11
Feb
2025

Building a Fully Integrated Biopharma For the Muscle: Robert Blum on The Long Run

Robert Blum is today’s guest on The Long Run.

Robert is the CEO of South San Francisco-based Cytokinetics. He joined the company back in the beginning in 1998 and became CEO in 2007.

Robert Blum, CEO, Cytokinetics

This company, and Robert’s career, are emblematic of what this show is about — The Long Run that it takes to develop new medicines. The company has been in business more than 25 years and still doesn’t yet have any of its own products for sale on the US market. It has burned through more than $2.5 billion since the beginning, according to its most recent filing with the Securities and Exchange Commission.

The narrative of a relentless, but perennial development-stage company is likely to change this year. Investors expect it to win FDA clearance to start selling its first product. It is aficamten for hypertrophic cardiomyopathy or HCM. It’s a thickening of the heart muscle that makes it more difficult to efficiently pump blood. The drug is a cardiac myosin inhibitor that has been shown to improve exercise capacity and clinical outcomes for patients whose lives are constrained by HCM.

Robert is a fascinating character. He grew up in a Jewish family and went to Catholic school in Western North Carolina. He idolized biotech entrepreneur Bob Swanson as a kid. He has spent his adult life trying to follow the playbook of the full, vertically integrated biopharma company that discovers, develops, and commercializes its own medicines – the original biotech model envisioned by the Genentech co-founder. This is just about the hardest thing imaginable in business.

There’s a tenacity and grit to Robert that I think you’ll hear clearly. It was especially tested in the low moments, like when the FDA declined to approve omecantiv mecarbil, a cardiac myosin activator for heart failure.

This episode was recorded at the JP Morgan Healthcare Conference in San Francisco. We could have gone for another hour or two talking about some of the key events in the company’s history. But listeners will certainly get a sense for the man’s philosophy, how it got here on the cusp of building its own commercial team, and why Cytokinetics has had the staying power to remain independent and in position to compete with Bristol Myers Squibb in a high-stakes therapeutic category.

Now before we get started, a word from the sponsor of The Long Run:

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Have you listened to a handful of episodes of The Long Run? My friends at The Linus Group helped craft a survey so you can provide me some feedback on what you like, what you don’t, and what you’d like to see more or less of from this podcast. It only takes 5 minutes, and if you complete the survey, you will be entered with a chance to win one of three complimentary annual subscriptions to Timmerman Report (a $199 value).

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Now, please join me and Robert Blum on The Long Run.

10
Feb
2025

Aligning Risk-Benefit Assessments in Sickle Cell and Oncology Therapies

Alan Anderson, MD

Pfizer’s decision last fall to withdraw voxelotor (Oxbryta) from the worldwide market is an example of how companies make risk-benefit calculations about medicines, and how those decisions vary widely from one category to another.

Cancer drugs have their own set of standards.

The risk-benefit calculus routinely accommodates uncertainty and severe side effects, if the medicine offers a modest and temporary clinical benefit, given the life-threatening nature of many cancers.

Sickle cell disease is a different story. Decisions to advance or shelve a drug candidate often appear to be driven by a more risk-averse model.

This is odd, because sickle cell disease dramatically reduces quality of life and results in a 30-year reduction in life expectancy. This different calculus for cancer and sickle cell disease patients is especially concerning when considering that sickle cell disease research and development suffers from chronic underinvestment and historical stigmatization.

Patients with sickle cell disease have never been given the R&D resources or clinical support they deserve. These patients have a debilitating, chronic illness. Their treatment options are few.

Pfizer released a statement on Sept. 25 that concerns over Oxbryta’s long-term safety profile and questions about its overall clinical benefit were key reasons for its market removal. However, these explanations seem at odds with the evidence from the HOPE clinical trials, which showed a significant, sustained improvement in hemoglobin levels, reduction in hemolysis, and a reassuring safety profile (NEJM article, June 2019).

Moreover, since FDA approval in November 2019, many U.S. physicians have reported tangible clinical benefits and manageable side effects in patients treated with Oxbryta.

This disconnect between Pfizer’s stated rationale and both the trial data and real-world experience raises questions about whether factors other than the established clinical performance are driving the decision to pull the medication from the market. It was also surprising that no alternatives were made available to clinicians, including the addition of warnings to the label or the development of a compassionate use program for patients with no other options.

When a medication like Oxbryta is removed from the market with little warning or input from the community it serves, the consequences are far-reaching. This decision, and others like it, limit the ability of clinicians to engage in detailed, patient-specific discussions about the trade-offs inherent in therapy choices. These conversations are standard practice in oncology.

Cancer patients are routinely informed that aggressive treatments come with high risks, yet the potential benefits may justify these risks. By applying a balanced risk-benefit framework to sickle cell disease, pharmaceutical companies could empower physicians to provide tailored, nuanced care, fostering informed decision-making even amid uncertainty.

Furthermore, the rapid removal of an effective drug like Oxbryta undermines trust among patients, clinicians, and advocacy groups. A more inclusive process that incorporates these voices can ensure that decisions are made with a full understanding of the lived realities of patients, whose needs and perspectives are often marginalized. Such an approach not only aligns with ethical imperatives but also has the potential to drive innovation by fostering a more collaborative environment among industry, regulators, and the community.

The case of Oxbryta should serve as a wake-up call: pharmaceutical companies must recognize that a one-size-fits-all approach to risk evaluation is inadequate.

Instead, embracing a more balanced and inclusive strategy will enable physicians to have the kind of comprehensive, informed bedside discussions that are the hallmark of oncology care. By adopting a nuanced risk-benefit framework for sickle cell disease treatment, we would honor the principle that every patient deserves the best possible chance at improved quality of life.

 

Alan R. Anderson, MD, Associate Professor of Pediatrics, University of South Carolina School of Medicine; Medical Director, Lifespan Sickle Cell Center of Excellence, Prisma Health, Greenville, SC

4
Feb
2025

DeepSeek Shocked Silicon Valley, but It’s Not Earth Shaking for Biotech

Simon Barnett, partner and head of research, Dimension

DeepSeek, the artificial intelligence (AI) research group owned by Chinese hedge fund High-Flyer, dominated last week’s news cycle—at least for 24-48 hours. The group launched R1, the latest in a series of cutting-edge large language models (LLMs). Investors panicked, erasing over $1 trillion of U.S. equity market cap in a single day.

Nvidia (NVDA), the maker of high-powered AI chips, shed $500 billion alone. Speculators feared the demand for Nvidia’s chip might dry up since DeepSeek found an ostensible workaround delivering stellar LLM performance on vastly less compute. The news sent shockwaves throughout Silicon Valley.

Could there be a similar DeepSeek moment for the burgeoning intersection of machine learning (ML) and the life sciences?

No—I don’t think so. The conditions leading to the market frenzy in the natural language processing (NLP) space are quite different from those in biotech—setting these domains on divergent courses.

THE STATE OF THE ML UNION

The frontier of NLP research is governed by so-called scaling laws. Chief amongst these is that training large ML algorithms using vast datasets and enormous gobs of compute will result in monotonically improving model performance. 

Big tech is betting these models will steadily breach performance thresholds wherein they can extract inexorably more economic value—first by displacing low-level tasks and eventually complex knowledge work. 

In the NLP realm, complex ML model architectures and Internet data are easy to come by. Compute is the scarce resource gating the progress of LLMs. Training large algorithms requires expensive, specialized hardware—principally Nvidia (NVDA) GPUs

Frontier NLP model development is thus a pay-to-play endeavor. Companies like OpenAI and Anthropic have contributed enormously to ML research. They’ve also leveraged the compute scaling narrative to corral the capital necessary to build veritable armamentariums of GPUs. The size and scope of these compute investments – in sheer dollar terms – functions like a competitive moat.

These conditions have shaped the industry into an oligopoly of well-capitalized, closed-source groups exchanging dollars for compute with the hope that scaled ML models will power a growing set of applications—forking the history of life on Earth.  

DEEPSEEK R1 CONSTITUTES A NARRATIVE VIOLATION

DeepSeek R1 seemingly violated the closed-source scaling narrative, casting uncertainty over big tech’s ML primacy.

R1 isn’t the most performant model, but it’s good enough to power most downstream tasks. Far more relevant are the facts that—(a) DeepSeek made R1 open-source under the MIT license and (b) DeepSeek claims R1 cost ~10x less to train and ~90% less to use than other contemporary LLMs.* 

The emergence of an inexpensive, open-source (ish) LLM has driven the value capture conversation marginally away from the close-source cabinet and more towards the application layer—to groups solving UI/UX issues and product/market fit questions. Understandably, big LLM providers aren’t static. They will rebut with their own competitive salvos. Perhaps they already have. 

BIOLOGY IS A SEPARATE BEAST

Biotech companies and academics alike are releasing scaled biomolecular ML models at a fever pitch, whether to predict protein-ligand complex structures, engineer therapeutic proteins, or surface developable small molecule hits. 

However, the dynamics governing the evolution of ML in the life sciences is unique. Market participants should be cautious about reapplying the parables of the current moment in natural language processing into the biotechnology field. 

While GPUs cost the same across ML domains, they aren’t the rate limiter (yet) in the life sciences. Throwing disproportionately large compute at sparse data results in overfitting, a dangerous phenomenon where models overstate their performance and struggle to generalize.

Data is the scarce asset in the life sciences. Biological data doesn’t expand ambiently like the Internet, with several billion users contributing to the information commons every day. Open-source life sciences datasets are relatively small and contain experimental artifacts, challenging ML model training. Even so, this public data has been enough to power innovation to date.

ML model innovation is perennially useful in biology. For example, AlphaFold2’s architectural novelties burst open the field of computational protein structure prediction in 2021 despite the underlying dataset—the Protein Data Bank—being available for years. 

The reason there’s unlikely to be a singular DeepSeek moment at the intersection of ML and biology is because we’re still inundated in DeepSeek moments. Acts of algorithmic clairvoyance have spiked the field in new, exciting directions.

As the open-source data wellspring dries up, however, ML in the life sciences may move in the opposite direction to NLP. The field may instead shift towards closed-source walled gardens that house high-throughput, experimental data foundries—the scarce asset that will imbue scaled biological models with economically valuable capabilities. 

 

 

*DeepSeek likely distilled R1 from other LLMs. They also did not include all the R&D costs they drafted off of to build R1, casting significant doubt on the stated training costs. The inference costs have replicated in users’ hands, making them much more viable. 

2
Feb
2025

Timmerman Report Turns 10

Timmerman Report is 10 years old today.

On Feb. 2, 2015, I rode my bike to the office on a wet Seattle morning and turned on the lights. I thought there was a need for clear, probing, contextual — and fiercely independent — biotech journalism.

The past 10 years of biotech have been remarkable. I’ve had a front-row seat.

It’s been a privilege to report on lifesaving CAR-T cell therapies for cancer and autoimmunity, a CRISPR gene editing cure for sickle cell disease, transformative medicines for hepatitis C, HIV and cystic fibrosis and more. A wide range of emerging treatment modalities are here today and arriving by the bushel tomorrow. I’m talking about antibody-drug conjugates for cancer, targeted radiopharmaceuticals, bispecific and multi-specific antibodies, targeted small molecule protein degraders, mRNA vaccines and therapies, small molecules that bind at allosteric sites, and RNA-based medicines. The underlying biology is being better elucidated, and the tools to intervene with disease targets are getting better.

The core challenge remains: How to bring these medical marvels closer to more patients, at a price that we can afford and that rewards the scientists and entrepreneurs who create them.

Thank you to all of the loyal subscribers who have made it possible for me to cover these seismic events. Special thanks to my advisory board: Vicki Sato, Bob More, Julie Sunderland, Rob Perez, Katrine Bosley and Roger Longman.

I’m grateful to have this platform for independent biotech journalism, and to steward it as a trusted source. TR seeks to understand, to inform, to enlighten, and to challenge readers to think. It’s about exploring the frontiers of science and drug discovery and thinking through the implications of it for society.

That’s not necessarily the formula for going viral. Yet the business is thriving, with more than 1,300 active, paid subscribers. The Long Run podcast has received 1.5 million plays since it began in 2017.

Timmerman Report is a platform for covering biotech without fear or favor. It is the beating heart of everything I do. TR has opened up avenues for me to give back, mobilizing the biotech community around worthy causes. Since 2017, my mountaineering campaigns have catalyzed the biotech community to give back more than $12 million to alleviate suffering from cancer, poverty, and sickle cell disease.

Those trips have been deeply meaningful. Friendships have been formed. Companies and collaborations have been born. I’m proud that we, together, have catalyzed so much good work. This will continue. The impact will grow.

Sometimes we all need to stop and think about what we’re doing, where we’ve come from, and where we’re going. I’m not taking anything for granted.

Thank you. For reading. For listening. For supporting quality independent journalism. And for doing the day-to-day, bit-by-bit work of improving human health and creating a better world.

Come celebrate the TR 10th anniversary with fellow readers and listeners.

TR10 East Coast Party / Cambridge, Mass. / Mar. 6

TR10 West Coast Party / Seattle / Mar. 13

Interested in joining HSBC Innovation Banking as a sponsor of these free and fun community events? Write to luke@timmermanreport.com.

Let’s imagine an even more vibrant biotech future for the next 10.

 

2
Feb
2025

The Future of AI and Health, Part III: Improving Health By Enhancing Agency

David Shaywitz

Part II of this series is here

“Agency,” Harvard’s Zak Kohane and I agree, is the word of 2025.   

Kohane’s reasoning: “Patients understand how to increase their agency in their disease journey with often correct and thoughtful instant second opinions from AI.”   

This perspective aligns with the opportunities described by A16z VCs Vijay Pande and Marc Andreessen, as discussed in Part II.

Agentic AI

While I’ll focus on human agency, it’s important to acknowledge that agency is also showing up everywhere in connection to generative AI technologies (although Kohane says “the agency of computational entities is less of a quantum leap by comparison”).

What’s excited the AI community are “AI agents” or “agentic AI” — AI-enabled tools that can perform a series of tasks with far greater flexibility than traditional, rule-based automation approaches. 

As data scientist Sahin Ahmed explains in a January 2025 Medium post, AI agents are:

“emerging as a significant force driving the next wave of technological innovation. AI agents are autonomous systems capable of perceiving their environment, making decisions, and taking actions to achieve specific goals. This burgeoning field is experiencing rapid growth, with the AI agents market projected to soar from $5.1 billion in 2024 to $47.1 billion by 2030.”

AI agents may also be useful in health and science. Kohane’s (and my) colleague in Harvard’s Department of Biomedical Informatics, Marinka Zitnik, along with her co-authors, published a visionary Perspective in Cell late last year offering a bold framework for “Empowering biomedical discovery with AI agents.” Such agents, the authors suggest, would work alongside human scientists, enhancing their abilities.  

This is where I get particularly interested – the opportunity, in the broadest sense, for technologies to enhance human agency. 

Human Agency

The idea that technology, particularly AI, can expand our agency is the central thesis of Reid Hoffman’s latest book, Superagency, which I recently reviewed in the WSJ (here).  

Agency – including the power of individuals (with a lot of luck) to shape the course of history, and our obligation, in the face of ambiguity, to try our best rather than shrug our shoulders – is also an important theme of several upcoming books I’ve read for review (stay tuned).

Martin Seligman, Zellerbach Family Professor of Psychology, University of Pennsylvania; Founding Director, Positive Psychology Center

Perhaps the most comprehensive perspective of human agency has been developed by University of Pennsylvania professor Martin Seligman, the father of positive psychology, whose work I’ve discussed for TR readers here in May 2021 and here in December 2021.

As Seligman explained in a 2021 talk at the MIT Media Lab (video here), his entire career has focused on the importance and plasticity of agency, which he says boils down the belief, “I can make a positive difference in the world.”

In an ambitious 2021 “psycho-historical” paper making the audacious argument that agency is responsible for human progress, he writes,

“When do we try hard? When do we break out of our sloth and overcome barriers that seem insurmountable? When do we reach for goals that seem unobtainable? When do we persist against the odds? When do we make new, creative departures? These all require Agency, an individual’s belief that he or she can influence the world.”

Agency has three components, he says:

  • Efficacy – I can achieve a specific goal in here and now;
  • Optimism – I can achieve this specific goal now just now but also far into the future;
  • Imagination – I can achieve many goals far into the future.

Historically, Seligman says, the field of psychology focused on misery. 

“Freud and Schopenhauer told us that the best you could ever do in life was not to be miserable.  So a successful life held suffering as close to zero as possible.  There was no theory of well-being.” 

His own initial work focused on depression, and he is perhaps best known for the “learned helplessness” model of this condition.

Over time, as he recognized resilience even in people facing difficult situations, he decided that he was wrong about the learned helplessness model. Helplessness is our default reaction, he concluded, and what can be learned is hopefulness and optimism.

He subsequently founded the field of positive psychology which he describes as “the generalization of optimism.” He introduced the “PERMA” framework, composed of five different, buildable elements, as discussed in TR here in May 2021. 

Critically, he says, “having PERMA is causal.” It’s not that being successful makes you happier. Citing longitudinal studies, and alluding to evidence-based interventions, he says “happy people are healthier, they live longer, they have better social relationships. They’re more productive at work. They’re better citizens. They’re more creative. And they’re more resilient.”

Referencing what he describes as an extensive literature, Seligman argues that “people who have high agency are physically healthier,” adding “If you look at people with high agency holding constant the traditional risk factors, they live on average 6-8 years longer,” compared to people with low agency.   

He continues, “Optimistic people — people who believe that they can control things far into the future, bounce back. They resist depression.  They succeed.  They try harder and give up less at school.”   They do better in college than their SATs predict, he says, and do better at work.  In contrast, “pessimistic people are less productive than their talents predict.” 

From a health perspective, he says “about 20 well-done studies” have shown that after accounting for “the usual risk factors,” it turns out that “being in the bottom quartile of pessimism is roughly equivalent to smoking 2-3 packs of cigarettes a day for longevity. “

Critically, he believes agency is teachable. Positive psychology, he argues, tells us “how to build efficacy, how to build optimism, and a little bit about how to build imagination – although if someone tells you they know how to build creativity, hold on to your wallet; that’s unknown.”

Seligman contends the way to build agency has been “well-defined,” adding “there are a couple of hundred articles on exercises that build agency and well-being.” 

He explains one approach, often referred to as “cognitive restructuring,” involving recognizing “the most catastrophic things you say to yourself when things go badly and then to dispute them realistically.” 

He continues,

“So if you’re rejected by your girlfriend, you have to be conscious that you’re saying, I’m unlovable, you’ll never find love again. And then we teach people to realistically dispute their most catastrophic beliefs, treat them as if they were said by a third person whose mission in life was to distort reality and to make you as miserable as possible.”

So far, this all sounds really promising. 

However, in my reading, data demonstrating that positive psychology (“pro-agentic”) interventions meaningfully improve health are, most generously, a work in progress. 

The field has been dogged by methodological issues like consistency in both approaches to interventions and approaches to measurement, as discussed by Feig et al in 2022, here, and by Kubzansky et al in 2023, here

“The existing literature is limited by small sample size, low study quality and inconsistent intervention content and outcome measurement,” Feig writes.

So where does this leave us?

Foundationally, I suspect Seligman is right about the centrality of agency, about its power and importance, and its role in enabling us, as individuals and collectively, to live better, healthier, more meaningful lives.

I am also excited by the promise of technology to help us build and enhance our sense of the agency Seligman describes, while recognizing the need for more persuasive data linking agency-enhancing interventions to meaningfully improved health. 

I’m particularly drawn to the health-promoting opportunities I see at the intersection of interventions seeking to enhance agency and interventions that seek to encourage movement (a priority discussed in TR here in November 2021). Imagine the promise of a fitness platform (like Peloton or Tonal), device (Whoop, Oura, Apple Watch), or app (Strava, All Trails) if supercharged by deliberate, PERMA-informed efforts to enhance our sense of agency. (The alignment of the Timmerman Traverse with these goals has not escaped TR’s notice.)

Data Agency

One important caveat here is to the ensure we’ve learned a critical lesson from the tribulations of the early quantified-self movement (see my TR discussion here from April 2021): simply measuring or tracking data doesn’t necessarily lead to insights or improvements.

As former quantified-self enthusiast and Wired editor Chris Anderson famously tweeted in 2016, “After many years of self-tracking everything (activity, work, sleep) I’ve decided it’s ~pointless. No non-obvious lessons or incentives 🙁”

The point here is that, generally speaking, simply delivering us lots of data may not translate to meaningful improvements in either agency or health.

On the other hand, I strongly share the optimism of Goldberg, Kohane, and others that generative AI tools are already helping to empower patients and caregivers, a trend that (as Andreessen suggests, see Part II) will only continue. 

One example highlighting both the potential and need was recently described in The Free Press: a writer’s mom, initially diagnosed with Alzheimer’s Disease, was subsequently discovered to have a reversible condition. It turned out her symptoms were caused by an occult leak of spinal fluid, which was identified and corrected. Her symptoms disappeared, her “life restored,” as the author put it.

While AI played no role in this story, it is the exactly the sort of unusual but transformative diagnosis that in the future, AI is likely to suggest. 

Harried physicians – especially in the case of patients like in the example above, who are evaluated for a spectrum of symptoms by a range of doctors – tend to focus on the most common conditions, aligned with their specialty.  If you see a pulmonologist for insomnia, she’s likely to suspect obstructive sleep apnea, obtain a sleep study, and recommend CPAP.  In contrast, a psychiatrist may consider anxiety or depression and suggest cognitive behavioral therapy or a medication. 

If you are a patient or a caregiver, it’s easy to imagine that an AI tool, uniquely, may have the patience to receive as much information as you are willing to offer; the ability to engage with you around the data you’re providing; and the insight (if that’s the right word) to integrate the totality of information and suggest potential diagnoses or at least next steps in a comprehensive manner, not biased by the specialty (or relative ignorance) of a given physician.

Finally, speaking of cognition and agency, an encouraging paper (originally flagged by Daniel Drucker) from Australia was recently published in Nature Medicine.  This study demonstrated that the delivery of four on-line personalized interventions targeting established dementia risk factors (“physical activity, nutrition, cognitive activity, and depression/anxiety) to older people “resulted in significantly better cognition in older adults over 3 years.”

While an animated discussion around potential methodological issues flared in response to Eric Topol’s LinkedIn post about the study, the possibility of reducing dementia risk through online interventions is tremendous exciting, especially if you consider this is likely the beginning of an optimization process. 

In the same way traditional combination medical therapies for conditions from HIV to cancer improved significantly through incremental advances (as I’ve discussed here), the establishment of a foothold for digital therapies might provide a meaningful starting point for future progress.

Bottom Line

We are living through a remarkably exciting time to pursue the promise of technology, especially AI, in health – even if no one really knows what this future will look like.  The use of technology to enhance personal agency represents a significant opportunity, and through the consumer-facing tools of generative AI, is already reframing the patient/doctor relationship.  The application of technology to develop and support our sense of efficacy and optimism – as well as to encourage us to move more – represents an area of exceptional interest and significant potential impact.

2
Feb
2025

The Future of AI and Health, Part II: Andreessen and Colleagues Weigh In

David Shaywitz

Part I of this series is here.

Over its 15 years of existence, the Andreessen Horowitz (“A16z”) venture capital firm has evolved from a media-savvy disruptive upstart to an exceedingly well-heeled incumbent and powerful force in Silicon Valley and the country. 

In April 2024, the firm announced a gargantuan $7.2B (with a “B”) fund.  For a typical VC firm with a “2 and 20” compensation structure that pays the VC a 2 percent annual fee for assets under management and a 20 percent share of the returns on investment, this would translate to $144 million annually in management fees alone, even if the firm didn’t generate any positive returns (which it apparently does).

That’s a lot of kombucha. As Nate Silver points out in On the Edge (a book I discussed in TR in August, 2024), a16z’s reputation helps it recruit top founders, leading to a positive feedback loop, which Andreessen tells Silver is “sort of a self-fulfilling prophesy.”

A16z made its first real splash with the Aug. 20, 2011 publication of Marc Andreessen’s essay “Why software is eating the world,” advancing the thesis that most every business was going to become a software business. This thesis proved both resonant and prescient. It positioned A16z as the VC firm that seemed to understand and could explain where technology was headed. 

On Apr. 18, 2020, in the midst of the pandemic, Andreessen’s effort to follow this up with a new call to action, “It’s time to build,” seemed to fall comparatively flat. 

Three years later, Oct. 16, 2023, Andreessen attracted considerable attention with his publication of the “Techno-optimist manifesto,” advancing his perspective that technology makes life better for humanity, so let’s not impede this progress with ignorant regulation (my reaction in TR in October of 2023 is here).

Marc Andreesen

In July 2024 Andreessen and firm co-founder Ben Horowitz, “both longtime Democratic givers…stunned the tech world” by endorsing Trump, the New Yorker’s Susan Glasser reported, adding that Horowitz subsequently announced “a significant donation” to the Harris campaign. In recent months, Andreessen has spent time with the President, seeking to influence national priorities on a range of technology and economic issues.

What does this have to do with biotech and healthcare? A16z has an abiding interest in biomedicine, represented by their “Bio+Health” vertical, which seeks to introduce tech innovation into these sectors, based on the firm’s tacit (and at times, not so tacit) conviction that they understand tech, and the future of tech, better than anyone. 

In early January 2025, Eli Lilly and A16z announced the establishment of a $500M “Biotech Ecosystem Venture Fund,” paid for by Lilly (thank you, Zepbound…), co-managed by both organizations, and focused on what A16z Bio & Health partner Vineeta Agarwala describes as “bleeding-edge technology,” Stat’s Matthew Herper reports.

Vineeta Agarwala, general partner, A16Z Bio & Health

In keeping with A16z’s pursuit of thought leadership, the firm offers many (many) podcast episodes focused on the intersection of technology and health.  Occasionally, these can feel like efforts to improve healthcare through the earnest application of tech analogies – the term “full stack” makes an appearance in nearly every episode.  Most of the time, however, these discussions are engaging and informative – and never more so than when Andreessen himself is featured.

One of the more thoughtful conversations I’ve heard about AI and health emerged from recent A16z podcast (imperfect transcript here) featuring Andreesen, who was joined by Bio+Health general partners Vijay Pande and Julie Yoo. Their discussion topic – “Can Tech Finally Fix Healthcare?” – could have been cribbed from the title of the 2013 book Lisa Suennen and I wrote, “Tech Tonics: Can passionate entrepreneurs heal healthcare with technology?”

To be sure, listening to the three tech VCs discuss solutions to healthcare woes inevitably evokes the famous SNL “Bill Swerski’s Super Fans” sketches (“Coach Ditka versus a hurricane: who would win?” “Ditka! Ditka!”) except that instead of Ditka, the response is invariably “AI!” 

Reflexive embrace of AI aside, the discussion touches upon several themes of likely interest to TR readers:

How AI enters health: The route “might not be tools,” Andreessen suggests, but rather “almost like the equivalent of hiring workers, full stack.” (Buzz!)

Yoo agrees. “The allocation of revenue within health care enterprises that goes towards technology or IT, as they would call it, has been an order of magnitude smaller in health care than other peer industries,” she points out, adding that AI is increasingly “packaged” or conceptualized as “labor units,” raising the possibility of tapping into the much larger HR budgets at healthcare organizations, rather than the IT budgets.

In health systems, Pande suggests, AI might start with “subclinical nursing and primary care. Then inching into clinical primary care, I think, would not be that crazy to imagine. Essentially, AI could be a great router.”

Vijay Pande, general partner, A16z Bio & Health

He continues, “especially if you think about what a primary care physician has to do, they have to ingest all this data and make a diagnosis and then send to a specialist. That’s increasingly literally becoming a data science problem.”

Where AI might struggle: Andreessen highlights “Morevac’s paradox,” which I sometimes think of as the technology version of the classic Gilligan’s Island joke: “What’s the deal with the professor – he can figure out how to turn a coconut into a radio but he can’t fix a hole in a boat?”

Look at technologies like ChatGPT, Andreessen says.

“They will paint art for you. They will compose music for you. They will debate, like, abstract philosophy for you. They will explain quantum physics to you, but they can’t pack your suitcase. They can’t clean your toilet, they can’t cook you lunch. They can’t do anything that a normal person operating in the world can do.”

He adds, “The more abstract, intellectual, knowledge-driven, data-driven, the task, the easier it is to get the AI to do it. The more applied, the physical, messy, unpredictable, the sort of all the human elements are probably the hardest thing.” 

(This may be an opportune time to point out that that the most challenging – and rewarding — parts of medicine involve these pesky “human elements,” and incidentally, nowhere is this more true than in primary care.)

Pande notes that a challenge for AI in the physical world is that “it has nothing to learn from,” in contrast to the digital world. 

Andreesen offers that the “Tesla self-driving car might be the reason for optimism here.” He points out that Tesla:

“tried different approaches to AI, and it turned out the thing that worked was basically put a neural network in the wild, embodied in the form of a car, and in fact, embodied in the form of a million cars, and then let those cars drive around and collect the data and learn about reality.”

He adds, “The more you take the rules out of the system, and the more you just expose it to the real world and let it gather the data and let it build up the neural network, the better it gets at self-driving.”

Big picture considerations: Andreessen places healthcare in a select group of industries, that also include education, housing, and law/government, that he says exhibit flat or negative productivity growth – we’re doing less with more, rather than more is less. 

In healthcare, specifically, he asks how is it that “we have some of the best doctors in the world.  We have the best technology in the world.  We pay the most and we have the worst outcomes. How is that possible?” (I’ve recently discussed this disconcerting paradox in The Bulwark, see here.) 

The fundamental culprit in all four problematic domains, Andreessen believes, is the combination of constrained supply (due in large part to excessive regulation, he says) and subsidized demand. 

“The political system is totally unable to deal” with this challenge, Andreesen argues, concluding (wait for it…), the answer “has to come from the private sector, and it has to come from the introduction of disruptive technologies.”

He points to television sets as a “case study in the opposite direction,” an example of what can happen when the markets are allowed to work, and technology is liberated. 

“The price of television sets has crashed as the quality has exploded,” he says. “You’re going to have a flat panel TV and 32K resolution that’s going to cover your whole wall. It’s going to cost $100, but yet it’s going to cost you a million dollars to send your kid to college.”

Enhancing the agency of healthcare consumers: Andreessen argues that “in healthcare from here on out … the existing system, left to its own devices, is going to degrade further and further. It’s going to give worse and worse results, at higher and higher cost over time. As a consequence, some percentage of people are going to try to break out of that.” 

This creates an opportunity, he believes, for companies that meaningfully help patients take control of their health and give them enhanced agency.

(As I will discuss in Part III, I couldn’t agree more strongly with the emphasis on agency, the contributions of agency to health, and the opportunities for technologies to enhance agency and sustain or improve health.)

Yoo points to the emergence of agency-enhancing technologies that are “totally dislocating the price curve.”

Pande then offers what I found to be the most resonant observation of the entire discussion:

“What we’re really providing patients is agency … this sense of agency is starting to really grow. Where people have this ability to monitor their health and then do something about it and then repeat. And that cycle, actually, I think, works for a lot of people. And being in control of your health feels very different than being at the mercy of a system.”

Thinking About Change. Citing Amara’s Law, Andreesen explains that “changes in technology take a lot longer to happen than you think they will, but when they happen, they have much more consequence than you think. They’re much more dramatic than you think.” (I discussed the arc of technology adoption in TR, here in June 2023.)

Andreesen notes that doctors have been famously frustrated by patients coming in with printouts from Google searches, and says this phenomenon is only going to grow, as patients have more sources of information. Not everything they dig up will be valid, he acknowledges, but notes “there are going to be things that actually work,” and these will spread.

(These sentiments, aligned with Pande’s focus on technology’s ability to enhance patient agency, have been strongly echoed by such leading lights as Carey Goldberg and Zak Kohane, who have emphasized (as discussed in TR in August, 2023) the opportunities generative AI has created for patient empowerment. We will return to the theme of agency in Part III of this series.)

Julie Yoo, general partner, A16Z Bio & Health

Yoo notes that physicians are also leveraging emerging technologies, citing social media as one example. (OpenEvidence, an AI tool I discussed in TR in October, 2024) stands out as well.)

The bottom line, Andreesen argues, is that while the talking heads may debate whether “a new technology is good or bad, and should it be adopted or not, those are all beside the point. Because the fact is, young people are just going to use what’s helpful and useful and they’re not going to have the emotional reaction. And I think that that will apply to many of the things that we’ve been talking about.”

Andreessen’s point about the adoption of technology is correct, though it’s hardly confined to the young (an enduring bias of some of Silicon Valley’s most experienced leaders; hopefully more will consider the data presented in books such as Ali Tamaseb’s Super Founders, as discussed in TR here in April 2021). 

Practitioners of all ages are astutely attuned to new approaches that offer palpable benefit, particularly once they see colleagues productively utilizing these tools. The rapid adoption of non-invasive prenatal testing is one example; the recent embrace of OpenEvidence is another (I’ve reviewed both in TR, here in October 2024).

Continue to: The Future of AI and Health, Part III: Improving Health By Enhancing Agency

2
Feb
2025

The Future of AI and Health, Part I: Forecasts Reveals Little Consensus

David Shaywitz

The likely impact of AI on health and medicine is … highly dependent on who you ask.

Consider the spectacularly wide range of opinions offered in just the last several weeks.

A $500 billion AI project, dubbed “Stargate,” was announced with great fanfare on January 21 in the Roosevelt room of the White House by President Trump. He was flanked by Masayoshi Son, CEO of SoftBank; Larry Ellison, chairman of Oracle; and Sam Altman, CEO of OpenAI.   

Stargate, according to OpenAI, is “a new company which intends to invest $500 billion over the next four years building new AI infrastructure for OpenAI in the United States.”  The “key initial technology partners” are Arm, Microsoft, NVIDIA, Oracle, and OpenAI.

Altman touted the promise of AI in healthcare.

“We will see diseases get cured at an unprecedented rate,” he said.  “We will be amazed at how quickly we’re curing this cancer and that one and heart disease. And what this will do for the ability… to cure the diseases at a rapid, rapid rate, I think, will be among the most important things this technology does.”

Ellison highlighted the possibility of an mRNA cancer vaccine. 

“You can do early cancer detection with a blood test,” he explained, “and using AI to look at the blood test, you can find the cancers that are actually seriously threatening the person. You can make that vaccine, that mRNA vaccine, you can make that robotically, again using AI, in about 48 hours.”

Oncologist and gadfly Vinay Prasad, for one, wasn’t buying this.  “AI will do a lot of good things. But it won’t cure cancer,” he said on X. One problem, he argues, is that AI’s ability to inhale all published literature won’t help it sort through the vast amount of fraudulent or irreproducible work.

Another problem he perceptively highlights is “biology itself” – that is, “understanding what is happening in the cell that has not been seen or detected in current experiments. AI has no way to do this unless it again picks up a pipette.”

Derek Lowe

Grizzled pharma veteran Derek Lowe is similarly skeptical. Writing in Chemistry World, he argues that even if AI can help at the earliest stages of the drug discovery process, it “gives you a speedup in the earliest and least expensive part of the whole process, one that is often as not the shortest as well. Unfortunately, that’s not quite the material of a revolution.”

He continues,

“Compounds found (wholly or partly) by such AI methods are still going to be subject to the same white-knuckle dice-rolling as all the others when they get into human trials, because we have (as yet) no computational tools that really help us predict whether we have picked the right target, the right disease, the right biochemical pathway, or the right compound to affect it without doing anything unexpected along the way. When AI systems start to help with those questions, the revolution may really be at hand. But as it stands, some of the current press releases sound like someone trying to sell a new car model by pointing out that its windows roll up and down much more quickly than the competition.”

Lowe’s hesitations are shared by Andreas Bender, an AI expert with big pharma experience who has since transitioned to academia. As I discussed in TR in October 2022, Bender worries, essentially, that AI is solving stylized, reduced problems, which lead to publishable papers but may not be especially applicable to the challenges of real-world R&D.

Another experienced drug developer, Regeneron’s legendary chief scientific officer, George Yancopolous (a favorite of this column – see this April 2021 discussion) also thinks the promise of AI has been wildly overblown.

George Yancopoulos, president and chief scientist, Regeneron Pharmaceuticals

“There’s no miracles coming from stem cells and AI,” Yancopoulos told Andrew Dunn of Endpoints News.

Yancopoulus offered a visceral response to the term itself, Dunn reports:

“I just get a reaction to even the name ‘AI.’ There is no ‘I’ in AI,” Yancopoulos said last week in an interview at the JP Morgan Healthcare Conference. “It’s all about machine learning, even this generative AI stuff. We use machine learning and these approaches as much as anybody, but we understand what it can give you and what it can’t give you.

“The hype in these stages is just greatly exaggerated compared to the reality,” he added.

Yancopoulus, Dunn says, called the awarding of the 2024 Nobel Prize in Chemistry to the developers of Google DeepMind’s developers of AlphaFold “the stupidest thing I’ve ever heard.”  (The prize was shared with University of Washington biochemist David Baker, for his work on computational protein design.)

Yancopoulus says he appreciates the pattern recognition capabilities of AI/ML and hopes to turn these technologies loose on ever-larger integrated datasets comprising genetics, medical records, and proteomics, as they are doing now in partnership with the UK BioBank, and aspire to do the same in the United States.

“Our dream is to then get to 50 million [integrated data sets] and then to the entire US population,” he said. “We’re very willing to work with whoever wants to help on this, because I think this is an incredible resource.”

Historically, the issue hasn’t been so much potential scientific value of such a rich and integrated dataset, but rather the challenge of assembling it, particularly given privacy concerns and the highly siloed nature of medical data, data that patients nominally have the right to but often struggle to access easily. 

The tendency to gear EHR data to maximize billing may also get in the way. The rigorous and thorough protocols that patients (at least ideally) go through to enroll in a clinical study can differ significantly from the way patient conditions are documented in routine clinical practice – a discrepancy that healthcare leaders like Amy Abernethy, in particular, are striving to eliminate.

Subha Madhavan

Yet another perspective on AI in pharma can be found (like Bender’s pivotal work) in Drug Discovery Today (here), co-authored by Pfizer’s brilliant data scientist Subha Madhavan and me.  We offer a cautiously optimistic take and focus on the application of AI to clinical development.

We argue that “the most vexing challenge facing drug developers – as well as our most significant opportunity – is managing the exploding complexity at every stage of the drug development process,” and explain that “these hurdles are the direct result of biomedicine’s remarkable success and accelerating progress.”

AI, we suggest, can help drug developers manage this burgeoning complexity, and we offer a range of early, promising examples from manufacturing to document management to trial design. 

We also emphasize the changes in “ways of working” that are likely to be headed our way, highlighting the need to reinvent workflows (as discussed in TR here in June 2023).  We envision approaches to drug development that are “less siloed and more collaborative,” involving “shared comprehensive and timely data (enabled by AI), as well as common analytics and visualization dashboards.” (The value of such dashboard during the development of COVID vaccines was discussed in TR here in May 2022.)  

Read Part II: The Future of AI and Health, Part II: Andreessen and Colleagues Weigh In

27
Jan
2025

Looking at Live Cells and How They Interact at Scale: Mostafa Ronaghi on The Long Run

Mostafa Ronaghi is today’s guest on The Long Run.

He is the co-founder and an executive board member at Foster City, Calif.-based Cellanome.

Mostafa Ronaghi, co-founder and executive board member, Cellanome

Mostafa is a molecular biologist and technology developer. He is an inventor of pyrosequencing methods for DNA sequencing, and is best known for his work as chief technology officer at Illumina during its glory days from 2008-2021.

If the early part of his career was about developing technologies to help us sequence more and more genomes that shed light on health and disease, the current chapter is about moving beyond the underlying DNA code. This is about capturing large sets of data from cells, the fundamental unit where the instructions of life play out. Cellanome is developing technology to study live cells at scale, helping biologists understand how cells behave differently in reaction to certain stimuli. The idea is to do this with the fine-grain resolution of single cells, but at high-speed and high volume.

The company has been operating quietly for the past four years, and has recently begun talking a bit more publicly about what it’s doing at scientific conferences. Cellanome raised $150 million in a Series B financing in January 2024.  

In this conversation, we cover Mostafa’s early life growing in Iran during war time. He left to get his scientific training in Sweden and got early exposure to the slow, hands-on methods of Sanger sequencing before tools of automation became widely available. He has clearly overcome some big obstacles in life, and is undaunted by the challenge of scaling up cell biology way beyond where it has been in the past.  

Please join me and Mostafa Ronaghi on The Long Run.

22
Jan
2025

Party Like It’s 2015: Celebrate the 10th Anniversary of Timmerman Report

Luke Timmerman, founder & editor, Timmerman Report

The Timmerman Report is gearing up for the 10th Anniversary.

Time to Party!

Join a stellar cast of biotech leaders at the TR10 East Coast Party. This free and fun event will celebrate the 10th anniversary of Timmerman Report. Don’t miss the toasts and roasts of TR Founder Luke Timmerman. Listen for a few predictions about the next 10 years of biotech innovation. Enjoy music, drinks, and good company.

See you there Mar. 6 at Alnylam Pharmaceuticals headquarters in Cambridge, Mass.

REGISTER HERE

TR10 East Coast Party

Toasts / Roasts / Predictions.

  • Vicki Sato, board chair, Denali Therapeutics, VIR Biotechnology
  • John Maraganore, founding CEO, Alnylam Pharmaceuticals
  • David Schenkein, general partner, GV
  • Andy Plump, president of R&D, Takeda Pharmaceuticals
  • Katrine Bosley, founding CEO, DaCapo BrainScience
  • Jeremy Levin, CEO, Ovid Therapeutics
  • Roger Longman, chairman, Real Endpoints
  • Abe Ceesay, CEO, Rapport Therapeutics
  • Reid Huber, partner, Third Rock Ventures
  • Alex Harding, entrepreneur-in-residence, Atlas Venture; TR correspondent
  • Jeb Keiper, CEO, Nimbus Therapeutics
  • Katherine Andersen, head of life science and healthcare, HSBC USA Commercial Banking
  • Christine Lindenboom, chief communications officer, Alnylam Pharmaceuticals
  • David Shaywitz, biopharma R&D executive; TR healthtech columnist
  • Rosana Kapeller, CEO, Rome Therapeutics
  • Julie Sunderland, board member, Variant Bio, eGenesis, Horizon Surgical Systems

TR10 West Coast Party

Join a stellar cast of biotech leaders at the TR10 West Coast Party. This free and fun event will celebrate the 10th anniversary of Timmerman Report. Don’t miss the toasts and roasts of TR Founder Luke Timmerman. Listen for a few predictions about the next 10 years of biotech innovation. Enjoy music, drinks, and good company.

See you there Mar. 13 at Adaptive Biotechnologies in Seattle.

REGISTER HERE

Toasts / Roasts / Predictions.

  • Thong Le, investment director, managing partner of Strategic Investment Fund, Gates Foundation; chairman, Accelerator Life Science Partners
  • Bob More, managing director, Alta Partners
  • Jim Olson, professor & director, Invent@Seattle Children’s Postdoctoral Scholars Program
  • Sam Blackman, co-founder, Day One Biopharma
  • Brad Loncar, founder, BiotechTV
  • Andrew Farnum, co-founder and CEO, Variant Bio
  • Aaron Ring, associate professor, Fred Hutch
  • Andrew Dervan, co-founder and co-CEO, Cajal Neuroscience
  • Cliff Stocks, CEO, OncoResponse
  • Andy Scharenberg, co-founder and CEO, Umoja Biopharma
  • Tae Han, co-founder, ProfoundBio
  • Lesley Stolz, VP, early innovation partnering, J&J Innovation
  • Bill Newell, CEO, Sutro Biopharma
  • David Younger, co-founder and CEO, A-Alpha Bio
  • Kelly O’Brien, chief philanthropy officer, Fred Hutch
20
Jan
2025

Pfizer’s Oxbryta Was Transformational For My Sickle Cell Warriors. Bring it Back

Mapillar Dahn, founder, MTS Sickle Cell Foundation

Following Pfizer’s voluntary withdrawal of Oxbryta from the global market, a mother of three daughters battling sickle cell disease shares why patients need it as a therapeutic option.

The headline rocked our family to the core.

At 5 pm ET, Sept. 25, 2024, the statement read: “Pfizer Voluntarily Withdraws All Lots of Sickle Cell Disease Treatment OXBRYTA® (voxelotor) From Worldwide Markets.”

This pulled the rug out from under the global sickle cell disease community. We did not see it coming. We weren’t ready for the chaos that ensued.

Oxbryta was the only disease modifying therapy for sickle cell disease that actually worked for my oldest daughter Tully. She’s a college student, and the drug offered her hope for a bright future, free of pain crises. Breaking the news to her, that she could no longer have access to Oxbryta, was one of the hardest things I’ve had to do as a mother.  

The day started out beautifully. I had just landed at home in Atlanta after joining other patient advocates in Washington for the Sickle Cell Disease Summit. It was a first-of-its-kind event organized by the US Department of Health and Human Services to highlight progress in research, care, and cures. I was on an emotional high, more hopeful and optimistic than ever about the future of my daughters and all people living with this dreadful disease.

The swing from high to low sent a shock through my system that I still haven’t recovered from nearly four months later. It is a numb sensation that continues to permeate my body.

At first, I was stunned, broken, and saddened. There was no time to process feelings of shock and grief. Instantly, a barrage of messages started coming in from other caregivers, patients, and community members.

“How is this even happening?”

“Are you OK?”

“Do we just stop taking the drug?”

Great questions. I did not have the answers. Pfizer’s announcement was vague, leaving room for a host of interpretations. No guidance was provided on how to go about stopping the therapy. Those questions went to doctors and community leaders.

No one knew what to do.

This loss felt personal.

Prior to the FDA approving Oxbryta in November 2019, hydroxyurea was the only drug on the market for sickle cell disease. It offers a marginal benefit for some but provides no real clinical benefit for almost half of patients. As a mother of three daughters who all suffer from sickle cell disease, I was painfully aware that one medication on the market is nowhere near enough. Millions of patients around the world are suffering and need more treatment options. Patients have long been neglected, and that’s a great injustice.

So, when Oxbryta came along, I fought for it. It wouldn’t have mattered if it worked for my daughters or not. This was a fight of principle. I fought for the right of my children and all patients to have therapeutic options. I fought knowing that, like all medications, Oxbryta will work for some and wouldn’t work for others.

I painted the picture of three sisters — ages 15, 14, and 10 at the time — being hammered by an unpredictable disease that has no boundaries of the types of havoc it wreaks. I shared our challenges with pain crises, a stroke, too many hospitalizations to count, over 10 surgeries, stigma, acute chest syndrome, monthly blood transfusions, jaundice, and so much more.

Before my oldest daughter Tully started taking Oxbryta, she suffered from chronic fatigue, hemoglobin that tethered between mid-6 to low-7 grams per deciliter of blood (normal is 11.5-15 g/dl). Her immune system develops antibodies against the donor blood she’s given, making it difficult and dangerous for her to be transfused.

Oxbryta raised her hemoglobin level, making it less likely for her to need a transfusion. Now, if her hemoglobin drops suddenly, or she needs a higher level for a procedure requiring anesthesia, she will not have Oxbryta to help her. She will instead get daily injections of erythropoietin to try to stimulate her already overworked bone marrow to make more red cells, a painful treatment that is far less safe and effective than Oxbryta. About one in five people with sickle cell disease are hard to transfuse safely and are in the same situation as Tully.

My daughter’s life was shaken by the withdrawal of Oxbryta. She went to the emergency room for a pain crisis three or four times a year when she was on the drug. When the drug was taken away, in the first month, she had to go to the ER every single week.

There is never a good time to need emergency care; however what breaks my heart even more is that this happened during a time when hospitals were out of IV fluids. When the hospitals were forced to ration what little supplies they had, sickle cell patients were unable to get access to these vital fluids. Sickle cell patients like my daughter who were seeking emergency care because of pain were only receiving strong opioids.

Tully missed a lot of school and lost a lot of weight. She is back to being chronically fatigued, jaundiced, with low hemoglobin.

She and many patients who relied on Oxbryta are back to living life without any disease modifying therapy that works for them. In fact, they are back to being defenseless against a monstrous disease that is systematically damaging their organs.

That is not OK.

When Pfizer acquired Global Blood Therapeutics (GBT), the company that developed Oxbryta, we all had concerns about what this meant for the future of sickle cell drug development. Pfizer, the world’s second largest pharmaceutical company, bought out a company that existed unapologetically for the advancement of sickle cell disease. We knew that GBT had other sickle cell compounds in the pipeline and were afraid that they might become a lower priority for development at a big company like Pfizer.

After all, Pfizer had left our community high and dry before, when it was unsuccessful in developing rivipansel to treat acute pain in sickle cell.

Even so, with all of our reservations, while we hated to see GBT go, we prayed that with Pfizer’s global reach, Oxbryta and the other therapies would reach parts of the world that are being hit the hardest by sickle cell disease, like sub-Saharan Africa, where 50-80% of children born with the disease die before their 5th birthday and upwards of 90% die before their 18th birthday.

Unfortunately, rather than making Oxbryta available to more individuals, Pfizer has taken it away from everyone. The reasons for this drastic decision have not been fully explained but appear to be related to risk in malaria endemic areas.

As a member of the sickle cell community, I am speaking for many when I say that we need this medication. We have only the small hope that on careful review with the FDA, Pfizer will do the right thing and reverse their voluntary withdrawal of Oxbryta.

13
Jan
2025

RNA Editing Medicines: Ram Aiyar on The Long Run

Ram Aiyar is today’s guest on The Long Run.

Ram is the CEO of Cambridge, Mass.-based Korro Bio. The company is developing medicines that edit RNA, instead of DNA, which more people have heard about.

Ram Aiyar, CEO, Korro Bio

Previously, Ram co-founded Corvidia Therapeutics and served on the management team up through its $2.1 billion acquisition by Novo Nordisk. He’s had a long and interesting set of experiences in science, large pharma, venture capital, and startups.

In this conversation, we cover Ram’s career journey and how it’s led him to this moment when it’s possible to develop drugs that can precisely intervene with underlying disease processes, at the level of RNA, and be re-dosed conveniently for patients who may or may not be good candidates for a DNA-editing treatment of the future.  

Please join me and Ram Aiyar on The Long Run.

13
Jan
2025

Moving from Biotech to Nature

Kaja Wasik, co-founder, former chief scientific officer, Variant Bio

Everything started with my love for animals.

I studied biology and journalism at the University of Warsaw — science because I loved nature, and journalism because I believed it would be my escape from the confines of post-communist Poland.

I yearned to explore the world with friends, and did a variety of jobs – waiting tables, gorilla zookeeping, blackjack dealing – to scrape together cash for travel. Each trip would inevitably end with me in the emergency room waiting for a rabies shot after feeding an overzealous stray dog or cat. My dream of being a foreign correspondent was not to be. Science carried me across the oceans.

After completing my PhD at Cold Spring Harbor Laboratory in New York, I moved to the New York Genome Center and spun up my first company, Gencove. That company democratized genomic access by focusing on computation combined with low-coverage sequencing to make novel genomic discoveries at a fraction of the cost of previous methods.

But I wanted to do something that combined my love of the world, ethical sensibilities, and desire to do groundbreaking science. Over cocktails in a New York City bar, one of my best friends and a brilliant geneticist, Stephane Castel, and I came up with a concept that became Variant Bio.

Medicines Based on Diverse Genomes

Variant was inspired by methods from population genetics that pushed the boundaries of imagination on population-wide approaches to new drug target discovery.

Variant Bio was met with skepticism by many who thought it was too risky. We partnered with diverse populations around the world who harnessed unusual genetic or epidemiological traits. We sequenced their genomes and performed deep phenotyping to identify single genetic variants with strong effects that point to ideas for novel therapeutics for common diseases across humanity.

The company, founded in 2018, has delivered on this concept. It now has five therapeutics programs in preclinical development for kidney disease, fibrosis, and inflammation-immunology.

What I am most proud of, however, is Variant’s paradigm-shifting approach to engagement and benefit sharing with our partner communities. These are often vulnerable groups, overlooked by science and not reaping its benefits. Many are naturally wary of collaborating with scientists from abroad, given the long history of colonial exploitation.

Variant sought to overcome this challenge by creating a new kind of discovery partnership. We committed to sharing 4% of our revenue in perpetuity and are about to deliver on that promise for the first time. The company just announced a $50 million partnership with Novo Nordisk, which is Variant’s first revenue. This is a great—and still rare—example of completing the circle, delivering financial benefits to the original research contributors.

Seeking New Challenges in Africa

I left my job as chief scientific officer of Variant Bio in September 2023. Five years at Variant reminded me that nature and human health are interconnected—there are no healthy communities without healthy ecosystems. I had spent a lot of time in the office and in the usual business settings. It was time to fall back in love with nature.

In September 2023, I ignored everyone who said it was crazy, gave my ski boots and paddleboard to Stephane, and moved from Seattle to Kenya. That was the first country that I ever visited outside of Europe. It was home to my godfather, an economist and a Kikuyu community member. My journey resembled a small-scale Noah’s Ark, including three stops and my dog, Lulu, and my cat, Chairman Meow.

Kaja and Lulu in Kenya

Ten days later, I woke up in a conservancy that I would call home. Elephants regularly broke through the fence. Hungry baboons stole the leeks in the vegetable garden. A black mamba, one of the world’s deadliest snakes, lurked around the house. In case of a bite, I was told, pour a whiskey to enjoy for a half hour before you die.

Humans live close to nature in this part of the world. Time moves differently. (Unfortunately, Chairman Meow was somewhat under-par and went out in a blaze of glory. After the best year of his life, at the ripe age of 14, he came face to face with his much larger cousin. Chairman was as feisty as his namesake, but a leopard is a leopard. Lulu is doing well. She was always the more sensible one.)

I wanted this after years of the fast life as a biotech executive. At least for a while. I found new work in Kenya to create ways of securing and financing the planet’s most essential, yet often ignored, infrastructure: nature itself.

Finding Balance Between Humans and Nature

I’ve worked on two projects that feel like extensions of my work in biotech, albeit through a new lens. I started the Tehanu Foundation, that builds on recent advances in blockchain and AI to create an economy for a beloved and threatened species – mountain gorillas in Rwanda.

Here’s how it works. Rwandan gorillas get digital identities and wallets. Through expert knowledge and artificial intelligence, these “financially empowered” gorillas gain access to resources they need. (Think food, water, shelter, and peaceful territory to roam without too much human encroachment).

The gorillas now have a capacity to better communicate what they need and want, which hopefully will help their populations grow, rather than dwindle. This is a new model for integration of nature into human economies and for building a more equitable future, Tehanu is also a flagbearer for the UN Sustainable Development Goal for “Life on Land”, a finalist for the 2024 XPRIZE Rainforest, and selected by The Economist as a promising technology for 2025.

Kaja training Rwandan Volcano National Park rangers in environmental DNA collection.

I also spent time working with Natural State, a nature restoration-focused NGO. Here, I got the opportunity to experiment with creating standardized metrics of ecosystem health. This work mirrors genetic analysis techniques. We rely on large amounts of robust and unstructured sound and visual data to evaluate landscapes without the painstaking need for species-specific annotations. To understand the health of an ecosystem, we don’t need to completely understand it — we only need a useful representation.

All of this work culminated in creating “Echo.” Echo draws from both Natural State and Tehanu. It combines scientific rigor with aligned economic incentives and ecological stewardship. Echo is still in stealth, but I have high hopes.

This “biotech sabbatical” has been an eye-opening experience of learning that humans urgently need to reconnect with nature.

Basic Health Gaps

Life in East Africa has come with a few lessons about health economies. While the US is leaping ahead in personalized medicine, and biology is becoming engineering,

A woman named Stella recently collapsed outside my house, and I helped rush her to the hospital. She had been living with undiagnosed diabetes and hadn’t seen a doctor in 15 years. She is now receiving treatment but was not familiar with the concept of routine health screenings.

Three years ago, the major health concern in Kenya would have still been malaria, HIV, or tuberculosis, but now those have been overshadowed by non-communicable diseases. Diabetes has become the biggest health challenge in Kenya, according to Stella’s doctor.

In other ways, healthcare in Kenya shines. After a recent bite, I once again needed a rabies shot. Seven minutes later, I paid $9 USD and felt invigorated antibodies cruising a familiar course through my veins.

A complete rabies course requires five shots within a few weeks, and sometimes that interferes with international travel. Needing another shot back in the US at Princeton University, I believed this would be fast and easy. Wrong. After being turned down again and again, I found myself staring at a $3,000 USD bill from Princeton Hospital ER. Something’s gone off the rails with access to medical basics in the US.

Coming Home for What’s Next

Soon it will be time to come home. For me, this time away hasn’t been about retreating. It’s more about reaffirming my most important driving forces: working on unconventional ideas, challenging norms, and supporting a strong mission.

I anticipate a lot of failures. Mistakes are inevitable if you want to try something never done before. Sometimes, you need to step out of the lab, or the office, or the continent — to see the bigger picture. Whether it’s delivering medicines to underserved communities or empowering gorillas with digital wallets, my goal is the same: to create systems that benefit everyone — human and non-human alike.

There’s a lot of work to do.

9
Jan
2025

Australia’s Little-Known Biotech Advantages and Risks

Daniel Getts, co-founder and CEO, Myeloid Therapeutics

Most US biotech entrepreneurs and investors don’t consider Australia a thriving global hub. But there are compelling reasons to take another look at what’s happening there now.

Australia has become more attractive based on its willingness to allow fast, affordable clinical trials to help early-stage developers gather human data on new drug candidates. That low-cost, high-speed, high-quality early development capability allows for capital efficiency and amplified returns on venture investments.

In the early 2000’s, the Australian Government and industry leaders sought to create a favorable climate for biotech.  A quarter of a century later, those efforts are paying off. The Government offers a comprehensive regulatory framework, substantial incentives, and supports world-class research. 

The pro-growth business environment in Australia enabled Cambridge, Mass.-based Myeloid Therapeutics (TR coverage, Jan. 2021) to initiate the first ever application of in vivo mRNA CAR development candidates into clinical trials, for advanced epithelial tumors and hepatocellular carcinoma, respectively.

As an Australian by birth, this advance is meaningful to me. I finished my PhD research at the University of Sydney but departed for the greener innovation pastures in the United States. I became an American citizen and US-based biotech repeat-entrepreneur. It is particularly fulfilling to see Australia build its relevance in the biotech world anchored by major coastal US cities. I see the strengths of the US and Australian operating models and continually reflect on how we can work together to accomplish more.

Opportunities for American Biotech in Australia

Regulatory Advantages

Australia’s regulatory environment, spearheaded by the Therapeutic Goods Administration (TGA) is renowned for its efficiency and scientific rigor. This enables clinical trials to be initiated earlier than in other countries, based in part on a rational safety assessment. It often takes multiple years to move from concept to the clinic In the US. In the case of Myeloid, the Australian system allowed us to move from a white-board product concept to human clinical testing in eight months. 

The TGA is generally viewed as more open to collaborating with scientific entrepreneurs. Within the past five years, Australia’s streamlined process has made the country an attractive destination for early-stage clinical trials, particularly for companies focused on innovative advanced therapies, such as CAR-mRNA constructs and other cell and gene therapies.

Generous R&D Incentives

The Australian Government supports entrepreneurship through its R&D Tax Incentive program, which annually reimburses up to 43.5% of eligible research expenditures. This reimbursement can significantly lower the cost of early-phase trials, a key consideration for U.S. biotech companies operating in a capital-intensive, high-risk environment.

World-Class Infrastructure

Australia boasts a well-established network of research institutions with a proud history of scientific innovation and established clinical trial networks. In the progression of Myeloid Therapeutics, this infrastructure enabled rapid progression of its CAR-mRNA and myeloid-targeted therapies into the clinic. Getting to the clinic faster means collecting human data faster, getting the answers executives and investors want to see with less capital committed, so we can ultimately get the therapies to the patients faster.

Moving to a lower-cost environment doesn’t necessarily mean it’s lower-quality. Biotech companies have ready access to an excellent network of hospitals, and research universities such as The University of Sydney, University of Melbourne, University of New South Wales and University of Queensland. All regularly rank in the top 100 of world research universities. The Australians are justifiably proud of their operating setting and related mindset.

Gateway to Asia-Pacific

Australia is a member of the Five-Eyes strategic alliance — Australia, Canada, New Zealand, the United Kingdom, and the United States — all countries that ally and share national intelligence. This high degree of trust, at the senior levels of government, makes Australia a country well suited to the expectations of global investors. Australia has a much lower geopolitical investment risk than other parts of the world in 2025.

We see this as an important consideration as trade tensions between the US and China run high, despite the continuing progress of Chinese discovery candidates into global pharmaceutical pipelines.

Australia provides stable strategic access to the broader Asia-Pacific region. This region has 60 percent of the world’s population and a growing set of healthcare needs. US biotech companies can use Australia as a launchpad for expanding into large and growing markets like Japan, South Korea, and even to Taiwan or China, including for additional clinical development.

Beyond R&D to manufacturing advanced medicines

Recognition of the R&D tax breaks and fast regulatory framework in Australia prompted the Myeloid team to evaluate working in Australia. We saw an opportunity to expand further into GMP manufacturing.

In partnership with RNA Australia, a non-profit economic accelerator, and the NSW Government, Myeloid embarked on the design construction and development of Aurora Biosynthetics. Aurora is a novel private-public partnership focused on transforming the biotech ecosystem through advanced biologics manufacturing in Sydney. We expect it will bring significant investment opportunities to harness the Australian operating model described here.  

Challenges

There are risks to all investment, but after careful evaluation our team determined they are manageable risks.

Interstate Rivalries

Think California and Texas are fierce rivals? Or Ohio and Michigan? Try New South Wales and Victoria. Economic competition between Australian states is more intense here than in the US. It contributes to fragmentation that dilutes the labor pool, making it harder for companies to hire enough people.

Within the RNA therapeutics field, two states (Victoria and New South Wales) have designed separate “solutions” viewed as driving innovation and supporting drug development. Each state holds its own investment priorities.

New South Wales, with Sydney at the core, is focused on startups through mid-sized biotechs. Victoria, with an emphasis on working with well-capitalized publicly listed companies, has taken a different path.  Each path has innovation considerations. As entrepreneurs and company creators, we gravitated to NSW, where the emphasis is on building a local biotech ecosystem, that in turn will create broader network effects with global impact.

Australia’s land mass is vast, comparable to the contiguous United States. Yet the population is comparatively small — about 27 million. With a few urban centers attempting to become concentrated biotech economic zones, the main risk is spreading the talent pool too thin.

Talent Recruitment and Retention

Australia has a highly skilled workforce, but there’s no denying the magnetic pull of global biotech hubs Boston and San Francisco. There are reasons why so many talented Aussies emigrate to the US. Salaries can be lower in Australia. Career advancement opportunities are also fewer at this stage in the ecosystem’s maturation. Access to venture capital is more limited than in the major US biotech hubs. All of these factors make it harder to attract and retain top-tier local talent.

Development of advanced immunotherapies requires expertise in a range of disciplines, including translational research, regulatory strategy and affairs, and commercialization. As Australia continues to build up its biotech capabilities, it will attract some talented immigrants. Companies like Myeloid need to find a balance between developing talented local people and attracting people from elsewhere to move to Australia. This is a long-term strategy, but we have found it’s possible.

Geography

Australia is a long distance from major U.S. biotech hubs. It’s about a 14-hour flight from Sydney to San Francisco. This requires increased flexibility in collaboration and execution. Many parties have found a way to succeed by collaborating across wide geographies and time zones. But it also means that supply chain logistics require careful thought and increased reliance on local suppliers. This isn’t always easy for startups. Myeloid has learned to address local supply chain logistics and do so within cultural considerations on project teams.  

How to Succeed in Australia

Embrace Regulatory Benefits

Companies should prioritize leveraging the TGA’s efficiency to expedite timelines while using Australian trial results to support global regulatory submissions, including subsequent filings with the US Food and Drug Administration.

Leverage Tax Incentives

The R&D Tax Incentive can be a game-changer for companies managing tight budgets. Ensuring compliance with program requirements and working with local partners familiar with the system can maximize these benefits.

Collaborate Across State Lines

Rather than navigating interstate rivalries, ex-Australia parties including US companies can bring a collaborative mindset as an objective participant in economic growth. Myeloid Therapeutics continues to successfully build partnerships bridging research institutions and clinical sites across the Australian continent.

Invest in Talent Development

US companies can help deepen the talent pool by forming partnerships with Australian universities and advising on workforce training programs. Partnerships may include co-op programs. The Aurora Biosynthetics manufacturing site located at MacQuarie University, New South Wales, is one example of a co-op program where undergraduates can earn credit toward their degrees while gaining valuable career skills.

Companies can engage by guiding curriculum development and providing pro-bono mentoring to students, which Aurora does at The University of Technology, Sydney and The University of New South Wales.  

By investing in local talent, companies can build a long-term, skilled, and loyal workforce while reducing the risks of reliance on international hires and associated transfer costs. Offering competitive compensation and global career development opportunities can help to retain talent over the long term, creating a mutually beneficial situation for employees and employers.  

The Future for US Biotech Companies in Australia

With change as the only constant, investors will need to revisit established playbooks of company scaling and milestone attainment. As investors look to continue reaping high and higher returns on capital invested, American biotech operating managers need to re-evaluate their paths to bring new products to the global market.

The benefits outweigh the risks. It’s a good time to be building great biotech companies in Australia.  Looking forward to seeing you Down Under.  

8
Jan
2025

How the US Can Continue to Lead As China Rises

David Li, co-founder and CEO, Meliora Therapeutics

China made its intentions known 10 years ago. In the “Made in China 2025” plan, released in 2015, the government identified biopharmaceuticals as one of the industries where it sought a world leadership position.

The investment has paid off. By making biotech a top priority, the China biotech ecosystem is now thriving.

As we enter 2025, the strength of China’s biotech industry is evident. Across all modalities of therapeutics, but especially antibodies, T-cell engagers, ADCs, and small molecules, Chinese assets and companies are now competitive for leading the industry.

A foundation for its ascendant life sciences industry has been its R&D productivity, which has quickly moved to the front of the pack globally.

The rise in research productivity for China’s biotech industry has caused Large Pharma to take note. Sanofi, Pfizer, Novartis and numerous others have made significant investments.  

High R&D productivity has also yielded a relentless drumbeat of partnership announcements for assets licensed from Chinese biotechs to US biopharma and biotech companies.  

Landmark deals such as Summit x Akeso’s PD-1 / VEGF bispecific antibody, Roche x Regor’s CDK2/4 inhibitor, and Merck x Lanova’s bispecific antibody, another entrant into the PD-1/VEGF space, demonstrate that Chinese biotechs are no longer relegated to ranks of producing only me-too and fast-follower assets. These are potential first-in-class medicines that could dominate multi-billion-dollar product categories for many years.

Source: DealForma

Science Hubs Thriving in Shanghai and Suzhou

China biotech’s rise is one I have observed and needed to contend with firsthand. I serve as co-founder and CEO of a US precision oncology company, Meliora Therapeutics, based in Boston and San Francisco. We work on covalent allosteric small molecule drugs for breast cancer and other solid tumors.

Over the last 12-18 months, we started noticing that there seemed to be a Chinese competitor asset for every target we were exploring. M&A in the industry began slowing noticeably as Pharma buyers opted to license drug assets from China en masse – sometimes reaching multiple deals announced a week.

There were signs that we had reached a true tipping point in the industry in terms of R&D productivity and competitive landscape dynamics. We could no longer operate with the default assumption that US companies would be at the front of the pack.

To learn about what was actually happening on the ground, I spent time on the ground in Shanghai and Suzhou last month. I met many leading developers of small molecules, bispecific and trispecific antibodies, antibody-drug conjugates, and more. I toured their facilities.

What I saw would cause any biotech leader to sit up and take notice. I saw science parks many multiples larger than Kendall Square or South SF, filled with startups. Integrated biology, chemistry, biochem and structural biology, and vivarium labs were running at scale. Even smaller biotechs were running vivariums processing tens of thousands of in vivo mouse experiments monthly. Programs which went from standing start to registering for human clinical trials within 18 months(!) were not uncommon.

Speaking with the executives of local biotech leaders, I saw clinical development timelines which I estimate to be 50-100% faster than normal in the US or Europe. Depending on the novelty of the target, preclinical development timelines could be 100-200% faster than Western counterparts.  

The proof on the ground was difficult to ignore. My experience raised the question whether the steady flow of business development news out of China may actually still be *understating* the accelerated R&D pace and novelty of China’s biopharma firms. The deals we have seen the past year could just be a preview of more to come.

What are the implications of this massive shift in the global biotech industry?

China’s rise sets a new standard for R&D productivity in terms of time and cost. This creates competitive pressure around the world. Generally speaking, capital will flow to areas of highest productivity. As asset IP development and R&D execution becomes cheaper, the premium for target selection and novel biology advantages increases.  

This is true because Chinese biotechs, as fast as they are at execution, are often still limited in their understanding of the clinical and commercial value of different targets and programs in the Western market. This is understandable. Unless you have direct access to Western clinical key opinion leaders and understand the true treatment gap for patients in Western healthcare systems, being able to pick targets and target product molecule profiles is a very tall order.

Here is one place where US and European biotechs can continue to retain a comparative advantage.

Key point: In a world where R&D execution becomes ever more commoditized, novel scientific innovation is where the vast majority of the value creation in the therapeutics universe will accrue. American innovation should not cede its pole position.

How should American biopharma confront this change in the industry?

First, American biotechs should double down on its strengths in life sciences R&D. Exploring novel modalities of therapeutics to expand our drug toolkit, elucidating new underlying biological mechanisms to open up new therapeutic lines of attack against disease, and setting the global standard for converting translational / clinical trial insights into world class clinical patient care – these are the strengths US biotech must double down on as its unique advantages.  

Second, American biotech should recognize the realities of our current situation and engage and partner with Chinese biotechs to leverage their strengths. In my opinion, the days of directly competing with Chinese biotechs in R&D execution are over for many (and perhaps soon, most) modalities of therapeutics.  

Key point: Those who can pair best in world R&D execution with truly innovative and clinically meaningful biology hypotheses stand best positioned to garner capital, create more impactful medicines, and lead our industry.

What exactly does engaging and partnering with Chinese biotechs actually look like?

Here are a few directions US biopharma can take:

Ken Song, CEO, Candid Therapeutics

  1. License assets from Chinese partners after clinical de-risking in China (e.g. Summit x Akeso’s PD-1/VEGF bispecific antibody or ArriVent x Shanghai Allist’s EGFR inhibitor). Large pharma and numerous other groups are actively searching in this space, as it’s a fairly straightforward licensing structure. Future Chinese assets may not make it to late clinical stage before they are outlicensed to US / global firms.
  2. License preclinical or early clinical stage assets from a Chinese partner in order to help with clinical development. Candid Therapeutics is one example with multiple Chinese T-cell engager assets, and Hercules is another with multiple metabolic assets from Jiangsu Hengrui. In 2024, a number of these types of deals were announced as US venture capitalists began to explore earlier clinical stage pipelines from established Chinese biotech players. Aiolos Bio was one example of a company backed by US VCs with $245 million, with a TSLP-directed antibody from Jiangui Hengrui that was quickly acquired by GSK for more than $1 billion. (TR coverage). Interestingly, there are many more assets to comb through here in the China market.
  3. Form partnerships with China biotech companies to develop global IP for assets within a US umbrella newco. In this option, US firms can utilize their strengths in target discovery and target prioritization to guide the execution within a Chinese R&D organization and still retain IP rights outside China. However, execution is also difficult as close collaboration with Chinese biotech partners often requires on-the-ground presence and rare skills in navigating both US and China business culture.   

Surely, all three types (and other derivatives) will continue to happen as the industry evolves, but the bottom line remains the same — successful biotechs, whether American, Chinese, or something else, will need to unlock true innovation. Gone are the days of me-too or fast follower plays. Technical and clinical innovation are the only ways forward.

There is a path for American biopharma to continue leading as the intellectual powerhouse of the industry — but that likely means leveraging the best R&D execution abilities wherever they are globally.  

We owe it to American innovation to figure out what is that path. Patients, here and across the world, are waiting.

Investors, scientists, entrepreneurs, and policy makers interested in taking action on the significant opportunities ahead, feel free to message me on LinkedIn or X.com. I will also be at JPM conference in San Francisco.

6
Jan
2025

AI Needs Natural Language to Give Structure to Biology

Sam Rodriques, co-founder and CEO, FutureHouse

The word of the day, at least in the AI for Biology community, is foundation models. Everyone wants bigger data on more things to throw into bigger models.

Virtual cell models will enable us to predict how cell states will change in response to chemical perturbations. Protein language models will enable us to identify better enzymes for degrading plastics or protein binders that have more drug-like properties. These layers are on top of increasingly accessible genomic data. The future is bright.

Real biology discoveries look somewhat different, though, and I think it is telling that there are not many actual biologists at AI biology meetings like NeurIPS, a conference on Neural Information Processing Systems. which I attended last month in Vancouver BC.

Contrast these dreams of foundation models driving biological discovery with the latest table of contents from Science or Nature:

I struggle to imagine how any of these discoveries could fall out of a multimodal biology foundation model.

This is not intended to be a straw man argument. Surely, a foundation model could potentially identify the lncRNA from the first paper, but I am not sure how such a foundation model would associate it with chromatin remodeling.

A multimodal foundation model with enough data could also potentially identify metabolic changes associated with melanoma cells subjected to certain kinds of treatments, but I don’t see how that foundation model could identify the effect of those metabolites in preventing CD8+ T cell activation. Indeed, I do not think that any of the foundation models that are being developed today would be capable of generating rich new biological insights of the kind described in these papers. And yet, these are the kinds of insights that new therapies are made from.

The issue, I think, is that machine learning models work extremely well on structured data, and so all the foundation models that are being built are highly structured. Take a protein sequence as input and produce a protein sequence as output. Take a cell state and a chemical perturbation as input and produce a new cell state as output.

Biology, however, is poorly structured. The lncRNA insight is a good example: what structured representation can we use for the action of the lncRNA in modulating chromatin architecture? Protein models cannot represent it; DNA models cannot represent it; virtual cell models cannot represent it. Perhaps a model that incorporates RNA expression and 3D genome state could represent it, but then how would that model represent the lipid modulation of the monocytes?

I worry that every discovery may need its own representation space. Indeed, the nature of biology is such that there likely is no representation, short of an atomic-resolution real-space model of the entire organism, that is sufficient to represent the diversity of biological phenomena that are relevant for disease. Such a whole-organism model is far off – we still don’t have a computer model that fully represents the complexity of a single living cell.

Except, of course, for natural language, which has evolved to represent all concepts that humans are capable of contemplating. Indeed, I think natural language is ultimately unavoidable for discovery in biology, insofar as it is the only medium we know of that is sufficiently structured for machine learning and sufficiently flexible to represent the full diversity of biological concepts.

One way to combine language and biology is to use agents, like the ones we build at FutureHouse, a non-profit AI lab that I run in San Francisco. Language agents are language models – like ChatGPT – that can use literature search tools (e.g. PubMed), protein structure prediction tools (e.g. AlphaFold), DNA analysis tools (e.g. BLAST), and so on to analyze biological data in the same way humans do, but much faster and at much larger scale. We recently deployed an agent we built, PaperQA2, to search the literature and write an accurate and cited Wikipedia-style article for nearly every protein-coding gene in the human genome. In the future, language agents will be able to automatically analyze experimental data and clinical reports to provide detailed biological hypotheses similar to those in the Nature and Science papers above.

There are other ways to combine language and biology as well. Training models that combine natural language with protein, DNA, transcriptomics, and so on will also be extremely productive, provided the addition of the structured datatypes does not restrict their ability to represent unstructured concepts.

The history of biology is built on tools that we have found in nature to study biological phenomena. CRISPR is one powerful recent example. As all biologists know, trying to engineer things from scratch (almost) never works; what works is finding things in nature and repurposing them. It will be aesthetically pleasing if it turns out that our engineered representations are yet again insufficient for studying biology, and that good old natural language is simply another such tool that we have found in nature that must be applied to unravel the mysteries of biology.

2
Jan
2025

Investing in Biotech: David Schenkein on The Long Run

David Schenkein is today’s guest on The Long Run.

David is a general partner with GV. It’s the non-strategic corporate venture firm formerly known as Google Ventures. GV is backed by a single limited partner, Alphabet, and has $10 billion in assets under management in 400 active portfolio companies working in tech and life sciences.

David Schenkein, general partner, GV.

In this conversation, we talk about turning points in David’s career, the opportunities he sees at the nexus of technology and biology, and how he thinks about company culture. This last point is especially important to David, and deserves more public discussion.

Please join me and David Schenkein on The Long Run.

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