and shelter. Others provide long-term pathways out of poverty through education and job training.
Life Science Cares provides a lifeline to these nonprofits. It is the bridge between the biotech community and the broader community. Life Science Cares connects us to each other and to our mission – alleviating suffering from disease.
Please show your support for these men and women working in common cause.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $199 per year, you reward quality independent biotech reporting, and encourage more.
Times are tough in biotech, but this is an industry where we learn, adapt, and move forward.
I’m proud to announce that the 2025 Timmerman Traverse for Damon Runyon Cancer Research Foundation has hit its fundraising goal of $700,000 to support high-risk / high-reward cancer research. We stand at $702,555 in closed donations.
Our team of 16 hikers is now packing bags and gearing up to trek to Everest Base Camp at 17,500 feet / 5,364 meters. We will hike in Nepal Apr. 15-25.
This Timmerman Traverse campaign, like all others, required sweat and sacrifice. We had to overcome adversity. It took creativity and relentlessness. We kept working because it’s important to uplift the next generation of outstanding cancer researchers, especially in a moment of so much potential.
We did it together.
Now we will enjoy some quiet time, away from the daily work world. We will come together as a community of men and women united in shared purpose.
We will slow down, unplug. We will stare up in awe at one of the marvelous mountain ranges of the world. We will feel the challenge of hiking uphill, on dirt and rock, breathing thin air. We will sip warm tea in rustic lodges, around a wood burning stove. We will play card games and tell stories. We will shiver when sliding into our sleeping bags at night.
We will form friendships to last a lifetime.
Thanks to our top-tier sponsors – Bristol Myers Squibb; Kite, a Gilead company; and Alnylam Pharmaceuticals.
Thanks also to Cooley, Higgins Group, HLX Life Sciences, KMAK Capital, Latham & Watkins, Lincswitch Therapeutics, Lumanity, Lyfe Capital, NeoGenomics, Nucleate, PH Foundation, PhaseV, Relation Therapeutics, TD Securities and WilmerHale.
Thanks to Aragen, Argot Partners, Bain Capital Life Sciences, BioInvent, British Land, Causaly, DH Life Sciences, Emily Whitehead Foundation, ImmunoPrecise Antibodies, Lonza, Nurix Therapeutics, OrbiMed, Recursion, Saras Capital, Singular Biotech, and TCG Life Sciences.
For a full list of corporate sponsors, click here.
Thanks to this year’s team:
Friends, family, and colleagues can follow our progress on the expedition here.
Finally, thanks for everyone who donated, and everyone who makes it their life mission to alleviate suffering from cancer.
We may come up with a few ideas on the trail to share with you later. — Luke
L to R: Henry Kilgore of the Whitehead Institute, Luke Timmerman, and Will Chen of the University of Washington on Kilimanjaro, Feb. 2024. Henry and Will are Damon Runyon Fellows who participated in the inaugural Timmerman Traverse for Damon Runyon on Kilimanjaro, Feb. 2024. They are a couple of the brilliant young scientists that our donations support.
Enjoy a few more photos from my Everest and Everest Base Camp archives.
Monks in training, Thame Monastery.
The legendary Lakpa Rita Sherpa, 17-time Everest summiter, in front of a Tibetan Buddhist stupa, with Ama Dablam in the background.
Hiking into and above the clouds.
Spinning the prayer wheels, paying respects to the local culture, sending forth good vibrations through the Khumbu Valley.
Luke Timmerman with mountain guide Jangbu Sherpa at Everest Base Camp. 2018.
David Roblin is today’s guest on The Long Run podcast.
David is the CEO of London-based Relation Therapeutics. The company uses multi-omic tools to look for drug targets in human tissue samples. It seeks to find the relationships between perturbed biological states and disease, with the help of machine learning.
Relation emphasizes relationships in another sense as well – the cultural kind among biologists, engineers, physicians and other professionals who need to find ways to meld their disciplines together to improve biopharma R&D success rates.
David Roblin, CEO, Relation Therapeutics
The startup has raised more than $80 million to date from a diverse group of tech and biotech investors. Late last year, it announced a preclinical partnership with GSK in which the pharma giant is supporting Relation’s work to discover novel drugs for fibrosis and osteoarthritis.
David comes to this work after a long career as a physician, then as an R&D executive at large biopharma companies Bayer and Pfizer, and in translational research from The Francis Crick Institute..
I met David and the team in London in late January. I was wearing another hat there, as part of a fundraising event for the Timmerman Traverse for Damon Runyon Cancer Research Foundation. I learned about the London biotech community, and how the many players – academia, hospitals, startups, and large tech and pharma companies – are seeking to work together and put the pieces together to improve the biopharma R&D enterprise. I hope you will learn something too.
Now, please join me and David Roblin on The Long Run.
