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.
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.
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.
TR10 East Coast Party
Toasts / Roasts / Predictions.
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.
Toasts / Roasts / Predictions.
Mapillar Dahn, founder, MTS Sickle Cell Foundation
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.
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.
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.
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.
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.
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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.
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.
