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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.
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.
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.
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.
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.
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.
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.
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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.
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.
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.
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.
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.
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
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.
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.
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.
Here are a few directions US biopharma can take:
Ken Song, CEO, Candid Therapeutics
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.
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.
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.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $199 per year, you reward quality independent biotech reporting, and encourage more.
Today’s guest on The Long Run is Kevin Fitzgerald.
Kevin is the chief scientific officer of Cambridge, Mass.-based Alnylam Pharmaceuticals. He joined the company way back in 2005, when it was aspiring to create a new class of RNA interference medicines. These are sometimes referred to as “gene silencing” drugs. They are designed to shut down the production of disease-related proteins.
Kevin Fitzgerald, chief scientific officer, Alnylam Pharmaceuticals
Kevin has been through a roller coaster ride of events, as it worked through years of challenges on how to effectively deliver these promising molecules into cells. Alnylam now has four FDA approved medicines for rare diseases based on this technology. A fifth drug from Alnylam’s platform, inclisiran, is now marketed by Novartis as Leqvio for lowering LDL cholesterol, and reducing people’s risk of cardiovascular disease.
In this episode, we talk about how Kevin found his way into science and ultimately, on the front wave of a revolution in RNA-targeted medicines. He’s stayed around 20 years, he says, in large part because the technology keeps improving and opening up new possibilities to treat patients with both rare and common diseases. He also discussed why patients might choose RNA medicines when given a variety of other options with gene editing and gene therapy.
Please join me and Kevin Fitzgerald on The Long Run.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $199 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $199 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $199 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $199 per year, you reward quality independent biotech reporting, and encourage more.
Simon Barnett, research director, Dimension
I recently attended the Molecular Machine Learning (MoML) Conference sponsored by the MIT Jameel Clinic, an institute focused on cutting-edge machine learning (ML) techniques in the life sciences. Computational approaches to drug discovery and development were the centerpiece of the symposium.
Investor sentiment for ML-centric discovery biotechs has been turbulent recently, but researchers at MoML were widely and consistently enthusiastic. Specifically, in silico therapeutic protein design stands apart as an area with enormous, near-term disruptive potential.
Computational techniques may materially compress the costs and timelines associated with therapeutic protein discovery, spawning new business paradigms along the way. How these technologies saturate the pharmaceutical ecosystem to capture value is still nebulous.
Should this thesis play out, adjacent phases of drug development (e.g., clinical translation) will become bottlenecked. We should be grappling with how to solve these challenges today because this future is not as far off as it seems.
Monoclonal antibodies (mAbs) are a cornerstone of the pharmaceutical industry. Comprising both in vitro and in vivo approaches, the screening technologies scientists use to discover and optimize mAbs have matured over several decades.
Researchers can inject a drug target (e.g., an antigen) into a mouse, rabbit, or other mammal, leveraging these species’ immune systems to produce antibody candidates. Alternatively, scientists can use a method called biopanning. This involves expressing antibody libraries on the surfaces of microorganisms and testing to see which candidates bind to a target antigen.
Both screening paradigms are effective, having produced dozens of approved mAbs. Over the years, both approaches have undergone steady improvements, though I’d argue these have been incremental. At MoML, some even claimed that mAb discovery is effectively solved since very few drug campaigns fail because a high-affinity antibody couldn’t be produced.
I agree—to an extent. Immunization and biopanning are still relatively cost and time-intensive, especially compared to the promise of in silico antibody design. Computational approaches could meaningfully alter the economics of early-stage antibody discovery, enable multi-objective optimization (e.g., affinity and developability) in a manner that chips away at downstream program failures, and contend with the exploding complexity of next-generation biologics (e.g., multi-specific antibodies).
Drug discovery’s core challenge is traversing between a molecule’s structure (or sequence) and its activity. This relationship is often complex and non-linear. Another hallmark of modern drug discovery is that the design space is orders of magnitude larger than our experimental screening technologies can contend with—creating search bottlenecks.
In silico design is tantalizing because it offers an ostensible bridge between inputs and outputs that isn’t reliant on the throughput of physical laboratories. What if there were a world where researchers could condition ML models to generate a small number of high-quality candidate designs for pennies? This might allow scientists to reconfigure physical assays for the purpose of validation rather than discovery.
This is fiction in 2024, but it may not be in 2030. Progress won’t be uniform, however. My sense is that digital tooling for therapeutic protein design is the most advanced and rapidly improving category.
Proteins have several advantages that other established therapeutic modalities (e.g., small molecules) do not when it comes to the viability of contemporary ML techniques.
Firstly, ML models are only as good as the data they’re trained on. Very large, diverse, well-annotated bodies of data make for the most performant models. These are few and far between in the public domain. Researchers can leverage open repositories like UniProt that are replete with matched protein sequence and function data. Antibody-specific databases like OAS also contain over a billion, highly relevant datapoints.
Small molecules don’t have this advantage. Protein-ligand structural databases, such as the Protein Data Bank (PDB), contain a fraction of the data we have on proteins in the public domain. Though the PDB has given rise to invaluable ML models like the AlphaFold series for structure prediction, I’m convinced that other enabling technologies (e.g., neural network potentials) are required for bridging the structure-activity chasm of small molecules.
Secondly, ML models are attuned to decipher the rich, evolutionary signal embedded in protein sequence data. During training, models extract how natural selection has etched patterns linking sequence motifs with functional attributes. This is how in silico protein models can gain multi-objective capabilities, enabling the simultaneous optimization of affinity as well as other intrinsic properties like aggregation potential, thermostability, and more.
Finally, it’s much easier to physically express and analyze protein sequences than it is for small molecules. Researchers can choose from a host of highly optimized expression chassis and leverage next-generation sequencing (NGS) to map sequence to functional data. This allows labs to establish active learning loops that marry together wet- and dry-lab capabilities.
Over the next few years, I predict that state-of-the-art computational models will be able to generate 10s of candidate antibody sequences with nanomolar affinity towards specific target epitopes. It’s likely that these models will be multi-objective, enabling co-optimization of multiple, desirable properties. Certain downstream properties with miniscule data (e.g., manufacturing titer) will prove challenging, however.
There’s also a world where specialized or otherwise fine-tuned models excel in adjacent biologics categories, such as multi-specific antibodies, T-cell engagers, minibinders, and more.
What happens in this new, potential reality? It’s true that molecular discovery only represents a fraction of the total cost, time, and failure risk of a drug program. Bookending molecular discovery are target nomination and clinical translation. Both of these are challenging domains that aren’t subject for disruption by even the most sophisticated protein ML models today. Even so, with the rise of potent generative models, several industry aftershocks may occur.
Large pharmaceutical companies will seek to maintain their positions. Recently, large pharma has outsourced innovation via M&A of smaller, agile biotechs. This is likely to persist. Genentech’s acquisition of ML-pioneer Prescient Design in Aug. 2021 is an example. I wouldn’t be surprised if most large pharma companies seek to acquire similar, emerging computational platforms.
Established and growing biopharma alike will also outsource biologics R&D to specialized development partners who themselves increasingly lean on computational approaches. San Mateo, Calif.-based BigHat Biosciences and Boston, Mass.-based Generate:Biomedicines are both exceptional protein drug discovery platform companies with burgeoning pipelines.
Other companies will try to transform their discovery engines by purchasing and integrating a wave of ML-native protein design tools from companies like Cradle, Latent Labs, Chai Discovery, and more. The speed of progress is astounding, as evidenced by the launch and open-sourcing of several competitive structure prediction models just 12 months after AlphaFold3’s introduction.
Next-generation antibody development partners may have totally different unit economics. They may have very small physical footprints, and low fixed labor costs, while supporting an equivalent or greater number of campaigns compared to current players. Whether they try to undercut existing vendors or retain the margin to morph into a new type of company is still unclear.
If the cost and time associated with molecular discovery collapses to near-zero, it will place immense pressure on the up and downstream phases of drug development. Do we have enough sound drug targets to prosecute? Do we have the translational infrastructure necessary to deliver these new molecules to patients?
Investing in the entire stack, from target biology to regulatory affairs, is Dimension’s modus operandi (TR coverage, Jan. 2023). While we expect generative protein models to supplant existing discovery techniques, innovative methods will need to saturate the entire ecosystem to achieve tidal shifts in the aggregate burden of bringing new medicines to patients. The potential exists to make drug discovery faster, cheaper, and better. We’re excited about the future and there’s still so much to build.
Simon Barnett is Research Director at Dimension.
Disclosure: Dimension is an investor in Chai Discovery.
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The intensive care unit in a hospital is a place where hope and despair whisper back and forth in the air.
For Richard, the emotional seesaw was becoming all too familiar. This was his third ICU stay in a month, and the ninth brush with life and death from pulmonary arterial hypertension. No matter how hard the day was, he remained determined to live happily. He’d belt out Rolling Stones songs at full volume, drowning out the hum of machines.
Dr. Lindsey Ulin, palliative care fellow, Massachusetts General Hospital and Dana Farber Cancer Institute.
I could never quite bring myself to disturb him, so I’d gently slide the door closed, not wanting to disrupt his joy.
His prognosis was grim. High-flow oxygen and a constant Remodulin infusion were his companions. Even so, when he got out of the hospital, he would quickly hop on planes and trains to see the world. His will to live a good life was powerful. So when it came time to address his recent escalation in medical care, I wasn’t surprised that Richard put up another fight.
Pulmonary arterial hypertension (PAH) is a terminal illness, manageable through medications like treprostinil in the injectable or inhalable forms (Remodulin) and (Tyvaso). But these drugs only buy some time. The disease is irreversible without a lung transplant. For Richard, his age (80s) and medical history of other co-morbid conditions meant he was no longer a candidate for a transplant. Time was running out. We began discussing hospice care.
Dr. Jingyi Liu, a hospitalist and biopharma investor in New York City.
Hospice is both a philosophy of care and an insurance benefit. The focus of care changes from curative therapies to maximizing comfort and quality of life with an interdisciplinary team of clinicians, social workers, and chaplains. It’s an option for adults and children with a life expectancy of less than six months, but it requires making a difficult decision.
Receiving hospice care requires stopping medical treatments to help them live longer, which also may make them feel better.
This is where the H.R. 9803 Hospice Care Accountability, Reform, and Enforcement (CARE) Act, currently introduced to the US House of Representatives, comes into play.
Currently, under Medicare, hospice services are paid for at a per diem rate (~$200 per day for hospice-at-home) which must cover everything ranging from nursing care to medications to equipment.
This payment structure hasn’t evolved since the 1980s. Payments were based on a couple of assumptions. Cancer patients, for example, tended to decline and die fairly quickly. Second, there was a clear line between drugs that extend life (e.g. chemotherapy) and treatments that alleviate symptoms (e.g. opioids for pain and shortness of breath).
Advances in medicine have made this payment structure outdated. Medications like Remodulin can both reduce symptoms and extend life. It’s not a cure. Remodulin is one of a handful of treatments that isn’t covered by Medicare’s hospice payment structure because it extends life for a while, without offering hope for a cure. Inotropes and diuretics for heart failure, dialysis and related medications for kidney failure, supportive medications for liver failure, and blood transfusions for leukemia are a few other examples of medicines that reduce suffering at the end of life but aren’t covered by Medicare’s hospice payment plan because they also extend life for a while longer.
Provisions within the CARE Act could expand access to what’s called “concurrent care”. This would allow Medicare to pay for the usual hospice treatments, and a few of the others listed above that help people live better and maybe a while longer.
Interestingly, while most adults on Medicare, like Richard, cannot receive concurrent care, veterans receiving care through the Veterans Health Administration and children can. So there is a precedent.
For Richard, Remodulin made breathing easier, but it wouldn’t change the fact that he was likely to live six months or less. The dilemma was clear: stop the medication and enter hospice, but likely face death within hours, or stay on Remodulin, forgo hospice support, and hopefully have a few more weeks to months of life.
It’s a tough decision, one that weighs heavily on those who rely on medications that both alleviate symptoms and extend life.
Conversations about the end of life are never easy. But what makes them even harder is the unspoken truth: we’re forced to put a price on something we can never truly quantify—how much we’re willing to pay for someone to die well.
Healthcare costs soar as life comes to an end. Medicare data confirm that hospitalizations are the primary driver of these rising expenses. The cost of medicine is a smaller contributing factor.
Within these tough and nuanced discussions lurks a bigger question: How much are we willing to invest in giving people a good death? What’s considered a good death will be different for each of us, but we all share the same fears of dying in pain and discomfort.
When people want to continue living, we’re quick to pay the bills for treatments that offer a few more months, a few more breaths, a little more hope. But when people are ready to die, we decline to pay for medications, even if they help people live a bit longer and better.
A good death and the memory of it for loved ones left behind should count, too.
Richard decided that he wasn’t ready to unplug his Remodulin. I couldn’t blame him. With a favorite Rolling Stones song and a twirl of his motorized wheelchair, he checked himself out of the ICU.
Next stop? Las Vegas. The casinos. The flashing lights. And maybe, just maybe, a triple 7 on a slot machine.
For Richard, it wasn’t about the odds; it was about the joy and the fleeting happiness we all crave, even as his time was running out.
Dr. Ulin is a palliative care fellow at Massachusetts General Hospital and the Dana Farber Cancer Institute.
Dr. Liu is a hospitalist and biopharma investor in New York City.
I’m excited to announce the 2025 Timmerman Traverse for Damon Runyon Cancer Research Foundation team.
This group of 17 men and women are on a mission to raise more than $700,000 for the next generation of outstanding cancer researchers. In April, we’ll come together on the world-famous trek to Everest Base Camp, elevation 17,600 feet.
We’re raising awareness for cancer research. Raising funds to propel the careers of young scientists. Forming friendships. Preparing to marvel at the world’s most spectacular mountain range.
Who’s on the Team?
These people are tasked with raising $50,000 apiece for Damon Runyon Cancer Research Foundation. You can see their personal statements on why they are doing this, and how you can help, at the team donation page.
Corporate sponsors, please reach out to anyone you know on the list above to ask how you can show your support. Or reach out to Elyse Hoffmann at Damon Runyon Cancer Research Foundation. elyse.hoffmann@damonrunyon.org.
If you are interested in joining the trekking team, see me. I am looking to add a couple of alternates. Tell me about your physical fitness, health history at altitude, and why you are passionate about cancer research. luke@timmermanreport.com.
Thanks for your support. For more on Damon Runyon Cancer Research Foundation, see this short video on the Feb. 2024 Timmerman Traverse team that summited Kilimanjaro.
Timmerman Traverse
Today’s guest on The Long Run is Jonathan Bricker.
Jonathan is a professor in the cancer prevention program that’s part of the Public Health Sciences Division at Fred Hutchinson Cancer Center in Seattle.
Jonathan Bricker, Professor, Cancer Prevention Program
Public Health Sciences Division, Fred Hutch Cancer Center
This episode is a little different than most. Jonathan is a clinical psychologist by training. His research team focuses on how to use a combination of technology tools — chatbots, smartphone apps, websites, telehealth – to help people quit smoking and break other harmful health habits. Pharmaceuticals aren’t the end-all, be-all here. But they sometimes can play a role in combination with tech-enabled behavioral interventions.
Despite major progress in reducing tobacco consumption in recent decades, smoking is still the leading cause of cancer death in the US. Anything that could help millions of people quit smoking has potential to reduce a huge source of suffering and death from cancer. It could make a bigger difference than any single pharmaceutical product.
This is a fascinating conversation that spans the boundaries of disciplines that don’t often converge – tech, biotech, and psychology.
Jonathan has a popular TED talk about “the secret to self-control” that you can find in the show notes on TimmermanReport.com. He has found broad audiences for this work, at one point capturing the imagination of comedian Trevor Noah. And FYI, I’ve known Jonathan a while, as he happens to be an alumnus of one of my past Kilimanjaro expeditions for Fred Hutch.
Please enjoy this fascinating conversation with Jonathan Bricker about alleviating a major source of cancer suffering and death. You might even discover some insights here that could translate into creative ways to break other sorts of addictions.
If you like listening to The Long Run, you’ll love a subscription to Timmerman Report. This is where you can read my coverage of the most interesting startups in biotech, my weekly Frontpoints column, and commentary from a rotating cast of contributing writers. Individual subscriptions are available on a monthly, quarterly, or annual basis. Group subscriptions are available at a discount. Go to TimmermanReport.com and click on ‘Subscribe’ for more.
David Shaywitz
As we head into Thanksgiving, I wanted to share a story that highlights the promise and possibility that can emerge from a devastating diagnosis, and emphasizes what can happen when industry, academia, and — especially — impassioned parents and advocates join forces.
Consider the devasting rare genetic disease, spinal muscular atrophy, or SMA.
According to Cure SMA, SMA is “a progressive neurodegenerative disease that affects the motor nerve cells in the spinal cord and impacts the muscles used for activities such as breathing, eating, crawling, and walking.” It is caused by mutations affecting the SMN1 gene, which is critical for motor neuron survival and function.
Today, there are several treatments (not quite cures) available for SMA patients, approaches that can be highly impactful in some patients, particularly if administered early in the course of the disease.
The parents of one child with SMA have been particularly involved in driving the development of treatments: Dinakar Singh and Loren Eng, both high-powered investors whose two-year-old daughter Arya was diagnosed with SMA in 2002. The couple helped established the SMA Foundation the following year. The foundation went to work finding the most promising science in the SMA field, and ultimately securing $150 million to support basic, translational, and clinical research.
Loren Eng, president, SMA Foundation
Their drive to help their daughter was relentless.
As Loren Eng described in this piece from the Stanford Graduate School of Business magazine:
Arya had a milder form of the disease, which meant she would probably survive early childhood. But with no treatment in sight, her life would be a hellish series of hospitalizations and painful, relentless physical attrition. “The doctor said she might live to finish high school,” Eng recalls.
Eng devoted herself to changing that outcome.
As her parents and the SMA foundation fought to accelerate the development of effective medicines, Arya’s condition worsened.
By the time she was five, Arya was in a wheelchair. Each succeeding year brought new challenges as her physical capacity diminished, and the effects of her condition led to serious, sometimes life-threatening problems. As the muscles in her chest weakened, Arya lost the ability to cough, which is critical for clearing the airway during a respiratory illness. As a result, common colds could turn into pneumonia, a leading cause of death among people with SMA. “I missed tons of school because every time I got a cold, it would turn into two weeks of respiratory therapy,” Arya says.
Gradually, her muscles weakened so much that they could no longer hold bones in place. Her hips dislocated. Scoliosis twisted her spine; orthopedic deformities developed throughout her body, requiring multiple corrective surgeries. Pain shadowed her constantly.
Over time, the science advocated by the SMA Foundation advanced, and by the time she was 11, Arya was the second subject in a clinical trial for a SMA medicine. The drug candidate, nusinersen (Spinraza) is an antisense oligonucleotide aimed at the SMN2 gene, a “backup” gene that usually produces only small amounts of SMN because of alternative splicing that results in a truncated non-functional form of the protein.
Nusinersen (developed by Carlsbad, Calif.-based Ionis Pharmaceuticals and Biogen) works by modulating splicing of SMN2 pre-mRNA, increasing the amount of full-length SMN protein that’s produced. The drug required regular injections into the spinal cord, but miraculously, seemed to halt the inexorable progression of disease in Arya. Her condition stabilized.
Occasionally, the grueling regimen of operating-room visits and spinal injections tested Arya’s resolve. She was a little girl, and this was not how little girls were supposed to live. When she was scheduled to receive a dose on her 12th birthday, Arya broke down in tears and declared to her mother, “This is the worst birthday ever!” Eng tried to console her. “This is the best birthday present you will ever get,” she told Arya. Recalling the moment, Arya acknowledges that her mom was right. “I didn’t agree with her then, but I do now.”
She later participated in a clinical trial for a different drug, risdiplam (Evrysdi), a small molecule that also aims to increase the expression of full-length SMN2 pre-mRNA, and boost SMN production. The mechanism of action of risdiplam (developed in a collaboration between South Plainfield, NJ-based PTC Therapeutics, the SMA Foundation, and Roche) is somewhat different than that of nusinersen.
Most importantly, the drug can be taken as an oral pill. Arya subsequently switched to that medicine, which obviated the need for spinal cord injections. She was not eligible for a third medicine, Zolgensma (a gene therapy approach developed by Chicago-based AveXis, later acquired by Novartis), as it was approved only for much younger patients.
“Thankfully, Arya’s mind and heart have not been touched by SMA,” Dr. Chung says, adding, “She has been a strong advocate for others with disabilities.”
Now, flash forward to this summer.
Each week, the New York Times features a wedding in their Vows section, a detailed portrait of a particularly interesting couple getting hitched. On August 9, 2024, the featured bride, who had graduated from Yale in 2022, was Arya Singh.
