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Today’s guest on The Long Run is Tim Lu.
Tim is the co-founder and CEO of South San Francisco-based Senti Biosciences.
Tim Lu, co-founder and CEO, Senti Biosciences
Senti is working to develop gene circuits for cell therapies. This is about reprogramming cell therapies with precise genetic instructions on what to do in certain circumstances. The code essentially can tell the cell to kill tumor cells with a certain molecular marker on them, while sparing other cells that carry a particular molecular signature.
The first-generation cell therapies have delivered some extraordinary results for patients with cancer, but they also have some limitations. If Senti and others in the cell reprogramming world are successful, they could take cell therapies to a new level of safety and efficacy.
Tim and his colleagues have been working on gene circuits for a long time, dating back to his time on the faculty at MIT. He left that esteemed academic institution to go to work full-time on turning this research work into cell therapies that will someday hopefully help patients with cancer.
Senti’s work is still very early stage. It’s all preclinical. But it plans to seek clearance from the FDA to begin its first clinical trial, for patients with acute myeloid leukemia, in 2023.
Tim, like many biotech entrepreneurs, is the son of immigrants. His story starts there and takes a few interesting turns before getting to his current chapter, running a startup company. I think you’ll enjoy hearing about the person and the science.
Now before we get started, a word from the sponsor of The Long Run.
Calgary is home to more than 120 life sciences companies, from emerging startups to established firms. With this critical mass of research, technical talent and expertise, the city is an active hub for life sciences innovation.
Technologies homegrown in Calgary are changing the face of healthcare. Syantra is revolutionizing breast cancer detection using artificial intelligence-derived algorithms. NanoTess is harnessing the power of nanotechnology to tackle chronic wounds and skin conditions. And this is only the beginning. Calgary’s life sciences sector is projected to spend $428 million on digital transformation by 2024.
If you’re a bright mind or bright company solving global health challenges, Calgary is the place for you.
Take a closer look at why at calgarylifesciences.com
Now, please join me and Tim Lu 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 $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Today’s guest on The Long Run is Jo Viney.
She is the CEO of Watertown, Mass.-based Seismic Therapeutic. Seismic is working to discover biologic drugs for autoimmune disease. It aims to speed up the process by using machine learning on key aspects – starting with structural biology and including engineering of the protein drugs themselves.
Jo Viney, co-founder, president and CEO, Seismic Therapeutic
Jo has a long track record in this field. She was previously chief scientific officer of Pandion Therapeutics, a startup acquired by Merck for $1.85 billion in February 2021. Before that, she worked at Biogen, Amgen, Immunex and Genentech.
In this conversation, Jo talks about immigrating from the UK, how she found a career path in industry, and some key insights on how she thinks about building a startup with a creative culture.
Now before we get started, a word from the sponsors of The Long Run.
Calgary is home to more than 120 life sciences companies, from emerging startups to established firms. With this critical mass of research, technical talent and expertise, the city is an active hub for life sciences innovation.
Technologies homegrown in Calgary are changing the face of healthcare. Syantra is revolutionizing breast cancer detection using artificial intelligence-derived algorithms. NanoTess is harnessing the power of nanotechnology to tackle chronic wounds and skin conditions. And this is only the beginning. Calgary’s life sciences sector is projected to spend $428 million on digital transformation by 2024.
If you’re a bright mind or bright company solving global health challenges, Calgary is the place for you.
Take a closer look at why at calgarylifesciences.com
For Bensalem Township in Pennsylvania, going a step beyond meant taking the word ‘serial’ out of crime, thanks to DNA analysis technology. Before the introduction of this technology, processing the sample of a suspect took 18 months. But with the dedicated efforts of Director Fred Harran and Thermo Fisher Scientific’s RapidHIT ID analysis system, it now takes only 90 minutes – meaning offenders can be caught and put behind bars before they have a chance to become repeat offenders. It’s also helped prove the innocence of 16 people in the last five years.
To watch Director Harran’s story, visit www.thermofisher.com/bensalem-DNA-analysis
Now, please join me and Jo Viney 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 $169 per year, you reward quality independent biotech reporting, and encourage more.
Today’s guest on The Long Run is Ivan Liachko.
Ivan the founder and CEO of Seattle-based Phase Genomics.
Ivan Liachko, founder and CEO, Phase Genomics
First off, Ivan is originally from Kiev, Ukraine. He came with his family to the US at the age of 11, around the time of the fall of the old Soviet Union. When Russia invaded Ukraine back in February, he spoke up and mobilized his team and members of the biotech community to stand with the people of Ukraine.
That was interesting. But it turns out the work at Phase Genomics is also quite interesting.
Phase Genomics is helping scientists assemble difficult to put-together genomes, and metagenomes. That’s an extra tricky form of assembly of the DNA jigsaw puzzle that comes when you have a whole bunch of microorganisms co-existing in the messiness of life you find in something like a slab of dirt. One interesting application is now being supported by the Bill & Melinda Gates Foundation and the National Institute for Allergy and Infectious Diseases. The company is creating a repository of phage – bacteria interactions – a so-called interactome – that could be used to help identify precise phage therapies that could be used to fend off scourges from drug-resistant bacteria.
Talking with Ivan reminds me of the magic that comes when the right person lands in the right place at the right time. He and I come from very different backgrounds, but we both appreciate what’s special about Seattle as a community, and the long tradition of the United States as a leader in research and entrepreneurship. He is an immigrant who has had some success, and might have quite a bit more, partly because of his own skills and initiative, but also in large part because of the surrounding community, research culture, and business traditions.
Now before we get started, a word from the sponsors of The Long Run.
Calgary is home to more than 120 life sciences companies, from emerging startups to established firms. With this critical mass of research, technical talent and expertise, the city is an active hub for life sciences innovation.
Technologies homegrown in Calgary are changing the face of healthcare. Syantra is revolutionizing breast cancer detection using artificial intelligence-derived algorithms. NanoTess is harnessing the power of nanotechnology to tackle chronic wounds and skin conditions. And this is only the beginning. Calgary’s life sciences sector is projected to spend $428 million on digital transformation by 2024.
If you’re a bright mind or bright company solving global health challenges, Calgary is the place for you.
Take a closer look at why at calgarylifesciences.com
What does going a step beyond mean? For Gideon, a young boy fighting leukaemia, it meant getting a second shot at life. Through an innovative new treatment called CAR T cell therapy, Thermo Fisher Scientific supported our customers and the healthcare community to help Gideon reach full remission. Today, he is a healthy, happy eleven-year-old playing basketball and enjoying time with his family, thanks to our customers going a step beyond every single day to make a difference in the world. To watch Gideon’s story, visit www.thermofisher.com/Gideon.
Now, please join me and Ivan 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 $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
David Shaywitz
The implementation of emerging technologies requires front-line users to figure out what to do with the technology – how to adapt the technology to the problems users are actively trying to solve.
The most impactful use cases often are not immediately obvious – for example, Edison envisioned the phonograph would be predominantly used to record wills.
Moreover, effective adoption typically requires more than simply substituting new technology into processes built around legacy technology. For example, when factories first started using electric generators to replace steam power, there was minimal impact on productivity. It was only when the design of the factory was reimagined by entrepreneurs like Henry Ford (a redesign enabled by electricity) that the promised gains were realized.
It’s also important to consider what success looks like. PCR, an approach to amplifying often tiny amounts of DNA, was developed by Kary Mullis, who received the 1993 Nobel Prize in Chemistry for his efforts. Adopted relatively quickly, PCR enabled advances from disease detection (eg for COVID) to molecular engineering.
Yet if you look around medical labs today, you won’t find a “Department of PCR” or a “PCR Center of Excellence.” In a sense, the lack of such exceptionalism is a measure of PCR’s success and impact. Today, PCR is organically incorporated into the way science is done. It’s a tool, like the telescope and the microscope, that can be used to enhance our exploration of nature.
Today, medical researchers are actively exploring how to utilize AI. Rather than investing the methodology with spiritual or magical properties, it is increasingly recognized as a tool — a powerful tool if applied thoughtfully — that scientists are incorporating into their study of nature.
Alphafold, for example, is a deep learning tool that offers powerful predictions of 3D chemical structures based on the underlying amino acid sequence. It is already routinely, and appreciatively, utilized by structural biologists. It’s become a powerful new addition to the armamentarium.
Now that AI in healthcare has hopefully transitioned past both the peak of inflated (and truly extravagant) expectations as well as the trough of despair, we seem to have at last arrived at the point where savvy scientists are using AI as another technique to pursue their questions.
For these researchers, AI (like PCR, like microscopy) is a valuable means, a tool used to solve a meaningful problem; AI is not (like in too many breathless early publications) an exalted end, where the use of AI is celebrated, rather than any result it enabled, the “dancing bear” phenomenon I’ve described.
A recent paper, called to my attention by my long-time colleague Dr. Anthony Philippakis, a thoughtful physician-scientist and the chief data officer at the Broad Institute, offers an inspiring example of where AI in medicine may be headed.
The research he describes (and of which he’s a co-author) was led by MGH cardiologist Dr. Patrick Ellinor, who I first met when he was a cardiology and electrophysiology fellow at MGH, during the start of my medical training.
Patrick Ellinor
Ellinor and his colleagues were interested in understanding the basis of aortic aneurysms, dilations of the large blood vessel that can lead to sudden death. The identification of genes associated with aortic dilation could potentially guide the development of future medicines, while also enabling the identification of patients at risk.
Previous work had identified several extremely rare alleles that, if present, unquestionably contribute to the development of aneurysms. Yet most patients who develop aneurysms don’t have any of these alleles.
Other researchers conducted a genome-wide association study (GWAS) to identify genetic variations (single nucleotide polymorphisms, or SNPs) associated with aortic abnormalities based on data meticulously measured and recorded by echocardiography technicians; a dozen or so SNPs that could potentially contribute to disease were identified.
A talented member of Ellinor’s group, Dr. James Pirruccello, had another approach in mind. Pirruccello wanted to leverage the UK BioBank, a massive collection of deep genetic and extensive phenotypic data available to researchers for analysis. For example, cardiac MRI studies were available for about 40,000 subjects. This treasure trove of phenotypic data could be paired with the genetic data associated with participants in the U.K. database.
The elegance of Pirruccello’s approach was how he extracted the data he required from the MRI images. Manual annotation of 40,000 cMRI studies (each containing about 100 images) would be prohibitively demanding and expensive. Instead, Pirruccello trained an AI algorithm to assess aortic diameter, and, amazingly, he did so using a relatively small number of manually annotated images – 116 (92 in the initial training set, 24 in the validation set).
This approach was feasible because algorithms had previously been trained to do similar tasks. While millions of labeled images are required to train the algorithm initially, you need comparatively few to adapt an established AI algorithm to perform a similar task. This is the principle of “transfer learning.”
With the algorithm in place, Pirruccello was then able to turn it loose on the 40,000 or so cMRI images. The team was essentially converting a binary variable (aortic aneurysm: yes/no) into a continuous variable (aortic diameter). That enabled a more sensitive GWAS. Indeed, just focusing on the ascending aorta, Ellinor’s team identified 82 independent genetic regions (loci) of interest, 75 of these were novel. These loci could potentially shed light on the pathophysiology of aortic aneurysm.
These SNPs were then used to generate a “polygenic risk score”– an approach that seeks to integrate the risk contributed by a number of different SNPs, as I’ve discussed here; see also here). In turn, this measurement was used to analyze nearly 400,000 UK BioBank participants to see if it might help predict aortic aneurysms.
Remarkably, subjects with a genetic risk score in the top 10% were found to be twice as likely to develop aortic aneurysms as participants in the other 90% of the population. This type of approach, in theory, could be used to identify patients at higher risk of aortic aneurysm, and presumably help guide prevention strategies, as well as help select patients for future clinical studies. The genetic data might also help identify promising therapeutic targets.
There are many lessons from this approach, including the value of large integrated genetic/phenotypic databases, the power of GWAS analyses and its potential in target identification, and the promise of polygenic risk score assessments.
But the most exciting lessons here involve the intelligent incorporation of deep learning to “parameterize phenotype,” as Philippakis explains. The idea is to elicit an important continuous variable from a collection of images.
Significantly, Ellinor’s critical GWAS analysis, integrating genetics and phenotype, didn’t involve deep learning – just comparatively staid analytics that geneticists have been doing for two decades; the approach is at this point relatively routine.
Similarly, the polygenic risk score calculation didn’t involve deep learning.
And the research certainly didn’t involve someone asking Watson, Jeopardy-style, to think hard and come up with genes involved in aortic aneurysms.
What was clever was how the researchers leveraged AI to generate the input phenotype used in the GWAS analysis.
I hope and expect we’ll see more of these types of “organic applications” of AI as the approach becomes both less exotic and more accessible, and establishes itself as a powerful enabling tool for thoughtful medical scientists.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Vikas Goyal, former SVP, business development, Pandion Therapeutics (now part of Merck)
James Mutamba is the chief business officer of Waltham, Mass.-based Arrakis Therapeutics. It’s a biotech developing small molecules against RNA targets.
Arrakis struck its first major pharma partnership in 2020 with Roche. During the JP Morgan Healthcare Conference this past January, Arrakis announced another multi-target collaboration with Amgen to discover and develop small molecule RNA degraders, a new drug class which Arrakis calls nucleic acid targeting chimeras (NUTACs).
Arrakis’ and Amgen’s research teams are now working together to jointly design and characterize these novel NUTAC bifunctional compounds. For Arrakis, the partnership provided $75 million of upfront working capital, and expanded its platform capability for making small molecules against RNA. Amgen is getting the right to nominate a set of five initial targets and it has the option to nominate more. The deal is part of a pattern for Amgen, as it underscores the priority it has placed on drugs that specifically inhibit more than one target implicated in disease biology.
James Mutamba, chief business officer, Arrakis Therapeutics
Mutamba joined Arrakis on Dec. 6, 2021. Arrakis received the first draft of the agreement from Amgen that week. The deal was signed before Christmas Eve and announced two weeks later at the biggest healthcare investment and dealmaking event of the year.
Mutamba spoke with me recently about what it took to close such a broad and high-impact collaboration so quickly.
Why do partners come to Arrakis for access to your RNA platform?
Arrakis is building a broad platform that, given any RNA target, can figure out the structure of that RNA and develop a small molecule compound against that RNA. Building this kind of platform necessitates a lot of external resources, expertise, and insights. So as we build our platform, we are also out talking about our work. As folks hear about what we are doing, some have come to us and said, “Hey, we have a problem that Arrakis might be able to help with.” That is really what precipitated our collaboration with Amgen, as well as our earlier collaboration with Roche.
Arrakis is developing small molecules that bind to RNA. One way to leverage this is to target RNA’s intrinsic functions, and this is the focus of our partnership with Roche. This means inhibiting translation, changing splicing, modifying RNA stability, or other aspects of the RNA function. Another way is to look at extrinsic properties – can we use a binding event to force a function? One ‘extrinsic’ approach we are pursuing is our NUTAC platform for targeted RNA degradation. NUTACs are hetero-bifunctional small molecules – one side targets and binds RNA, the other side recruits a nuclease or other factor to eliminate the disease-causing RNA.
Why did Arrakis and Amgen want to work together?
We had done some early concepting and could keep working on NUTACs on our own. But, just like our partnership with Roche, we saw the potential to have a landmark NUTAC partnership to supercharge our efforts and more rapidly provide a foundation for us to build our capabilities. There is no better group to work with in the multispecific space than Amgen. They have deep expertise in both targeted degradation and induced-proximity degradation, as well as vast capabilities and competencies in the multispecific small molecule space. In addition to their technical expertise, they also have strategic goals and commitment to multispecific small molecules. And that’s an important piece in choosing the right partner. Is your partner committed to finding a way to make the collaboration and science work? Are they willing to work through any hardships?
We recognized that Amgen has a strong interest in proximity-induced drug approaches. Our NUTAC concept is akin to a PROTAC – an area in which by the way Ray Deshaies, SVP of Global Research at Amgen, is a leading expert. There’s a media interview Ray did on our deal where he explained that Amgen was looking across the RNA space seeking technologies to enable this kind of RNA degradation approach. They kicked the tires of a bunch of players in the space, and ultimately concluded that we were the right group to go with. My supposition is, again, that their decision to work with us is a testament to the breadth of our platform. At Arrakis, our proposition is ‘give us any RNA target and we’re able to tell you what structures are targetable and we can build binders.’ Amgen was bringing the drug function with the effector piece of the hetero-bifunctional molecule. So I suspect for them the focus was on which partner could best figure out the RNA binding.
How did your discussions with Amgen start and grow into this collaboration?
While we had a goal to ultimately find a good partner on NUTACs, we were not yet actively reaching out to potential partners. This collaboration started with an informal discussion between Ray Deshaies and Arrakis’ CEO Mike Gilman. Mike and Ray are both UC Berkeley alumni and were on campus together for a reunion. They started to talk and there was an alignment of vision that ultimately opened the door to this collaboration. And because of the strategic decisions we made early on to go after any RNA target, Arrakis was uniquely positioned to work on RNA degradation strategies compared to some of our peer RNA companies.
It was about a year from that initial discussion between Mike and Ray to when we executed the deal. Things really got serious when we came up with, what I like to call, our “peanut butter and jelly sandwich” concept. Arrakis is bringing the RNA binder to the table, and Amgen is bringing the effector molecule to recruit the degradation factor, and we will work together to develop those into hetero-bifunctional medicines.
Once that bifunctional concept came into view, we started putting the agreement together, including the workplan of who was responsible for which research efforts, and the budgets. We really know how to build the RNA binding piece. Amgen has the demonstrated expertise and interest in building hetero-bifunctional molecules. So a lot of the discussion was about how, working together, we and Amgen could do things sooner or faster or better than what we would have been able to do by ourselves.
This all went really quickly because we had alignment and a shared vision. From the first agreement draft to execution was three weeks. It is the fastest deal that I have ever worked on. Everyone was aligned on who would be doing what, and what was of interest to each party. There were snags here and there, which is true for most deals, but we quickly got over those because people had a very clear view of what success looked like. And we just pushed towards that.
How did you figure out the economics of the collaboration? Did you have any precedent deals or templates you could use as a starting point?
I would say there were more proxy deals we could look at, such as partnerships in the degrader space where one party brought the ubiquitination bait portion and another brought the targeting side. There were some macro guiding principles from those that we could learn from.
In parallel to working through who was going to do what part of the research plan, we also discussed how we each viewed the economics, and how we wanted to share and apportion downstream value upon successfully developing medicines.
Some of these discussions did have the risk to blow up the deal. There were 11th-hour issues that that needed to be worked through. But this is often the case during negotiations, right? Our teams at Arrakis and Amgen just had to step back and ask, “What is our larger goal here? Can we work around this issue?” And on some of the negotiation issues, both sides had to just prioritize what we actually needed to figure out how to get the technical work started and defer other issues that could be worked out in the future.
Going into your collaboration discussions with Amgen, how well did the two companies understand each other?
Both Arrakis and Amgen have done a really good job of telling the external world what we’re interested in and what our expertise areas are. From Arrakis’s side, we have rigorous publications speaking to the scientific community, for example on our PEARL-seq tool. There are also informal things we do. We post about our culture on social media and our website. Our CEO has a huge Twitter following and talks about everything from his guitars to our company. Our success at getting the word out has really been through utilizing a mix of the technical and informal channels available to us.
Of course, Amgen spent time under the hood to confirm we were the best partner with RNA binders. The main effort was on making sure both we and Amgen were thinking about the NUTAC application in the same way. I remember a technical discussion where both we and Amgen were presenting our proposed workplans – there were a lot of nodding heads and people bouncing ideas off of each other. And it became clear that our working together would be complementary. For our team, I think that meeting really cemented for us that Amgen was the right partner.
How did you approach your role in this BD process?
I joined Arrakis the first week of December 2021. Just a few days later, we received Amgen’s first draft of the agreement. This was a high priority for Amgen. They wanted to announce the deal at JPM 2022. Both teams were aligned that we did not want to work over Christmas. So the deal was actually executed on Christmas Eve at 6 pm.
The pressure was on to get the deal done fast. We needed a quarterback to manage the deal timeline. I stepped into this role to coordinate our discussions – which conversations needed to happen, who needed to be in the room, did it get scheduled, did our people actually have the bandwidth to work on it, can I make this process more frictionless? And then ultimately making sure what we discussed made its way back to Amgen and into the contract. We were parallel processing discussions across the overall agreement, the IP terms, the technical work plan and the program management team. There was a lot to coordinate.
There were also strategic things coming up. If Amgen asked for something, I was taking the lead on analyzing how that issue might affect our interests. And as things zigged and zagged, I was keeping an eye on what we were trying to achieve overall and making sure we were landing in an optimal place.
And I was definitely the hub of the discussions with Amgen. Formally, I was the one facilitating all the communications that were happening. Informally, I was also doing the work to understand what Amgen really wanted. For example, some term would appear in a draft which, as written, might have been problematic. I was the person able to go to the lead contact at Amgen and just say, “Hey, what’s the real ask? OK could we solve it like this instead?” And then I was able to come to the next drafting session with a real solution. Having those one-on-one conversations in a low-pressure way helped us get the deal over the finish line, and de-escalate issues that sometimes initially seemed like a hornet’s nest. Of course, there were also some issues that we had to escalate, but we tried to keep them to a minimum.
My counterpart was Chester Wong. who led the transaction from the Amgen side. Chester and I didn’t know each other before this deal and actually never met face-to-face, negotiating the entire deal by video. When we started, it felt like we were across the table from each other. By the end, after spending many late nights together, our relationship got much tighter. Discussions would veer off the deal to what we were watching on Netflix . . .
[laughs]
By the end we were all around the same table trying to figure out how to make the deal work. I remember one late night call with the IP folks from both teams, and in real time, we started writing the agreement together. There was none of the usual posturing you often get.
This was an all-hands-on-deck effort with Amgen. How did that impact everything else happening at Arrakis?
One thing is to just brutally triage what is and isn’t important. Amgen was right at the top of the list of priorities. Mike and everyone on the operational side was on board with that. Plus, we didn’t need to disrupt the entire organization over this. There were specific people from our senior research team who needed to weigh in with Amgen, and we just activated people from our side as and when needed. So we could keep running the business as usual. But sometimes I needed to get an hour of the research team’s time to get their input on the Amgen negotiation, and the team just had to pause whatever they were doing.
I had just been through a similarly complex, time-gated IPO process, so I quickly intuited the role I needed to play on this deal. I also had people around me who wanted and supported me to play that role. When I joined Arrakis, the team was very welcoming and gave me leeway to get the deal done.
Who were all the people around the table during these discussions to hammer out all the aspects of the deal?
We had multiple sub-groups who were parallel processing the discussions. The Arrakis team was literally exchanging notes at the end of every day to keep track of what was changing.
Our overarching BD team working on the actual agreement included me, our CEO Michael Gilman, and our Head of Legal, Erik Spek. Erik has a great IP background, as well, so he was really weighing in those considerations.
On the technical side, it was our CSO Jacques Dumas and our Chief Innovation Officer Jen Petter. They were taking the lead on reviewing the targets Amgen wanted to work on, even doing some early research to validate the ideas. Amgen also had a technical lead on their BD team, Duncan Huston-Paterson who was working closely with Ryan Potts, Executive Director and Head of Amgen’s Induced Proximity Platform.
And we also had our program management team, led by our SVP & Head of Operations, Heather Lounsbury. Heather’s team was instrumental in putting together the budgets and the timelines for the collaboration, and really mapping out what was required to bring this science over the finish line. One of Arrakis’ lessons from the Roche collaboration process was the value for coordination between the scientific and business discussions, so we also built this into the Amgen deal process.
All in all, it was an effort of working through all these facets of the collaboration and integrating all of them.
Now that you are in the collaboration, can you describe how it’s helping accelerate the NUTAC approach?
One way I think Amgen might help us is by learning the requirements for hetero-bifunctional small molecules. For example, how to consider the exit vectors from the RNA piece and therefore what the linker needs to look like. Amgen has also worked on the nuclease targeting side, which should enable us to put together that “peanut butter and jelly sandwich” much faster. So now we can work in parallel on the RNA binding piece, the linker piece, and the bait molecules.
Amgen is also nominating the targets for the collaboration. They know the biologies, likely have the assays in place, and know what success on those targets looks like.
And from a resource perspective, the funding Amgen is providing helps to finance the work and hire people to do our work even faster.
Ultimately, what’s also important is having a mature, seasoned, experienced partner help shape how we develop these NUTACs. We experienced this with Roche, as well. Where we are today, as a function of that partnership, is an order of magnitude difference. For example, with Roche we’ve industrialized our screening methods and run more than 40 high throughput screens and matured our approach to building RNA targeting molecules. So similarly with NUTACs, I think Amgen has the potential to help us mature how we think about hetero-bifunctional medicines.
How does this create more value for Arrakis?
Our collaboration with Amgen is initially focused on five targets. There’s undoubtedly more than five RNA targets one would want to degrade. All of that is open to us. That goes full circle back to our strategy to have landmark partnerships that helps us mature the platform. Yes, we give up value to a well circumscribed number of targets in the space, but then everything else is available to us. So we can work beyond the Amgen collaboration to build our capabilities and still retain value that we can build on.
The collaboration also definitely brought a new visibility to Arrakis. This deal made a splash at JPM, which is exciting for a preclinical deal. People across the biotech investor and business spectrum got interested and reached out to us. We were one of the few preclinical companies to present at the JPM conference this year
Shifting gears a bit, what have you learned about BD working on deals for so long now?
First is just my disposition, in any deal, to take nothing for granted. Until the money is in the bank, anything can go wrong. So foremost is just get stuff done, keep the trains running, be aggressive on the timelines, and just keep slogging away to get the deal done.
Second is to root out any sensitivities that might exist but aren’t being stated explicitly. It’s always navigating people. It’s what’s not being said that, in some cases, is more important.
What was surprising with Amgen was how fast we did it, and also what it takes to get it done that fast. I was blocking off whole portions of my days to do calls with Amgen, and also doing these calls at weird times. In some ways it was helpful to have the West Coast, East Coast time differential. We tried to set up cycle times where one group was working while the other was sleeping.
And we also built a really good relationship with Amgen’s deal team. I think that was because they were so strategically aligned with what we are trying to do and there was buy-in across the whole organization on their side. During meetings, we didn’t come into the room and pontificate or grandstand. Everything was solutions focused. We were very quickly just being transparent if something really was unacceptable. All in all, none of these are all that unusual. But when you bring all these pieces together, that’s the surprise. And I think because of our strategic alignment and the relationship we built, we were able to get over a lot of contract issues and other snags that otherwise could have become showstoppers.
What did I forget to ask you?
Maybe a few parting thoughts on the road ahead. At Arrakis, we have the opportunity to replicate all of the novel modalities and progress that has happened on the protein side, except with RNA. Historically small molecules bind to a protein’s active site to change the behavior of that protein. That’s what our intrinsic partnership with Roche represents. The NUTAC partnership is a play on PROTACs. We’re now looking at irreversible inhibition or irreversible binders to RNA, which is similar to some of the covalent protein modifiers. Arrakis is sitting at the precipice of this large opportunity space, and there continues to be a desire at Arrakis to work with other partners to broaden our knowledge and enhance our scope and speed of developing new medicines. We are interested in doing more partnerships. I wouldn’t be doing my job if I didn’t put that plug in.
Please subscribe and tell your friends why it’s worthwhile. Quality journalism costs money. When you subscribe to Timmerman Report at $169 per year, you reward quality independent biotech reporting, and encourage more.
Today’s guest on The Long Run is Dr. Sanduk Ruit.
He is an ophthalmologist and the founder and executive director of the Tilganga Institute of Ophthalmology. The institute is in Kathmandu, Nepal.
Dr. Sanduk Ruit, founder, Tilganga Institute of Ophthalmology
Dr. Ruit has restored the eyesight of more than 130,000 people in Asia and Africa. He’s the pioneer of a small-incision form of cataract surgery. Not only was that a medical triumph, but he’s found a way to make the treatment accessible to many very poor people in Nepal and beyond. His institute has developed a way to manufacture its own intraocular lenses to insert in the eyes of patients, with the same quality of Western suppliers, and at a tiny fraction of the cost.
Dr. Ruit comes from a very poor and remote region of Nepal. He’s an inspiration in his home country, and has won more than 40 awards from governments and other institutions around the world. There’s a book about him called “The Barefoot Surgeon.”
I was fortunate to meet Dr. Ruit in Nepal this past spring. I was there with my team of 18 biotech executives for a trek to Everest Base Camp, in which we raised $1.3 million for research at the Fred Hutch Cancer Center.
While in Kathmandu, one of the trekkers, Jeff Huber, the former CEO of Grail, introduced me to Dr. Ruit and his amazing story. Jeff and I invited him to speak to our broader group. I’m glad, because Dr. Ruit’s work shows what a difference a talented and driven scientific entrepreneur can make. We were thinking a lot about how to make an impact for people in need, and Dr. Ruit really shows the way.
When he and his trainees do these eye surgeries, they are giving people their lives back, and relieving a major burden from whole families.
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Now, please join me and Dr. Ruit on The Long Run.
David Shaywitz
Living in innovative domains like biomedical research requires an appreciation for the exceptional, the outlier. You might even argue that the goal of innovators – at least those who hope to see their ideas gain acceptance, or their inventions adopted – is to institutionalize the exceptional and make it routine.
In the Perez model of technology adoption, this is the basic difference between the “Installation Phase,” and the “Deployment Phase.” In the Installation Phase, the world tries to make sense of a new technology, and considers many possible expressions of it (rejecting most). In the Deployment Phase, the technology is widely adopted, becoming domesticated and routine.
Surviving and thriving in an innovation-oriented realm requires a distinctive mindset: the persistence and patience to search constantly for the exception..
At one level, of course, we understand the challenge: we know that most drug candidates don’t reach the market, that most startups fail, that most creative endeavors – music, literature, film – never leave an imprint on large numbers of people.
It’s also why many rational people prefer the comfort of more predictable domains, where consistency is both expected and prized.
The difference between exception-driven domains, ruled by the power law, and more predictable domains, governed by gaussian distributions, was also a central theme of Nassim Taleb’s The Black Swan – see here. Taleb termed these two worlds “Extremistan” and “Mediocristan.”
For those opting for innovation, for Extremistan, it’s easy to get discouraged and distracted by the median – especially after you’ve been pitched by the umpteenth unmoored AI startup or the latest vendor overpromising comprehensive distributed clinical trial capabilities, or forced yourself to remain awake through yet another dismal corporate visioning activity or ideation session.
Yet it’s critical to recall, as Stephen J. Gould famously explained, “the median isn’t the message.” Gould was diagnosed with a rare form of cancer, associated with a median survival time of eight months. While initially “stunned,” and “not, of course, overjoyed,” he was nevertheless able to recognize the possibility and promise of life on the far extreme of the distribution. Thanks to a deliberately positive attitude, exquisite medical care, and a lot of luck (not necessarily in that order), he lived another 20 years.
Colleagues who have thrived in innovative spaces seem to share Gould’s ability to locate the exception. Dr. Amy Abernethy, now at Verily, has long impressed me with her ability to identify the most hopeful outliers – ideas, people, organizations – however rare they might be.
The mindset is not to be confused with toxic positivity, which asserts that everything is just great; Abernethy, from what I can tell, has little trouble recognizing abundant mediocrity – but it doesn’t prevent her from also identifying and cultivating hints of unusual brilliance, wherever she might find it.
Similarly, I’ve always found myself involuntary drawn to the exceptional, and the most interesting. In organizations where most people are highly competent but just seeking to get their jobs done, I’ve consistently found the outliers, those with a slightly different perspective, and a more ambitious personal mission. The experience of connecting with an exceptional, perhaps overlooked innovator can turn a day of tedious, predictable meetings into one of discovery and promise.
Without question, in innovative spaces, it’s easy to get disillusioned. The hype is constant, and most innovation doesn’t pan out.
Nevertheless, to paraphrase Miracle Max from The Princess Bride (a movie that, as my friend and fellow Timmerman Report contributor Lisa Suennen has pointed out, may be the fount of all entrepreneurial wisdom), “there’s a big difference between ‘mostly crap’ and ‘all crap.’ ‘Mostly crap’ is slightly promising.”
And it’s this promise, however slight and elusive, that we need to celebrate, nurture, and relentlessly pursue.
As you wish.
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