The UK feels like a fully coiled spring, ready to unleash. It’s home to many of the finest technical minds on the planet, with four of the world's top ten research universities. But when it comes to turning groundbreaking science into world-changing startups, it’s lagging. The deep tech sector in the UK (population 68M) is a fraction of San Francisco’s (population 800K).1 No place on Earth has a larger gap between the caliber of technical talent and the robustness of the deep tech ecosystem. Bridging that gap is an opportunity for the UK to become a global engine of deep tech innovation and impact.

At Fifty Years, we think we can help. To do so, we've set up shop in the UK. We've opened our first HQ outside San Francisco in London, with five Happy Warriors on the ground.

The heart of our UK effort is Fifty Years’ flagship 5050 company creation program. 5050 is a free, 16-week program designed to help great scientists and engineers become great founders. Its goal is simple: help top technical talent start more indispensable companies. 250 scientists and engineers have graduated from 5050, and over 55 deep tech startups were started out of the program. 5050 alumni are building companies delivering ultrafast DNA sequencing, AI-driven drug discovery, autonomous wind-powered cargo ships, enzymatic textile recycling, and more.

In partnership with the UK's Advanced Research and Invention Agency (ARIA), we're bringing 5050 to the UK.

When we shared our UK plans, one of our investors pointed us towards two folks already doing great work building entrepreneurial communities for scientists in the UK -- Sir Tony Kouzarides and Steph Avraamides. Steph and Tony co-founded Vellos, an organization with a mission of transforming scientists into founders building paradigm-shifting companies.

Meeting Steph and Tony, we were immediately struck by the alignment. They were high energy happy warriors, shared the same vision for empowering great UK scientists to become great founders, and had already done leading work on the ground. These were our people. We realized combining Fifty Years' Silicon Valley know-how with Vellos' deep roots in the UK would help us achieve our shared mission faster. We're happy to share that Fifty Years and Vellos are joining forces to inspire and empower more UK scientists and engineers to launch indispensable companies!

By joining forces we’re combining the best of both worlds. Vellos brings deep connections to the UK scientific community – Tony and Steph having helped educate over 1,000 scientists, engineers, and clinicians in entrepreneurship. 50Y brings experience creating and supporting deep tech startups – having backed over 100 startups from the earliest stages and helping them raise nearly $5B in follow-on capital.

Tony and Steph are movement builders. In addition to being one of the leading figures in the field of epigenetics and cancer, Tony is one of the UK’s top scientist-founders. He’s founded billion-dollar companies like Abcam and drug discovery startups like Storm and Chroma. He’s also a relentless mentor, helping early-career scientists translate their work into real-world impact. After studying biomedical research at the University of Cambridge, Steph has built and led multiple launchpads and venture-building programs across the UK. Empowering the next generation is her calling.

They’re joined by a dream team of Happy Warriors: Vaitea, Souvid, and Kim.

Vaitea Cowan is a force of nature. At just 23, she co-founded Enapter to replace fossil fuels with renewable hydrogen. She helped take the company public, shaped energy policy across Europe, and deployed over 5,000 electrolyzers to decarbonize power, mobility, and industry. Now, she’s bringing that same intensity and optimism to Fifty Years UK—helping scientists in the 5050 program turn deep tech ideas into startups that can bend the arc of the climate crisis.

Souvid Datta is our in-house worldbuilder. A director, screenwriter, and creative force behind award-winning films at Cannes and Sundance London, he’s helped tech giants, charities, and broadcasters tell stories that matter. At Fifty Years, Souvid helps founders craft the kind of compelling, human-centered narratives that break through the noise. He’s here to bring deep tech into the cultural spotlight, inspiring us all to aim higher.

Kim Tieu is the operational heart of Fifty Years UK. She’s a seasoned Executive Assistant who brings calm to the chaos, clarity to complexity, and a steady hand to a fast-moving mission. With a background in creative writing and a home base that’s spanned four continents, Kim brings sharp organization and unwavering energy to everything we do.

We’ll also be adding a head of talent to the team. If that’s you, reach out!

We couldn’t be more optimistic about the future of the UK. We’ve already kicked off 5050 UK Cohort 1 and the talent and entrepreneurial energy is incredible. In partnership with ARIA, we’ll be running two UK 5050 cohorts a year, empowering UK scientists and engineers to build the next generation of civilizationally important startups. Beyond 5050, we’ll soon be rolling out additional programs and initiatives in the UK to fuel scientific innovation and entrepreneurship (stay tuned!).

Fifty Years gets its name from an essay written in 1931 by Winston Churchill. In Fifty Years Hence, he predicted nuclear power, cultivated meat, genetic engineering, robotics, mobile phones, and more. In times of rapidly accelerating technological progress, the essay also calls upon technologists to be ethical leaders, and deeply consider the societal impact of what and how they build. Given our namesake, this feels in many ways like a homecoming.

50Y 🤝 UK

The UK is a global powerhouse of invention.

Penicillin, DNA’s double helix, MRIs, monoclonal antibodies, the electric motor, the telephone, and the World Wide Web were all invented or discovered by brilliant UK minds. Yet, none of those inventions were successfully commercialised in the UK. Not one.

This is not a new story. In 1966, Charles Kao, a PhD from UCL, was working at Standard Telecommunication Laboratories in Essex, researching the potential of glass for optical communication. Everyone deemed glass a hopeless medium: light would scatter and fade too quickly for practical telecoms.

Kao discovered, however, that if he could purify glass fibers enough, they could carry huge amounts of data over vast distances with minimal signal loss. The problem: to replace the standard of the day – copper wires – he’d need to slash signal loss from a whopping 1000 decibels per kilometer to 20, a decrease by a factor of 10^98. It seemed an impossible task.

Kao struggled to find anyone to fund this effort until John Bray, the newly appointed research director at the British Post Office, recognized the potential. He funded the research and Kao was successful in demonstrating the potential of communicating over long distances using light in fiber optic cables.

But it was an engineer who heard about Kao’s work on a visit from America – William Shaver from Corning Glass Works – who commercialised it. The Corning team he assembled used a 2000°C oven from the company’s semiconductor arm to produce a fiber with 17 dB/km loss. By 1972, they hit 4 dB/km – low enough to enable the internet.

Corning's first commercial fiber optic system was deployed in Long Beach, California in 1977. Kao received the Nobel Prize in Physics, but it was a US industrial conglomerate, not its inventor, that turned this innovation into the backbone of global communication.

It was a variation on a well-worn theme. Britain invents the future – then others go build it.

This pattern is primed to be broken. At Fifty Years, we think we can help. Since 2015, we’ve backed over 100 deep tech startups and helped them raise over $4.6B in funding. We’ve built deep tech companies ourselves. The Spinout Playbook, which we published last year, is widely used by academic founders.

We've distilled everything we know about deep tech entrepreneurship into 5050, our free, 16-week programme to help great scientists and engineers become great deep tech founders. We’re excited to bring 5050 to the UK in partnership with ARIA, a new government R&D funding agency built to unlock scientific and technological breakthroughs.

The 5050 programme answers the following questions:

• Is this technology ready to be commercialised?

• Can this startup become civilisationally important?

• What do I need to make a startup idea work?

• How do I recruit a world-class team?

• Am I ready to be a founder?

Through 5050, participants:

• Zero in on civilisation-scale problems to tackle.

• Develop the essential entrepreneurship skills to grow into great founders. 

• Learn the critical components of building a deep tech startup, from recruiting to fundraising to negotiating IP rights.

In just four cohorts, 5050 has helped launch 45 companies, many of which would have never existed otherwise. Chi Zhang and Tay Shin, for example, joined 5050 as postdocs at MIT. They did not believe their science was ready to commercialised or that they were ready to become founders. 5050 helped them discover they had the traits that make great founders. After a 12-year academic career, they spun a startup out of MIT halfway through the programme.

5050 participants not only get a crash course in how to turn their research into a deep tech startup – from techno-economic analyses of their technology to breaking down ideas into fundable milestones – they also join a deeply-supportive community of scientists from leading labs, engineers from companies like SpaceX and Tesla, and 5050 alumni, many of whom are now founders eager to share their experiences.

The UK is suffused with talent, technical brilliance, and creativity. Our goal is to inspire and equip scientists and engineers in the UK to build the next decade of civilisation-defining companies. To break with the patterns of old.

Britain invents the future. We think it should be built and scaled on these shores as well.

If you’re a scientist or engineer curious about entrepreneurship, sign up to hear when applications open. If you know someone who should join 5050, recommend them or send them this post!

If you want to help us build 5050 UK, we’re hiring! Drop us a note at hello AT fiftyyears.com

Every so often, a technology shifts the arc of human civilization: the transistor, recombinant DNA, the Altair 8800. The significance of such inventions is often recognized only in retrospect, except by a small group who see the potential and rush to build the future. These are the founders who quietly spark revolutions.

At 50Y, we want to massively increase the number of startups sparking revolutions. Brilliant scientists and engineers have the potential to found civilization-bending companies, but they lack the skills, knowledge, and network to build them. That’s why we built 5050, a program to help scientists and engineers start indispensable companies.

We know deep tech. We’ve built deep tech companies ourselves. We’ve backed over 100 deep tech companies from the earliest stages and helped them raise over 5 billion dollars. We've helped our founders achieve many firsts:

• the first carbon-negative molecule factory

• the first cultivated meat approved in the U.S. 

• the first microgeo satellite for internet connectivity

• the first in-orbit space factory that manufactured pharmaceutical drugs

• the first de novo synthesis of a 1000+ base DNA molecule

• And many more

We supported these founders from the very beginning. We backed John Gedmark and Ryan McLinko when Astranis was just an idea on a whiteboard. They've now launched satellites, closed ~1 billion dollars in contracted revenue, and are on the path to connecting 3 billion people to the internet. 

We backed Sean Hunt and Gaurab Chakrabarti when they had just built a janky prototype reactor with wood, PVC pipes, and zip ties from Home Depot. Solugen has now built a 63 foot tall carbon-negative molecule factory that offsets over 30,000 tons of CO2 a year and is on the path to decarbonizing 90% of the chemicals humanity needs.

We started supporting Mark Budde when he was still a postdoc at Caltech, researching mammalian synthetic cell circuits. We helped him realize the workflows he built to speed up his research could help accelerate every biologist’s work. He set up a shack in his backyard and began delivering overnight plasmid sequencing. Two years later, Plasmidsaurus is the fastest-growing startup we’ve ever seen, serving scientists across 49 states and the UK.

The usual SaaS startup playbook doesn’t work for deep tech. “Move fast and break things” works in software because you can always roll back to a prior version. In hardware, you can’t ship if a core component is faulty. Software startup best practices don’t apply when you’re building nuclear reactors or bioengineering cell therapies. We’ve distilled everything we know about deep tech entrepreneurship into 5050, our free program to help scientists and engineers start indispensable companies.

The program consists of two phases. The first phase, Explore, helps answer the following questions: How do I turn my breakthrough science into a business? What do I need to make a startup idea work? How do I recruit a world-class team? Am I ready to be a founder?

At the end of Explore, those ready to build a startup will be invited to the next phase, Build. Build will help future founders de-risk their technology, hit milestones, raise a first round, and reach takeoff speed faster than they think is possible. They’ll learn everything they need to know about starting a deep tech company and what it takes to become a world class entrepreneur.

In our first cohort, 15 companies were started by the 50 scientists and engineers who went through the program. All of them raised their first round of funding. Cohort two and three are off to even stronger starts. 5050 will spark founders to build the next decade of civilization-bending companies.

If you want to start an indispensable company, apply to 5050. If you know an incredible scientist, engineer, or recovering SaaS founder, recommend them or send them this post!

Applications are open: www.fiftyyears.com/5050

Our lives are unfathomably better today than they were just a century ago thanks to breakthroughs in energy, materials, bioengineering, transportation, computation, communications, and more. This progress defines modern life. How we commute, how we communicate, and whether we’re healthy are defined by technological breakthroughs.

These transformative innovations have led to more abundance. Food, energy, and aluminum are 80-90% cheaper than in the late 1800s, air travel is 7X cheaper than in 1950, computing is 10 trillion times cheaper per calculation than in the 1940s, and communication is 10 million times cheaper per megabyte than in the mid 90s.

But in startup land, a huge percentage of people are now focused on progress within the same few small areas, like SaaS or low-code dev tools. This overconcentration comes at an enormous cost: brilliant people who could build the next massive leap forward are instead grinding out incremental innovations that others would have soon found. For example, the number of startups competing for customers in a single $50B market can vary by a factor of almost 1,000!1 We wondered what a modern treasure map would look like, but for startup opportunities.

To answer that question, we’re launching our first attempt at the list of Top Underfunded Opportunities: massive markets with little startup investment and ripe conditions for disruption. Based on our analysis, we selected five – sometimes counterintuitive! – progress areas based on their Opportunity Ratio: the U.S. market size divided by the total invested in startups in that market, as well as any key enabling technologies or macro tailwinds.2 Here’s what the numbers tell us:

Let’s talk about the (paper) elephant in the room. The top opportunities on this list were counterintuitive, even to us! Coming in at a ratio of $15,400 of spending for every $1 invested is paper products. It turns out that we buy a lot of paper: from disposable tissue paper, toilet paper, and paper towels, to the cardboard used to ship every ecommerce delivery. Very little has been done to imagine better forms of paper or better ways to make paper than (slowly) growing trees, chopping them down, and then squeezing them into thin sheets. What if we could use bioengineering to grow paper directly, without the trees? It could be a big win for energy efficiency, land use, the environment, and the entrepreneurs & scientists who figure it out. You can tell similar stories about the potential for reimagining other top opportunities on our list, like plastics, chemicals, housing, and education.

Paper might not seem sexy but improving the methods of production of paper would be a huge deal. It might seem odd for a hard tech investor like 50Y to be highlighting the unusual ratio of spend to startup investment in the paper industry, but the numbers don’t lie! 

Besides sharing some top opportunity areas, we’re also highlighting a few where the ratios are particularly bad. These are oversaturated markets where many founders fail by competing to solve low impact problems in similar ways.

The overconcentration of startups working on SaaS, marketing software, and low-code tools leads to low opportunity ratios. Even if you expect a new startup solution to outperform others and these industries to grow rapidly, the resulting impact on the economy would be comparatively very small.

The full Treasure Map of opportunities is much bigger and we hope to share more about it soon, as well as many open source datasets that our community has helped to gather along the way. This is a rough first pass at quantifying high-leverage areas to build. If you’re interested in exploring counterfactual opportunities like these or contributing to the Progress Index effort, sign up to be the first to hear when we post the full map!

At Fifty Years, we’re long-term optimists backing breakthrough founders. The 50Y Progress Index is our attempt at assessing how technology can shape the next fifty years. We believe that progress compounds and technology, thoughtfully stewarded, can uplift the prosperity of all.

The world is drowning in scientific research. Over 2 million scientific papers are published each year. That’s 5,500 per day! If you worked 24 hours a day with no breaks, you’d have to read 1 paper every 16 seconds just to keep up. That’s a new theory on solar geoengineering, a new AI technique, a new way of engineering proteins, a new approach to treating cancer, every 16 seconds. 

This unprecedented rate of discovery is an unqualified good. Every modern marvel, from the phone in your hand to the internet delivering you this post to the medicine you take, started as a science experiment. Fundamental research is the fuel of human progress and the discoveries are accelerating. Today more PhD’s are toiling and more money is being spent on research than at any point in human history.   

The problem, however, is that the explosion in research has not led to a proportional surge in breakthrough products or inventions — most notably in pharmaceuticals. While there have been incredible advances in fields like autonomous vehicles, quantum computing, and longevity, in many other areas the gains are less profound, require greater resources, take longer, and cost more to produce than they used to.

This dynamic has many facets, but it starts with the “too much research problem.” The first step in any experiment is the literature review. This is a tedious, painstaking process by which a researcher sets out to first understand a problem, what work has been done before, the questions that have been answered, the ones that haven’t, and to begin to think about how one might structure an experiment in virgin territory to fill in any gaps. 

This winnowing process, typically, relies on tools such as Google Scholar, which procure lists of PDFs of previous papers — some of them relevant, many of them not — based on basic keyword searches. These must then be read assiduously, and will often lead to new strands as a researcher follows a citation to a new paper, which in turn leads to another, and another. In a world where new papers pop up every 16 seconds, this winnowing process is hugely time-consuming and deeply inefficient. The problem of information overload is a giant speed bump on the road to progress. A survey back in 2016, when academic output was 40% lower than today, found that researchers spent at least 7 hours per week simply looking for information — ~20% of their work week!

What if there was a way to use AI to automate not just that first, painful step, but much of the rest of the process of scientific discovery as well? What if we could hand every bioengineer and economist and physicist a superpower that unshackles them from the drudgery that slows down their work and delays human progress? 

Enter Elicit, which has developed an AI assistant that leverages large language models to automate research. The spinout from Ought, a nonprofit research lab, launched the first version of its product two years ago and has by word-of-mouth alone built up a monthly user base of 200,000 researchers, ranging from MIT and Stanford scientists to researchers at industry leaders like Novartis, Genentech, and OpenAI. 

Elicit has built one-click literature review. And it’s working. Elicit’s language model responds to natural language prompts — "What are all of the effects of creatine?" or "What are all of the datasets that have been used to study solar geoengineering?” — to produce and summarize relevant papers. The results are based not on keywords but on concepts, and often link research from other disciplines that traditional searches would miss. In a pilot project, researchers using Elicit halved the time and cost of data extraction and analysis that today is still done by hand.

This isn’t easy (just ask Meta). Hallucinations plague LLMs. If you’re creating an image or writing marketing copy, a hallucination every now and then is annoying but tolerable. But if you’re going to invest tens of millions of dollars to develop a new cancer therapy based on LLM output, hallucinations are a gamestopper. To overcome this, the Elicit team pioneered iterated task decomposition, a new approach to language model deployment. This technique breaks complex tasks into more easily understood pieces, which then allow for statistical guarantees for each piece. By doing so, Elicit gets more understanding of how often different models hallucinate and in what context, which allows better checking. By forging new ground on Process Supervision, Elicit is able to uniquely synthesize vast quantities of scientific data without falling prey to one of the more hilarious and annoying failure modes of LLMs — confidently claiming something as fact that’s absolutely not the case.

Literature review at warp speed is just the beginning. Once a literature review is done, researchers must often then carry out a systemic review process, also known as meta-analysis. This is a deeper-dive that yields a rigorous empirical examination of the chosen domain of inquiry. The process, which leads to a written manuscript, typically takes five researchers 41 weeks to complete. Elicit will soon automate this as well. 

Elicit is building the power loom of scientific inquiry — a system that turns inefficient, hours-long processes into tasks that can be handled in an instant. In this dawning age of artificial intelligence, Elicit is pioneering a new paradigm in which thinking and reasoning will, increasingly, move from the human mind to machines. If today Elicit can automate the brute force task of plowing through the world’s compendium of scientific knowledge, it’s not hard to imagine a future where it becomes a true co-pilot — a thought partner to the world’s greatest minds that helps devise experiments to test a given hypothesis.

Imagine one wanted to know if metformin could treat Alzheimer's. With a click, Elicit can find and summarize all the relevant research. It will soon be able to create a meta-analysis that synthesizes all the studies into a full picture of what’s known to date. If a researcher decided things looked promising, today they’d assemble a team to design experiments and clinical trials to prove or disprove their hypothesis. This is extremely time consuming and expensive. In the future, one could imagine Elicit handles that as well. From a curiosity to a literature review to a meta-analysis to fully designed experiments — something that would today take a team of researchers many months could be done by a single person in hours. That would radically accelerate scientific discovery.

This is the future that Elicit co-founder & CEO Andreas Stuhlmüller has been thinking about since he was a teenager building chatbots with QBasic. And he’s well prepared for the challenge — he holds a PhD in Cognitive Science from MIT, was a Computational Cognitive Science postdoc researcher at Stanford, and co-created WebPPL, a programming language for probabilistic machine learning. In 2017 he started Ought, an AI research nonprofit, to address the concern that this powerful technology would primarily be used for unimportant things like meme generation or stock trading. He wanted to use AI to advance human knowledge, propel science, and influence policy for the better. 

To start Elicit, Andreas teamed up with co-founder Jungwon Byun, who holds an economics degree from Yale and has long been focused on maximizing positive impact. This focus led her first to microfinance in Africa and then to Upstart, where she was head of growth in the years leading up to its IPO. Lured by a shared passion to use artificial intelligence for societal good, she joined Andreas at Ought, which then spun out Elicit as a public benefit corporation. 

Together, they have built the tools to supercharge the scientific endeavor. The vision, however, goes much further. As Andreas says, "Over the next 3 to 30 years, AI systems will have the capacity to do human-like reasoning at superhuman quality and quantity, leading to a radical shift in our society, with most thinking happening in machines instead of human brains." Elicit wants to massively scale up good reasoning.

At Fifty Years, our sweet spot is supporting founders at the earliest stages of building deep tech companies that can generate huge financial outcomes and create massive positive impact.

1. Deep Tech: Preventing hallucinations is hard. The Elicit team has pioneered new approaches in AI like iterated task decomposition to do this. By building the critical infrastructure of the AI-enabled research age, Elicit will accelerate the entire scientific endeavor.

2. $1B yearly revenue potential: Big Pharma alone spends hundreds of billions of dollars on research and development and is desperate for technologies to make that money go further. This is in addition to the countless university researchers and industry leaders in semiconductors, energy, materials science, and beyond who are all bedeviled by the same problem: the slow, expensive, by-hand processes that are the foundation of all research.  

3. Massive positive societal impact: Elicit is making research systematic, transparent, and unbounded:

   1. Systematic: They’re running batch processing over millions of papers.

   2. Transparent: They’re taking the best practices in people’s heads and transforming them into software that can be shared and improved.

   3. Unbounded: They’re turning static PDFs into living models that anyone can extend and customize.

   Human progress is a story of technological and scientific advancements going back to harnessing fire and crafting stone tools. Fundamental research is the driver of those advances today and Elicit is bestowing practitioners of this vital work with superpowers that will unleash a new age of breakthroughs. 

Inspired by Elicit’s vision and execution, Fifty Years was proud to lead their seed round along with Fifty Years LPs Arash Ferdowsi, co-founder of Dropbox, Tom Preston-Werner, co-founder of Github, Ilkka Paananen, co-founder of Supercell, and Jeff Dean, Chief Scientist at Google, as well as Basis Set Ventures and angels like Thomas Ebeling, the former CEO of Novartis. We look forward to working with Andreas and Jungwon as they build the warp drive for research.

Scott is one of the most successful and experienced AI entrepreneurs. He founded Vicarious in 2010 to build AGI because he reasoned it was the highest reward-to-effort idea that could make humanity better. At the time, AI was deeply unpopular – AlexNet had yet to exist, the ecosystem was deep in another AI winter, and no one was funding AI companies.

Against tough headwinds, Scott got to work. He and his co-founder Dileep George assembled a small team to build the first AI that could solve any Captcha. They then beat DeepMind at Atari, including adversarial versions of games that demonstrated the Vicarious AI was learning cause and effect. Over the course of a decade, Scott raised $250M from iconic entrepreneurs like Dustin Muskovitz, Mark Zuckerberg, Jeff Bezos, and Elon Musk, and some of the biggest names in deep tech VC, like Founders Fund, 8VC, DCVC, and Khosla Ventures. They pioneered AI systems that learn and reason like humans while scaling an AI + robotics business for manufacturing and logistics. In 2022, Scott and his co-founder led Vicarious to a successful acquisition by Alphabet and spent a year integrating the company with Intrinsic and DeepMind.

Over Scott’s time building Vicarious, AI went from an academic niche to one of the most explosive new engines for economic growth. And so, the world no longer needed Scott to evangelize the promise and power of AI. Enter Fifty Years.

We met Scott shortly after he left Google and hit it off right away. We were impressed by Scott’s deep desire to make the world a better place. He’s pushed us to dream bigger. When talking about achieving Fifty Years’ mission of solving the world’s biggest problems with technology entrepreneurship, he asked us: How many founders a year could start such an impactful company? When we did the math, we estimated more than 10,000 people a year have what it takes to be such a founder (it’s a fun Fermi problem we’ll share later!). That’s 300x more people than we back in a year. Scott immediately took it as his next ten year quest to close the gap between founders who could start a deep tech company and those who actually do.

That kind of ambition only matters if you’re willing to work. Scott wants to spend his energy battling the ugly inertia dragging the world towards dystopia and despondency. He believes, like us, that empowering founders is the best way to pull forward the future we all need. We’re amazed at the degree to which Scott leans into the less glamorous parts of the job, especially helping founders navigate difficult challenges. He embodies the Fifty Years Founders First culture.

He’s been instrumental at helping 50Y portfolio founders hone in on great 15 minute pitches and work through hard strategic decisions, calling in the best experts in his network to iron out the gritty details. Scott brings a special intensity and energy when working with founders and is able to elicit self-belief out of everyone in the room. The harder and messier the situation, the more he leans in. Often, when he’d suggest a solution, the rest of our team would think “I wish I’d thought of that!” We couldn’t imagine a better builder and ally to our founders.

Scott will have a broad focus at Fifty Years, including AI but not limited to it. Deep tech is as important for AI as AI is for deep tech. You have pioneering companies like Nvidia and other material science companies that are going to be essential for the future of AI. And now you have AI companies that are pushing forward what’s possible in materials science, space, biology, energy, and more. There’s a virtuous cycle and, at Fifty Years, Scott can help accelerate from both directions.

To manifest the full potential of AI to help humanity thrive, we need to advance core capabilities and apply AI to things like unlimited clean energy, the end of aging, accelerated science, and other future goods. We don't just want the AI computer from Star Trek, we want it all – warp drives, advanced medicine, the replicator. At Fifty Years, we're helping founders build the Star Trek future. All of it.

We’re excited to make history with Scott and can’t wait to share more of what we’re building together at Fifty Years.

It started over a game of poker.

Sean Hunt, a PhD candidate in chemical engineering, was puzzling over how to make metal catalysts cheaper for chemical manufacturing. Gaurab Chakrabarti, an MD/PhD in training, was working on an enzyme in cancer cells that naturally produced high concentrations of hydrogen peroxide. They happened to sit across from each other at the poker table one night — and the possibility dawned on them. 

Could they combine their efforts to harness these biological processes, already happening in hyperdrive in cancer cells, for large-scale chemical production?

Seven years later, Solugen, the project hatched in that friendly game of cards, is a $2 billion startup. The company has pioneered a groundbreaking approach that leverages biology to produce carbon-negative chemicals and has charted a path toward decarbonizing the global chemicals industry.

Solugen is the exception, not the rule. It’s the type of ambitious scientific idea that rarely gets off the ground due to a funding gap for translational science. 

Sean and Gaurab have set their sights on a very big target. The chemical industry fuels the global economy but it primarily relies on oil and natural gas as its feedstocks, making it one of the hardest industries to clean up. Chemicals production generates at least 925 million metric tonnes of CO2 emissions annually, or more than 2% of anthropogenic CO2 emissions. 

The scientists needed a proof of concept to show their idea had commercial potential. But they faced a problem that has defeated thousands of researchers just like them. Grant financing would take too long to access (up to 20 months!). Venture capitalists are not interested in funding such risky science experiments. 

Sean and Gaurab didn’t need much: just enough money to test whether the basic science was translatable to the real world. Bereft of options, they entered the MIT Entrepreneurship Competition (open only to MIT students) and landed second place, winning $10,000. They used that cash to build their first reactor with materials bought in a Home Depot: wood, PVC pipes, and zip ties. It worked, and became the first iteration of Bioforge: an enzyme-powered chemical plant that could produce high-value chemicals without fossil fuels. 

Today, Solugen operates a 20,000 sq. ft Bioforge in Houston, Texas, is offsetting over 30,000 tons of CO2 a year, and is on track to decarbonize over 90% of the chemicals humanity needs.

That first $10,000 check was vital for Solugen. But scattered university contests are not a solution. Right now, thousands of researchers are working on innovative solutions to the climate crisis, disease, and other big problems. Only a few will get the opportunity to test whether their idea can be turned into a product or process that, just maybe, could change the world. 

We built Manifest Grants to bridge that gap. Manifest Grants is a fast grants program awarding $25,000 to $100,000 to scientists to accelerate their most ambitious ideas. The application takes 30 minutes to complete and applicants get a decision within 21 days. No IP is taken.

On August 1st, alongside EQT Foundation and Automattic, we launched Manifest Climate Round 1 to accelerate bio x climate research. Any academic scientist (PI, PhD, Postdoc) working on a bio x climate solution can apply at fiftyyears.com/manifest. The applications close on August 31st at 11:59 pm (PT). 

Our goal is simple: to give the most innovative ideas a fighting chance to move from the lab bench to the real world. By offering funding for that critical next step, from prototyping and techno-economic modeling to real-world testing, a new generation of innovators can determine whether their ideas translate to the market. 

How many Solugens is the world missing out on because there are few avenues for scientists to quickly test their ideas? We want to back all potential Seans and Gaurabs out there and accelerate the next generation of scientists solving the world’s biggest problems. If that sounds like you, apply! The world needs you.

A product launch video from a VC firm? 🧐

Giving our founders the support they need requires a different kind of VC firm. Not one that operates like a law firm, but one that runs like the startups we back. They need a partner that builds.

In the video below, we’re excited to give you an inside look at some of the things we’ve been building at Fifty Years.

You’ll hear from a few members of the Fifty Years team, folks like George Church, the father of synthetic biology, Tom Preston-Werner, the founding CEO of Github, and everyone’s favorite CEO of Pied Piper (yes, really 😉).

We've never been more optimistic about the future. From the climate crisis to disease to connectivity to inequality to aging, Fifty Years portfolio founders are building solutions to all these things. And they won't stop there. Their work will bring us a future of sustainable abundance, good health for everyone, and a connected and thriving world.

These are important things, and we take our responsibility to support our founders seriously. Our goal is to help them manifest their visions for a better world. We feel a fierce urgency in helping these founders build better and move faster. 

If a marketing startup is delayed in launching, the business might suffer but people won’t. Our founders are helping stop the climate crisis, connect the world, cure cancer. Some are developing therapeutics for untreatable diseases. Every week sooner they get to market is real lives saved — families that get to celebrate healing instead of mourning loss.

To best help founders solving the world’s biggest problems, we need to build. We're excited to, for the first time, show you some of the things we've been building.

We introduce:

• Fifty Years Network: software to 50x our founders' networks

• Fifty 50: programs to help great scientists become great founders

• The Paperscraper: an LLM-powered tool for staying on top of the latest scientific research

• The Spinout Playbook: the go-to guide for spinning out of a university

• The League of Giants: a superpowered LP base

• Manifest Grants: a philanthropic granting program for translational science

We’re proud of all we’ve built to better support founders solving the world’s biggest problems. There’s a lot more to come.

At its peak, Viagra generated $2 billion in annual sales. After its fast rising debut in 1998, it gained market share more quickly than nearly any prescription in history. In the two decades since, Viagra has racked up tens of billions of dollars in revenue and become ubiquitous in culture for men getting their mojo back. 

Female sexual dysfunction drugs have not fared as well. The first medication, Addyi (flibanserin), was approved by the FDA 17 years after Viagra hit the market. Despite fervent anticipation, sales totaled only $8 million. Why was Addyi such a let-down?

It certainly wasn’t due to a smaller market size. In fact, the market for women is larger. While only 1 in 10 men report experiencing issues with sexual arousal, for women the number is twice as high. Nor was it because of a lack of funding from capital markets. The day after the FDA approval, Valeant acquired Addyi for $1 billion.

The reason Addyi didn’t become a commercial success is the same one that disadvantages the entire femtech arena: a lack of robust early-stage science and therefore good products. While Viagra affected well-understood mechanics of male erectile dysfunction – relaxing blood vessels of the penis to cause an erection – Addyi aimed to do something more difficult by stimulating the brain to ignite sexual desire. The neurobiology of sexual desire is scarcely understood, to the extent that even the drug developer couldn’t articulate the exact mechanism by which Addyi worked. As a result, the drug had such a low efficacy (and excessive side effects) that the FDA had twice rejected it from entering the market. In the clinical trials, a woman using Addyi on average had one more “satisfying sexual encounter” per month, in comparison to those on a placebo. Not much of an improvement for a drug that came with the hefty price tag of $800 per month (2x the price of Viagra) and a long list of serious side effects.

Why is science hindering women’s health companies?

Simply put, we’ve just recently started studying female bodies. It was only in 1993 that the National Institutes of Health (NIH), mandated women to be included in clinical trials. Before that, the male body was the “medical norm”, with almost all medical research – including drug and diagnostic development – conducted exclusively on male bodies. Despite clear evidence showing sex differences in how bodies break down drugs. In 2016, the NIH revised the policy to include pre-clinical research and specified that researchers should acknowledge sex differences and run basic science experiments on both male and female mice. Until 6 years ago, a researcher could treat female reproductive organs and the hormonal cycle as either irrelevant or confounding variables when developing biological knowledge and medical know-how.

Yet even with these changes, women’s health attracts only a minuscule percentage of all science funding. In 2019, about 11% of all NIH funding went to conditions that solely, differentially, or disproportionately affected women. A recent study confirmed these results: in 3 out of 4 cases where a disease afflicts primarily one sex the funding patterns favor men. In 2019 alone, there were 5.8 times as many publications on erectile dysfunction than all of female infertility.1

If our legacy systems won’t fund the early-stage science then we’ll have to. That’s why we launched Repro Grants, a ‘fast grants’ style program to accelerate female reproductive science. We’ve brought together leading researchers to award $25-100K to the most ambitious and novel research projects from menstrual health to menopause. These grants are purely philanthropic and no strings attached – and come with no claims whatsoever to any IP. 

Modeled after Impetus and Fast Grants, the application takes 30 minutes to complete and applicants get a decision within 21 days. In the last 3 weeks, we’ve received over 140 proposals from leading universities across the globe. The applications close this Saturday on 17th of December at 11.59 (PT)!

We’re excited to fund the next generation of scientists. Because where only a few have gone, a lot is left to discover. Will we decode the sources of 1 million (per year) miscarriages and alleviate heartache from expecting families? Will we uncover the fountain of youth by deciphering the signaling pathways of rapidly aging ovaries? Will we unlock potential cures for dreadful endocrine conditions like endometriosis? 

We just might! But what is certain: as long as we fail to fund research at the earliest, most fundamental levels, we cannot expect to magically deliver safe, effective, and life-saving products for women. If we succeed at bridging the research gap, the world will look drastically better. Our aspiration for Repro Grants is for it to not only improve the well-being and health of half of the world’s population but also fund a future Nobel laureate or two.

— 

Thank you to our founding donors for catalyzing this program! 🙏 We’re raising up to $1 million more in philanthropic donations to support breakthrough science in female reproductive health. You can support our efforts by reaching out to sara@reprogrants.org.

The earliest written record of medical therapeutics is the Ebers Papyrus, a 20-meter-long, 110-page medical scroll that describes how to mix herbs, shrubs, leaves, minerals, and animal poop to cure depression, diabetes – or even destroy disease-causing demons!

It's safe to assume the FDA wouldn't approve all of these ancient Egyptian treatments! However, the papyrus did contain the first ever blockbuster drug: willow bark as a general pain reliever, though its route to market was a bit circuitous. 3,500 years after the Ebers Papyrus, Reverend Edward Stone, a clergyman from Oxfordshire, dried willow bark and pounded it into a powder to cure 50 people of “aguish and intermitting disorders” (i.e., fever). It took another hundred years before chemists at Bayer purified and acetylated the active chemical in willow bark, salicylic acid, and gave it the marketing name Aspirin. With aspirin, Bayer supercharged the nascent industry of pharmaceuticals, and within two decades, aspirin was one of the most popular drugs in the world.

Soon after the success of aspirin, Bayer started pioneering synthetic and rational drug discovery methods. Chemists at Bayer realized that making simple modifications to synthetic chemical structures could produce novel therapeutics. Starting with barbital (a sleep-inducing drug) they swapped a moiety (ethyl → phenyl) to create phenobarbital, an effective treatment for epilepsy that is still used today. This sparked the era of drug discovery – a mad dash to find therapeutics by chemically modifying synthetic compounds (the ‘methyl, ethyl, propyl’ era that tested variations in structure). As our understanding of biology grew, drug design started targeting specific proteins in order to solve diseases (protein–ligand). Eventually, we created libraries of molecules and screened them for activity against key enzymes in the body (‘throw them at the wall and see what sticks’). Thirty years ago, our tools and computational ability finally allowed us to rationally design drugs based on protein structure (the first unequivocal example of a rational drug design was dorzolamide in 1995). This is the current paradigm of drug discovery – one drug for one target to cure one disease.

Unfortunately, the human body is a bit like 4 billion years of accumulated spaghetti code; diseases caused by just one misbehaving enzyme aren’t typical. Take cancer for example. It might take up to 10 mutations before a cell turns cancerous, and this process might dysregulate the expression of hundreds of proteins. Designing a drug to target just one misbehaving protein is tremendously difficult – there are only 812 proteins with approved therapies out of the ~20,000 in the human proteome. Taking multiple drugs to target the multiple mutations for something as complicated as cancer is dangerous – only so many drugs can be stacked before the liver becomes permanently damaged.

Kinases are the perfect example of spaghetti code. Kinases take phosphates from biology’s energy molecule, ATP, and attach them to specific amino acids like serine, tyrosine, and threonine. This is called phosphorylation. Tacking a phosphate group onto a protein causes the protein to change shape and affects how it interacts with water. Phosphorylation can also switch a protein from inactive to active or can change its function altogether. In the infinite wisdom of random walks, biology uses kinases – which turn proteins on and off – in highly conserved signaling cascades that control basic cellular functions. 

Kinase signal cascades can push cells to become cancerous. The most well-studied cascade is the MAPK cascade, which begins with a stress signal at the cell surface. This phosphorylates a bunch of kinases, which in turn phosphorylate more kinases, which go on to phosphorylate a bunch of other proteins, which then leads to changes in gene expression that promote cell proliferation, survival, and migration. This is why the mutation and subsequent dysregulation of kinases in the MAPK cascade can lead directly to cancer. Take BRAF, a kinase in the MAPK signal cascade. A mutated BRAF is found in 50% of melanomas and causes a 500-fold increase in phosphorylation for 60 other proteins. This single supercharged kinase tells the cell to never stop growing and to move around the body – the definition of cancer.

This is why kinase inhibitors can be such powerful tools in the fight against cancer. Scientists understood that BRAF mutation helps cause melanomas, so they designed drugs to inhibit BRAF mutation, resulting in drugs like vemurafenib, dabrafenib, and encorafenib. Unfortunately, kinase inhibitors muck with variables deep in the spaghetti code that is biology. Kinases don’t just phosphorylate other proteins, they also form structures with other proteins that function in other signaling cascades. By inhibiting one kinase, you naturally affect the other proteins which would normally form structures with the uninhibited kinase. This is called crosstalk. Often, kinase inhibitors inadvertently target similar proteins that come earlier in the cascade, amplifying the changes to the cell’s signaling, a phenomenon known as retroactivity. Crosstalk and retroactivity lead to the off-target effects that generate a different kind of bug in our spaghetti code. These bugs have terrible consequences for patients, like cardiotoxicity, hypertension, hypothyroidism, skin reactions, proteinuria, or even more cancer (as is the case with vemurafenib and dabrafanib to treat BRAF!). We deserve more from our kinase inhibitors.

Fortunately, there is a better way, and aspirin is the clue. Aspirin is actually a very special drug – it is extremely promiscuous. Aspirin has been predicted to target over 23 proteins. It’s serendipitously polypharmacological, and because of its numerous molecular targets, it is a treatment for cardiovascular protection, fever reduction, pain relief, and may also prevent cancer (thanks Egyptians!). It’s an example of a drug that is almost impossible to design from a rational, computationally based, first-principles approach. But what if we could design kinase inhibitors that affect only the parts of cascades we care about, while modifying the surrounding cascades to avoid those terrible off-target effects?

Enter Harmonic Discovery, who are designing drugs to inhibit multiple kinases in order to cure cancer, autoimmune dysfunctions, and neurological diseases. Their drug design approach considers, from the very beginning, the multiple kinases they want to inhibit, while specifically avoiding activity with the kinases that lead to side effects. Traditional drug design attempts to target just one kinase. Trying to consider multiple kinases would multiply the complexity, so finding a kinase inhibitor for A, B, C, D, and E while avoiding activity with F, G, H, I, J, and K would be much harder (let’s say 10x harder for argument’s sake) than just finding an inhibitor for A. Harmonic Discovery fundamentally compares the structures of these kinases to create a Venn diagram – they look for motifs that exist only in the desired targets and avoid motifs that are present in the off-targets. Considering only those two circles of the Venn diagram lowers the computational complexity of finding a ligand from 10x to 2x, turning the intractable into tractable. 

This is the exact insight that cofounder and CEO Rayees Rahman kept returning to during his PhD in Biophysics and System Pharmacology at the Icahn School of Medicine at Mount Sinai. He eventually realized that it is now computationally tractable to design drugs that specifically target multiple kinases and avoid off-target kinases. He pioneered the fundamental computational approach during his PhD. He then met cofounder and CSO Marcel Patek, a 25-year drug hunter veteran at Sanofi and Icagen, who immediately saw the potential to discover a new class of kinase inhibitors. Cofounder and COO, Jason Lee, who received his MD after having been a biotech banker at Deutsche Bank and investor at OrbiMed, also joined the team. Together, they’re building the next generation of computational drug discovery tools for multi-target drugs, enabling a world where we can rationally design more drugs like aspirin. With this platform, they aim to keep kinase inhibitors from creating random traffic jams and roadblocks in the cascade, so patients don’t inadvertently leave the hospital with a disease worse than the one that brought them to the hospital. Instead, Harmonic will have precision control of signals across the whole cascade, leading to extremely safe cures for currently intractable diseases.

At Fifty Years, our sweet spot is supporting founders at the earliest stages of building deep tech companies that can generate huge financial outcomes and create massive positive impact.

1. Deep tech: Harmonic Discovery is building the tools and approaches to support a new era of drug discovery, where one drug is designed for multiple targets. They’re starting with kinase inhibitor design in order to cure cancer. 

2. $1b yearly revenue potential: Harmonic Discovery’s first market is the design of kinase inhibitors, which is already a >$60B yearly marketplace.

3. Massive positive societal impact: Just like the first chemists at Bayer ushered in the era of pharmaceutical drug discovery that gave us sedatives, antibiotics, and even aspirin (!), Harmonic Discovery will usher in a new era of drug design based on targeting multiple chemical pathways at once.

Inspired by Harmonic Discovery’s vision and execution, we at Fifty Years were proud to join its Pre-Seed round led by Innovation Endeavors and are now excited to deepen our partnership in their Series Seed.

Alex has been our Chief of Staff for the last two years. During our CoS search, we talked to nearly 200 candidates. It got to the point where we started asking ourselves “have we set the bar too high?” And then we found Alex and knew we hadn’t. He was obviously the right person, both in terms of culture and skillset. After many conversations and referencing, we made Alex the offer and … he said no 😳

We got creative in solving some of his concerns (e.g., he just bought a house in Los Angeles and would need to relocate his family to San Francisco) and thought we were there and … he said no again 😵‍💫

We tell our portfolio founders that closing the best candidates often requires creative problem solving after getting an initial “no”, so we kept at it. We kept talking and problem solving. Knowing Alex was a huge fan of HBO’s Silicon Valley show, we called in the big guns.

And, finally, Alex said yes!

Alex now says that choice is “the best decision I ever made”. We feel the same way.

Over the last two years, Alex has embodied the Fifty Years values.

He puts our portfolio founders first in everything — whether it’s trudging through thousands of LinkedIn profiles to help fill a key role, or closing candidates (he’s helped close 7 out of 14 employees for one Fifty Years startup!), or physically helping build infrastructure on site.

Alex has a constant drive to level himself up. Every time a great book on entrepreneurship is mentioned in passing, within a couple weeks he’s bought and read it. He constantly asks “how can I do this better?”

Alex is relentlessly helpful. By the time you’ve started the question “Alex, can you help with—“ he’s already interrupted with a “yes!” Whether it’s project managing a major initiative to help a portfolio founder, jumping on a 20 hour flight to close a partnership, or sweeping the HQ floors before an event. He always puts the organization first and does what needs to get done.

Alex embodies the spirit of Silicon Valley hustle. Whether it’s jumping on a call with a potential hire at 10pm on a Friday night or dropping weekend plans to get something important done — Alex operates with incredible urgency and speed. His response time to a portfolio founder or teammate that needs him is typically measured in minutes — regardless of the time of day or day of the week.

As a previous founder himself, Alex also brings a founder mentality to his work at Fifty Years. He steps up proactively to level up our organization and our teammates.

And finally, Alex is a walking Happy Warrior. If you’ve met him, you know what we mean. His laughter can be heard from blocks away. His optimism and positivity are simply contagious and inspire those around him.

In Fifty Years fashion, we thought sharing this news with Alex was a perfect opportunity to simultaneously have some fun. So we told Alex we needed to go for a walk “to talk about your performance”. We then explained to Alex all the things mentioned above that he’s been doing extremely well and then said “BUT — you knew there was a but coming…” (tense pause!) and followed it up with happy news of more responsibility and more carry. We then asked for his feedback on some website updates. We had secretly updated his title to Partner and his reaction to seeing it is classic Alex 😂

We can’t wait to see how Alex continues to grow and how he continues to contribute now that he’s graduated from Chief of Staff to Partner!

Biopharma research scientists are a hearty bunch. They have to be because they face comically bad odds! 

For every new drug to make it to the promised land of FDA approval, another 10,000 have crashed somewhere along the way. This chasm – between the lab bench and the market – is known as “the valley of death”. Translating research potential into world-changing medicine is broken – but not for the reasons you might think. 

The science is, of course, exceedingly difficult. But funding can be even harder! Principal investigators at a university lab can spend two-thirds of their time writing grant proposals in the hopes that a government agency or private organization will see fit to hand them a bit of money until they need the next tranche. The result is a financing hamster wheel that distracts scientists from doing the science it’s meant to fund.

The incentive structure is also counterproductive. The frequency of papers published in academic journals acts as a measurement system for university researchers. This “publish or perish” paradigm means researchers spend an inordinate amount of time publishing – and less on researching new drugs. It also incentivizes scientists to guard the intellectual property they work so hard to develop, which can be self-defeating! Doing foundational biopharma research solo is like trying to climb Mount Everest without sherpas to guide you, without fellow mountaineers to catch you when you lose your footing. 

Take all those factors together, and those comically bad odds become much less mystifying. And it’s getting worse! The cost of getting a single drug to market has soared past $2 billion, while the average time has lengthened to 13 years. In fact, since the 1950s, the cost of developing a drug has doubled every nine years. Biopharma research is one of the few sectors where, as technology and tools improve, results have worsened. This is an unfortunate reality known as Eroom’s law. In short, biopharma research is more costly and slower than ever. It desperately needs innovation. 

Enter Molecule, a drug development marketplace built on Web3 primitives to open the floodgates to a new era of biopharma research that is faster, more equitable, and breaks the innovation logjam. Molecule does this by turning research projects into assets that can be sliced into fractions in the form of special non-fungible tokens (IP-NFTs) that can then be sold to raise funds. The potential of this approach is vast. Researchers can more easily fund their work and unlock more time to spend on actual science. Their backers, be they patients, investors, fellow researchers, or really anyone, receive an ownership stake in intellectual property that might, one day, yield a blockbuster drug.

NFTs are, at their heart, a new iteration of property rights that allow value to be created and moved fluidly around the web. Molecule’s core innovation is its intellectual property NFTs (IP-NFTs), which confer legal rights of ownership to research-generated IP. Importantly, they also create a standard, akin to what Y Combinator pioneered with its SAFE financing documents. SAFEs leveled the playing field between inexperienced founders and seasoned investors by creating a template for funding terms that both sides understood and accepted. The result: negotiations that could drag on for weeks were eliminated. Partnerships close quickly, with no lawyer involvement and on fair terms for all parties. 

IP-NFTs can do the same by catalyzing a new market in which any interested party can, say, buy an Alzheimer’s research NFT, or potential treatment for pancreatic cancer, or a Covid-19 vaccine! There are two natural extensions of the IP-NFT framework. One is the Molecule marketplace, where researchers can create profiles and pitch their projects to potential funders. The second one is Molecule’s launchpad for bio DAOs centered on areas of interest, from psychedelics to longevity.

DAOs are, effectively, engaged Web3 communities with a balance sheet. DAOs enabled by Molecule comprise patient groups, researchers, angel investors, and other enthusiasts & experts. These DAOs raise money by issuing tokens to members, who then vote on which research projects to support. The most prominent of the DAOs that Molecule is powering is VitaDAO, a collection of longevity enthusiasts who – among others – invested $250,000 in a project led by Dr Morten Schiebye-Knudsen at the University of Copenhagen. Morten’s group is researching whether widely available, off-patent drugs can reverse DNA damage, which correlates to a number of ageing-associated diseases, including arthritis and Alzheimer’s. The money, however, was just one benefit. The researchers were stymied. They screened compounds for effects on senescent cells but were not seeing useful results. Senescent cells increase with aging and hamper the ability of stem cells to regenerate, increasing the risk of numerous diseases. One of the researchers in the DAO, who was based 4,500 miles away in St. Louis, Missouri, suggested that they dramatically increase the threshold of compound concentration for which they were screening. Once altered, the researchers saw significant anti-senescent effects where previously they observed little. 

That’s just one example of Molecule’s big idea. Creating communities with skin-in-the-game in exchange for their support can spawn new levels of collaboration. It also has the potential to realign incentives that, today, often run counter to patient needs. Goldman Sachs laid this bare in 2018 when it published a report that questioned whether inventing “cures” was a good business model for biotechs. Focusing on treatments that must be taken on an ongoing basis – in effect, a subscription business – was perhaps more desirable, the bank said, than creating a drug that is so effective that it reduces the pool of potential patients! Now imagine if the “cure” was instead owned by patient groups. How differently would treatments be developed and deployed if those set to receive them had a say? The team at Molecule is building the ecosystem to make that possible. 

The team launched Molecule to massively accelerate biopharma research. Co-founder and chief executive Paul Kohlhaas is a serial entrepreneur who, as a student, took part in online biohacking communities of people who lacked access to medicines and resorted to making their own with imported raw materials. He later dove into crypto as a business development director at blockchain software company ConsenSys. Paul then started Linum Labs, a studio developing Web3 projects. He started Molecule with chief science officer Tyler Golato. Tyler saw first-hand how skewed incentives and poor processes undermined researchers and widened the valley of death. He experienced this misalignment at Columbia University Medical Center, where he researched experimental treatments for late-stage terminal cancer, and then at the NIH’s National Institute of Aging.

At Fifty Years, our sweet spot is supporting founders at the early stages of building deep tech companies that can generate huge financial outcomes and create massive positive impact.

1. Deep tech: Molecule is creating new infrastructure for bio innovation. They pioneered a novel legal framework to standardize and fractionalize intellectual property in the form of IP-NFTs. The result is a new form of preclinical biopharma crowdfunding that is faster, catalyzes collaboration, and gives a wide group of stakeholders a piece of the IP that might lead to a blockbuster drug. 

2. $1B yearly revenue potential: The pharmaceutical industry brings in about $1.2 trillion each year. No less than 88% of preclinical assets – the next generation of potential “blockbuster”, billion-dollar drugs – reside in academia and biotechs. This is where most of them stay. By making it dramatically easier for researchers to raise money and build communities of interested and invested collaborators, Molecule aims to ignite an explosion of innovation that yields the next generation of blockbuster treatments. 

3. Massive positive societal impact: As the global population hurtles toward 8 billion, the need for novel drugs and therapeutics is growing more acute. Yet the pace of biopharma innovation has slowed. Getting a single drug to market costs more and takes longer than ever before, leading to unnecessary human suffering. Molecule can reverse the decades-long decline of biopharma innovation by remaking how drugs are funded and developed. 

Fifty Years was proud to participate in Molecule’s seed round, which was led by Northpond Ventures and included Shine Capital, KdT Ventures, Backed.vc, 1kx, Balaji Srinivasan, The LAO, Compound, Koji Capital, Petri Bio, and Box Group. We are excited to help Molecule create a new research ecosystem that is more productive, equitable, and better for humanity. 

We’ve all been there. A splitting headache comes out of nowhere. You reach for the Tylenol, pop a couple pills, and down them with a glass of water. Ah, relief. The pain subsides. 

What you may not know, however, is that it may not have been the Tylenol that delivered you from misery, but the water. Dehydration headaches are incredibly common. Yet in our haste to reach for pharmacological intervention, we often ignore our body’s most elemental needs.  

This is a small example of an enormous problem. The West is blessed with the most advanced medicine the world has ever known. Doctors in Maryland recently transplanted a pig’s heart into a human body. Vaccines for a once-in-a-century pandemic were designed in days, rolled out within months, and saved millions of lives! 

Yet in the shadows of these advances, we’re failing to meet patients' most basic needs. They’re starving, and it is happening in the least likely of places: hospitals. 

Hospital malnutrition is rampant and it’s expected to get worse. It’s estimated that one-third of the 33 million people admitted to US hospitals each year are already suffering from malnutrition. Once there, another fifth can fall victim to the condition. 

The numbers are shocking but understandable once they’re picked apart. Virtually any time the body gets an infection, whether it’s a seasonal flu or COVID-19, or suffers trauma like a broken limb, its need for energy, proteins, vitamins, and minerals spikes. Yet intake of those vital fuels typically falls just when the body needs them most because of symptoms ranging from shock to reduced appetite and loss of bodily fluids. It’s a fact that’s often overlooked in the rush to treat the primary malady, contributing to underdiagnosis and lack of treatment. Only 5% - 9% of hospital patients are diagnosed with the condition, resulting in untold suffering, avoidable deaths, and billions of dollars in additional healthcare costs. 

Population demographics are also driving the problem. Every day, 10,000 baby boomers turn 65. That age bracket – the over-65’s – are the most prone to malnutrition. A host of age-related issues, from loss of appetite to incontinence and gastrointestinal conditions, lead to a lower intake or absorption of nutrients, loss of muscle mass and subcutaneous fat, and increased susceptibility to conditions that will land them in the hospital. Over-65’s are twice as likely as middle-aged people to have a hospital stay in a given year.

Once there, clinical interventions can put the body’s natural healing mechanisms under added duress. After surgery, a patient’s protein needs can double as the body heals. Ventilated COVID-19 patients may benefit from a higher fat diet because metabolizing fat generates less CO2, lightening the load on damaged lungs. Malnutrition deprives the body of the raw materials to power these vital processes. Matrix metalloproteinases, for example, are enzymes that help heal wounds. Their catalytic effect is powered by zinc, a lack of which can dramatically slow wound repair.

Studies found that those diagnosed with malnutrition have a three to five times higher risk of mortality during their hospital stay. And the problem is getting worse. 

Clinical nutrition is a relatively young science that’s in the process of being more deeply integrated into the chain of patient care. Most people, when they think of hospitals, think of doctors, nurses, orderlies, and pharmacists. Yet clinical dietitians play a central and growing role in delivering care that optimizes outcomes and speeds recovery. 

Standing in their way, however, is technology – or the lack of it. The growing complexity of care, paired with a rapidly-expanding population of patients who require it, has outpaced the current tools to handle the workload.

The nutrition director of one hospital group said that dietitians on his staff see half the patients each day that they did a decade ago because so much of their time is spent on patient charts. They must manually trawl through electronic health records to find at-risk patients, assess a greater number of factors once they find them, and then create a feeding plan that can change by the hour based on the treatments they provide. 

So intense are the demands that dietitians regularly resort to creating their own spreadsheet-based aids to speed their calculations, which they then share with colleagues. But these are imperfect, limited solutions. Clinical nutrition has been virtually untouched by the march of technology, and the result is rampant under-nourishment: a silent killer lurking in America’s hospitals.  

But what if there were a way to automate the monotonous, laborious aspects of this work? This would free up dietitians to spend time on what is most important: matching feeds to needs. 

Enter HealthLeap. The company has developed a digital assistant, called NutriLeap, which solves several problems at once. The app uses machine learning to enhance the assessment of a patient’s needs and suggests the mix of nutrients they require based on medical history, body measurements, lab results, and symptoms. By plugging directly into the hospital electronic health record system, it can flag patients who are showing more subtle signs of risk that a harried dietitian, nurse, or doctor might otherwise miss. It then helps dietitians to match the precise patient needs with an optimal combination of nutrition products (based on available stock), which can consist of hospital diets, oral supplements, tube feeds, or intravenous solutions. 

Typically, all of this work is done by hand: scanning charts to assess risk and carrying out complex manual calculations to come up with a precise plan for each patient. HealthLeap reduces those hours of arduous, painstaking work to seconds, unlocking a productivity revolution for dietitians while helping them deliver best-in-class treatment. 

Take the case of a person with acute kidney failure. The dietitian uses age, sex, weight, symptoms, type of dialysis, electrolytes, and other tests to determine the levels of protein, fluid, magnesium, phosphorous, and potassium their kidneys can handle. The patient's kidneys improve, say, over the space of a week, during which time the dietitian continually recalculates and adjusts the tube feed composition to match improving kidney function. At the same time, the patient might be transitioning back to an oral diet. That means more calculations to prescribe a reduction in tube feeding amounts and an increase in oral intake. 

HealthLeap’s recommendations get better over time. That’s because adjustments that dietitians make to its suggestions, the stream of studies and research that can influence clinical best practice, and patient health outcomes, are constantly fed into the algorithm. HealthLeap, in short, hands dietitians a superpower. Fewer patients will fall through the cracks, and those receiving treatment will be ensured a more optimal level of care.

Once patients leave the hospital, the app can also provide a critical bridge for aftercare, keeping them informed of their changing nutritional needs and providing a link to their dietitian. This is crucial to reducing hospital readmissions, a key incentive for hospitals because insurers can claw back reimbursements if certain patients are readmitted within 30 days of discharge. 

Longer-term, HealthLeap aims to become the fulcrum of a new era of nutrition research. While a growing body of academic studies have highlighted the importance of nutrition in hospital care, the field is ripe for further investigation. A key blocker, however, has been a paucity of accessible data. HealthLeap’s trove of patient data could become the key resource for future scientific exploration, while also delivering immediate benefit to millions of patients. 

HealthLeap is led by Jemima Meyer, Josiah Meyer, and Ray Botha. Jemima is a clinical dietitian who saw first-hand the tragic effects of widespread and untreated malnutrition in hospitals. Frustrated, she built a rudimentary version of NutriLeap for herself and shared it with her colleagues, for whom it swiftly became a vital tool. She then showed it to her brother Josiah, and his close friend, Ray, both serial entrepreneurs. Josiah studied statistics and machine learning and has been starting profitable ventures since his teens. Ray was previously the founder and technical brains behind a successful $250M AI-powered crypto trading startup, where Josiah was the product manager until they both quit to start HealthLeap.

At Fifty Years, our sweet spot is supporting founders at the earliest stages building deep tech companies that can generate huge financial outcomes and create massive positive impact.

1. Deep tech: Nutrition is a critical component of patient care but is dramatically under-resourced. A machine-learning enabled tool that can process the dizzying number of factors that go into screening at-risk patients, creating feeding plans, and updating them as patients travel through treatment and recovery would address one of the most complex and vexing problems in modern medicine. 

2. $1B yearly revenue potential: America spends more than $4 trillion annually on healthcare. Malnutrition is a significant, silent contributor to that sum. It leads to worse patient outcomes, longer hospital stays, and higher morbidity and hospital readmission rates. A company that effectively addresses the problem will generate not only billions of dollars in industry savings but become a vital cog at the heart of an industry that represents one-fifth of US GDP. 

3. Massive positive societal impact: Hospital malnutrition affects tens of millions and is getting worse as the population ages. By 2030, one in five Americans will be over 65, the part of the population most prone to both malnutrition and hospitalization, where the former often gets worse. HealthLeap can save millions of lives by enabling dietitians to find at-risk patients sooner, treat them faster, and help them maintain healthy habits after treatment.

Inspired by their vision and incredibly fast execution, Fifty Years was proud to lead HeathLeap’s pre-seed round and we’re looking forward to continuing to help Jemima, Josiah, and Ray radically improve health outcomes by enabling more people to get the nutrition they need.

Watch the Super Bowl and you might be forgiven for thinking, if only for a moment, that we had finally gotten ahold of the climate crisis. No less than six electric cars ads were peppered throughout the big game, featuring a cast of Hollywood A-listers from Salma Hayek to Eugene Levy. Arnold Schwarzenegger even played Zeus in a spot for the new (electric) BMW. Detroit is going green! The internal combustion engine, which has been belching fumes into the atmosphere for more than a century, is on its way to the dustbin of history. We’re saved! 

If only it were so easy. 

Transport is just the beginning. The climate change task is so monumental because so much of the CO2 emissions we must eliminate are still hiding in plain sight. They are in the cement in our sidewalks. The cooking oil in our kitchen. The pills we take when we’re sick. The plastics in our packing. The ingredients of modern life – from the built environment to the goods we consume – require vast amounts of heat and electricity to make. Cement is the largest building block of civilization by mass, and accounts for 7% of global CO2 emissions because its production requires kiln temperatures as high as 1,450 degrees C. Nitrogen fertilizer (2% of global emissions) relies on ammonia made through the heat and energy-intensive Haber-Bosch process. Steel (8% of global emissions) requires vast amounts of heat to melt iron ore. Today just about all the heat needed for these processes comes, simply, from burning stuff.

And boy oh boy do we like to burn stuff. Feeling cold? Burn some wood and get cozy by the fire. Need electricity? Burn natural gas to boil water and drive a steam turbine. Making a skyscraper? Burn some special coal to melt metals and shape them into beams. Our entire civilization depends on burning fossil fuels to create the heat and electricity we need for our modern way of life. Despite all of our apparent advances, we’re not all that far removed from our primal existence: over 84% of our primary energy production still comes from burning stuff. That’s 450 exajoules/yr from 🔥, or 1/20th the energy released by the Chicxulub impactor that killed the dinosaurs. 

Reshaping atoms to suit our needs is unfortunately an energy-hungry undertaking. Viewed through that lens, it’s perhaps not surprising that industry is so heavily reliant on fossil fuels, making it likely the largest source of emissions globally (30%).

Renewables like solar and wind have started to chip away. Globally, 290 gigawatts of green power were added to the mix in 2021, increasing total capacity to 3.3 TW. In America, more than 90% of the utility-scale power projects added to America’s grid through the first half of 2021 were renewables. In some markets, solar and wind have reached par or are now cheaper than fossil fuel alternatives. 

Renewables, however, have a fatal flaw: intermittency. The sun doesn’t always shine and the wind doesn’t always blow, which means that the world’s rapidly-growing solar and wind fleets must be buttressed by “peaker plants”, typically fuelled by natural gas. These are kept on standby, ready to fire up when renewables fall short and prices spike. 

For industrial power users, this model is unpredictable and financially painful. A few peak days each year can account for the majority of the annual energy bill for, say, a steel smelter or an ethanol plant. 

Batteries have the potential to liberate industry from this toxic dynamic. However, the dominant technology – lithium-ion – is simply too expensive to deploy at the scale required to obviate the need for backup fossil-fuel plants. Lithium’s sweet spot is filling shorter gaps, say between four and eight hours. 

This has sent the industry on a search for the holy grail: a long-duration energy storage alternative that meets or beats gas power on price and performance, and can be deployed around the world. Today, there is just one option: pumped hydro. This involves two reservoirs, usually separated by several hundred feet of elevation. Energy is used to pump water up to fill the top reservoir, which then drains when it is needed, turning turbines that generate electricity. It is the cheapest and most plentiful energy storage option; America has 43 such installations. 

The problem, of course, is that there are so many bodies of water one can dam. Sites are typically remote, hugely disruptive to the environment to build, and present flooding dangers should something go wrong. And in an era of climate change, depending on water supplies for energy is a gamble. The federal government in August announced that, for the first time since the Hoover Dam was finished in 1936, it would ration water from the Colorado River, a source of power and water to 40 million people. Pumped hydro, in short, isn’t a scalable option. 

Enter Antora Energy. The company has developed a zero-carbon thermal battery that is safer, longer-lasting, more efficient, and cheaper than anything available today. Unique among electricity storage systems, it also stores and can dispatch heat required for most of the world’s core industrial processes.

The system revolves around two key elements: blocks of carbon and thermal photovoltaic panels (TPV). To understand how they work, think of a toaster. In a toaster, an electric current heats up coils that glow to brown your bread. Antora replaces the coils with carbon blocks about the size of a washing machine. These are off-the-shelf items used in smelting that can be heated to extreme temperatures and have an extremely high energy density (~700 Wh/kg) compared to chemical batteries (~100-300 Wh/kg). Housed in a well-insulated box that looks a bit like a garden shed, Antora’s blocks are heated to higher than 1,500 degrees C, at which point, they glow incandescent. The TPVs can then convert that glow back into electricity.

Antora’s breakthrough is in the design – ultra simple, no moving parts, and made from inexpensive pieces that are already easily manufactured at super large quantities. No rare elements have to be mined and no exotic metals have to be used. 

The system can discharge energy for more than 100 hours, with only about 1% energy loss per day, so that it can provide energy during cloudy and windless days. And if a facility needs a source of heat to, say, heat a furnace to make cement, it can draw heat directly from the Antora battery. 

The result is the most nimble energy storage system on the market, a ‘sun in a box’ that is capable of releasing electricity or arbitraging it to heat for industrial processes that would otherwise come from coal or gas combustion. More importantly, the system has the promise, at scale, to transform intermittent renewables into a source of smooth, baseload power that could help consign coal and gas-fired plants, like the internal combustion engine, to the dustbin of history. 

Antora’s founding team met at Cyclotron Road, a program at the Lawrence Berkeley National Laboratory for scientists seeking to commercialize their research. Chief Executive Officer Andrew Ponec sold his previous startup Dragonfly Systems, a photovoltaic startup, to Sunpower. Chief Product Officer David Bierman has a PhD in solar thermal energy systems from MIT, while Chief Operating Officer Justin Briggs earned his applied physics PhD from Stanford, where he researched the TPV technology at the heart of how Antora’s battery juggles between thermal and electrical energy. 

When they came together, they took a tech-agnostic approach to a simple question: what is the biggest problem in energy to improve human lives? 

Amid a renewables boom spurred by a historic manufacturing scale-up that drove down prices for panels and turbines, they quickly alighted on the long-duration storage problem. They looked at all of the options, from molten salt and compressed air to hydrogen, before zeroing in on carbon blocks and TPVs. 

Decarbonizing heavy industry has long been seen as the most difficult part of the climate puzzle. Plant owners run highly-complex, dangerous sites that demand total reliability in terms of safety and continuity of operations. Convincing them to swap out tried-and-true natural gas boilers requires confidence that the alternative can match or exceed their exacting requirements. 

Antora does. Power from natural gas costs about 2.5 cents per kilowatt hour. Antora expects to be able to win on costs alone. And that’s without accounting for additional carbon prices that may be imposed. The carbon blocks' energy density means that Antora’s modules have roughly the same footprint as a lithium-ion battery – or even smaller – which is important when it comes to integrating into an industrial site. And the materials they are using are abundant with a safety profile that carries none of the operational risks, like thermal runaway in lithium-ion, of rival technologies. 

Antora’s thermal batteries could be the key to greening industry and, longer term, speeding the end of fossil fuel plants for electric generation, which are the single biggest source of carbon emissions globally. 

At Fifty Years, our sweet spot is supporting founders at the earliest stages building deep tech companies that can generate huge financial outcomes and create massive positive impact.

1. Deep tech: Antora has built a thermal battery that’s more efficient and cheaper than anything on the market and promises to deliver the Holy Grail of energy: transforming intermittent renewables into zero-carbon baseload power that can be used to decarbonize first, heavy industry, and eventually, the entire electricity grid. 

2. $1b yearly revenue: Heavy industry spends hundreds of billions of dollars annually on electricity and heat. Antora can deliver both at prices that undercut natural gas plants and avoid present and future pollution penalties.

3. Massive positive societal impact: Carbon emissions are embedded in the built environment and virtually every product we consume. Antora promises to clean up the most stubbornly-dirty parts of the economy by decarbonizing the industries at the heart of modern life.

Inspired by their vision and execution, Fifty Years was proud to lead Antora’s seed round and we’re excited to now deepen our partnership in their $50M Series A led by our friends at Breakthrough Energy Ventures and Lowercarbon Capital. Also joining in the Series A are several other investors including Shell Ventures, BHP Ventures, Grok Ventures, Trust Ventures, Overture VC, and Impact Science Ventures. At Fifty Years, helping great scientists and engineers become great entrepreneurs is our jam, and we’re looking forward to continuing to help Andrew, David, Justin, and team transition industry to zero carbon heat and power.

Oil is destroying our planet and our health. But not the oil you're picturing. The black sludge that comes from the remnants of dead organisms buried underground millions of years ago is definitely ruining our lungs and destroying our climate while making our homes warmer. The oil that we often use for cooking, though, is creating a different kind of catastrophe. 

The vegetable oils you use on that stir-fry or the palm oil restaurants use for frying are rapidly destroying our environment due to the enormous amount of land and resources dedicated to producing it all. The crops used for oil are terrible when it comes to using land efficiently. An area of land used to grow one kilogram of vegetable oil from soybean, canola, or sunflower could instead produce 30-50 kilograms of actual vegetables, like spinach, sweet potatoes, and carrots that could promote healthy living and help curb food inequity! 

To create enough oil through this inefficient process to meet the world’s growing demands, we’ve exploited some of our most important and precarious ecosystems. Every minute, the planet loses more than 60 football fields worth of forest via deforestation.1 That’s one football field worth every second! Oils are the second largest driver of this deforestation, ahead of forestry and after only animal agriculture.2 As our forests go up in flames to make room for these destructive crops, we lose our beautiful biodiversity and exacerbate the effects of climate change as these critical sinks of carbon dioxide are lost.

But oil isn’t going anywhere, even if our land is. It was probably in the shampoo you used this morning, the vitamins pills you swallowed, or the make-up you applied. It is definitely in the packaged food we “sometimes” indulge in and the cooking oil we use for dinner.

To add insult to injury, our addiction to vegetable oil also comes with dire health consequences. As vegetable oil consumption has grown, rates of obesity, heart disease, and diabetes have also surged. But not all oils and fats are created equal. 

These days, the cooking-oil section at the supermarket is a crowded spot – so which one is the healthiest for you? From a biochemical standpoint, all fats are similar: three fatty acids bound together by a glycerol molecule. All the cooking fats we buy get most of their unique properties from these molecules. By simply swapping out different fatty acids that vary in size and composition, we change its chemistry and give fat new properties. This subtle difference is in the fats’ levels of saturation, essentially driving an oil’s health properties. 

Our bodies are good at using triglycerides with some fatty acids but are far worse at processing others. Naturally occurring types of unsaturated fats are absolutely essential in our diets. Think olive oil, omega-3 fats, and avocados. Eating these are associated with improved blood cholesterol and decreased risk of heart disease. On the other hand, certain types of saturated fats are not great for you. Think lard, corn oil, and palm oil. Although natural, these may increase your risk of heart disease by increasing bad cholesterol. 

But perhaps the worst – the one we check the label for when we pick up a bag of chips – is trans fat. Think margarine or vegetable shortening. These result from human intervention – taking healthier unsaturated fats and pushing them through a process called hydrogenation that increases their shelf-life. These unnatural fats have a different chemical composition than what our bodies are used to and are therefore hard to process and a major driver of heart disease, stroke, and diabetes. 

Vegetable oils, while nearly nonexistent a hundred years ago, now account for 20% of our caloric intake.3 Their ubiquity is, in large part, due to their unique properties that make them easier for food manufacturers and restaurants to use at scale. They’re made relatively flavorless as a result of an intensive extraction and refining process, using harsh chemical solvents. They’re cheap as a result of having a market for their leftovers in factory farm animal agriculture; after being pressed for oil, rapeseed (canola), sunflower, and soybean leftovers are fed to animals in feedlots – the most unsustainable form of animal agriculture.. 

But what if there was a better alternative? What if we can find a different, more sustainable source of oils and fats that don’t make us sick, wreck the environment, or propagate factory farm animal agriculture?

Enter Zero Acre Farms, who are brewing up a new category of healthy oils and fats, made by fermentation, not deforestation. Within the cell of some microbes lie an organelle that – in addition to a host of other functions –  can also store triglycerides. In other words, some microbes carry little packets of potential cooking fats, just waiting to be utilized. 

Zero Acre has developed a method to harness a particular type of microbe with an extremely useful storage mechanism. These microbes are fermented, much in the same way we make beer. But instead of making alcohol, they convert the plant inputs Zero Acre feeds them into triglycerides. This gets converted into liquid oil or solid fat, depending on the type of microbe and the fermentation conditions, which is then ready to be used in our deep fryers. Their products have less saturated fats than lard, palm oil, other vegetable oils, or animal fats and is less prone to trans fat conversion than canola, sunflower, or soy oil. In addition, their fermenter origin means a much smaller environmental footprint.

At its current scale, Zero Acre’s oils and fats are already cost competitive with premium oils and fats like extra virgin olive oil, avocado oil, and clarified butter. As they continue development and rapidly scale, they will approach the cost-effectiveness of soy or palm oil. By refining the method, upscaling cheap waste products, and using optimized facilities, Zero Acre’s oils and fats will become a cheaper, healthier, and more sustainable alternative to the oils used across our food chain. There's a lot more going on under the hood that will make Zero Acre’s oils preferable from a cost and function perspective that we can't talk about just yet. Stay tuned!

But the biggest advantage Zero Acre has is the deep knowledge of the platform they are working with. By tweaking the culture conditions that their microbes grow in, they have already demonstrated they can change the triglyceride composition of the lipid. Leveraging their expertise in synthetic biology, the team can also tweak the biology of their microbial strains and fine-tune the oil that is fermented to fit the target profile of any fat they need. 

In a world where Zero Acre Farms succeeds, the inefficient and unsustainable use of our forests to produce oils will be a thing of the past, and all fats used – from cooking to cosmetics – will be made by fermentation instead of deforestation.

This audacious dream doesn’t come from just anyone – the Zero Acre Farms founders are exactly the type of people to build this business into a billion dollar behemoth that can truly make a positive impact on the world. Co-founder & CEO Jeff Nobbs is a serial founder with a background in food and technology, having built the clean casual San Francisco Bay Area restaurant Kitava, the food security nonprofit HelpKitchen, and ecommerce websites Perfect Keto and Extrabux. Dr. Steve del Cardayre, co-founder and CTO, is a biochemist and microbiologist, with over 23 years of professional strain engineering and fermentation expertise from his time at Maxygen and through his experience co-founding LS9, a start-up using yeast fatty acids to make biodiesel. They’re joined by co-founder Dr. Jay Keasling, an authority on synthetic biology and the luminary behind metabolic engineering. A serial entrepreneur himself, Jay has co-founded several companies that have engineered microbes to produce pharmaceuticals, commodity chemicals, and cellulosic biofuels. Together they’re an indomitable team and are uniquely prepared to usher in this new era of sustainable, healthy, and cost-effective oil for whatever meal your palette desires. 

At Fifty Years, our sweet spot is supporting founders at the early stages of building deep tech companies that can generate huge financial outcomes and create massive positive impact.

1. Deep Tech: The team has invented proprietary methods that enable the optimization of new microbial strains. Combined with their vast experience in dissecting biochemical processes and scaling microbes, they have the technology and know-how to optimize the composition and yield of their oils and fats.

2. $1B yearly revenue potential: Oil is an essential part of our world, touching everything from food to consumer goods. Vegetable oils alone are a $200B+ annual market. Zero Acre’s ability to create a more cost effective version that performs better than the oil harvested from monoculture crops means their products can add value in virtually every part of the market.

3. Massive positive societal impact: The health benefits of Zero Acre Farms’ oils and fats means that consumers can enjoy many modern foods without taking on the health risks associated with many alternative oils. For the planet, Zero Acre’s products will stop rampant deforestation, restore carbon-sequestering natural habitats, and reverse destructive monocrop agriculture that destroys soil health. 

Zero Acre Farms is an example of how excellent science can create extraordinary impact through entrepreneurship. Inspired by their vision to create radically more sustainable, healthy, and cost-effective cooking oils and fats, Fifty Years was proud to lead Zero Acre Farms’ previously unannounced Seed round. And we’re excited to deepen the partnership by co-leading Zero Acre Farms’ Series A with our friends at Lowercarbon Capital. Also joining in the Series A are several other investors including S2G Ventures, Virgin Group, and Footprint Coalition Ventures – Robert Downey Jr.’s climate-focused investment fund. At Fifty Years, helping great innovators, scientists, and engineers become great entrepreneurs is our jam, and we’re looking forward to continuing to help Jeff, Steve, Jay, and team build a radically better food system for people and the planet.

Poor ole’ Sisyphus. Everyday he was forced to roll that big boulder up the hill. And everyday, the boulder rolled back down – doomed to repeat the task for eternity. Even the ancient Greeks could recognize the inability to complete this was a weird form of torture. 

For the last few centuries, we’ve accepted this same approach for our medicines. The vast majority of our therapies work by putting a band-aid on the problem and reducing the effects of the disease, but only if you remain on the drug indefinitely. These drugs don’t fix the underlying problem – much like Sisyphus rolling that boulder up the hill each day. Fortunately, there’s a new form of medicine that gives us superpowers – one that will keep that boulder at the top of the hill.

Cell and gene therapies are rapidly being adopted to recode the genetics of our own cells, endowing them with new abilities that fight or reverse disease. They work by inserting new genetic material into our cells and come with the promise of curing everything from rare diseases to cancer. 

These genetic “payloads” can add a healthy copy of a gene if you were born with a mutated version. For example, a mutation in the RPE65 gene leads to blindness but adding a non-mutated version to retina cells with gene therapy restores sight. In other cases, these payloads give cells a gene not found in nature. T cells, for example, can be pulled from a cancer patient and engineered with a chimeric antigen receptor (CAR) gene. These cells are then reintroduced to the patient as a cell therapy where the CAR directs the T cells to hunt and kill cancer.

To get these payloads into cells, we have repurposed nature’s best genetic engineers – viruses. Through decades of research, we have improved upon these microscopic gene delivery vectors, making them safe for use in humans, engineering them to target specific tissues in the body, and reworking them so that we choose what genetic payload they deliver. 

The issue is that we haven’t gotten much better at producing a large quantity of these viral vectors. To make these delivery vehicles currently, we take human cell cultures and shove DNA in them, giving them the instruction manual on how to produce our vector. Over the course of a few days, the cells secrete these vectors into the culture media, where it can be isolated and used. 

Unfortunately, the cells’ innate wiring make scaling-up this process extremely difficult – we’re asking the cells to go against eons of anti-viral evolutionary programming to make parasitic viruses for our benefit. Because cells are ill-prepared to make viruses, we end up with low yield. Often, this is simply because the cells throw in the towel before they make enough. Often, though, we simply didn’t give the cells the optimal instructions, leading to the creation of malformed and non-functional vectors.

This means manufacturing of cell and gene therapies is extremely bottlenecked. Use of these inefficient cells creates two manufacturing problems: capacity and cost. 

First, manufacturing capacity with current paradigms is insufficient to cure even diseases that affect only a handful of people. To treat an ultra-rare disease that affects only 0.001% of people, we would need to double our current capacity. To treat a rare disease – one that affects less than 200,000 people – we would need to 200X our current manufacturing capacity. 

In other words, our capacity to make vectors for cell and gene therapies is orders of magnitudes lower than it needs to be to help even a small subset of patients. To make matters worse, the problem can’t be solved by outsourcing to specialized manufacturers – every manufacturer uses the same inefficient cell lines and non-optimized instructions. So with a growing market, manufacturers have a 2-year waitlist. 

But even if we could produce enough vector, manufacturing cost is prohibitively expensive. That's why gene and cell therapies currently cost people hundreds of thousands if not millions of dollars. To manufacture enough viral vector for more common diseases like diabetes with current efficiencies, costs would exceed the entire U.S. government spend in 2020!

Thankfully, the yield problem can be solved with synthetic biology. It’s well established that randomly or rationally mutating either the vector-producing cells or the vector instruction manuals can optimize yield. Doing so, though, forces the vector-producing cells to do something they’re wired to avoid, so helpful mutations are exceedingly rare. To make matters worse, a cell will likely need multiple mutations to optimize production of a single therapy.

This blows up the space that needs to be checked to find the perfect cell line. Conservatively, if we need 7 mutations in a single cell, that's 1,030 possibilities to screen for a winner! Checking for these mutations one at a time would be impossible given the size of the space. Even worse, each new therapy would require re-running this process.

Enter 64x who have built a first-of-its-kind solution to overcome this problem. Realizing the intractability of searching this space with traditional methods, 64x generated a new approach that enables them to screen millions of optimizations in a single culture. Instead of editing, growing, and measuring cell-factories one at a time, 64x makes millions of edits to a pool of cells, manufactures vectors, and uses sequencing and computation to pinpoint which edit was optimal.

Yet even at this vastly improved throughput, it would still take a long time to empirically measure the whole space of 1,030 possibilities. If it took just one second to check each possibility, it would take longer than the entire history of the universe. So, 64x takes their proprietary dataset – the largest amount of edit-to-yield information ever coalesced and feeds it into CellMap, a model that whittles down the enormous possibility space into a subset that can actually be screened. 

With this, Dr. Lex Rovner, co-founder and CEO, leverages her years spent in Professor George Church’s lab at Harvard University pioneering the use of recoded cells to give them better functionality. At 64x, she combined integrated DNA library synthesis, next generation sequencing, and machine learning to create VectorSelect – an ultra-high-throughput approach that feeds 64x’s AI, enabling them to rationally design optimal vector manufacturing cell lines. 

Using VectorSelect, millions of cell or instruction manual variants create vectors in a single reactor. The key innovation involves a proprietary genetic barcoding method that connects information on viral vector productivity back to the parent cell which produced it, enabling massively parallelized genetic screens of millions of candidate production cell lines simultaneously – a feat which has been impossible until now. 

There are a lot of advantages:

1. VectorSelect enables millions of variants to be tested in a single assay relative to traditional methods. By doing everything at once in a pooled format instead of checking each variant one at a time in a multi-welled plate, 64x can screen orders of magnitude more variants.

2. Every VectorSelect assay creates data on each variant’s specific yield given a particular payload. This generates valuable information that is fed into computational models, refining 64x’s variant libraries and creating higher and higher yields for their customers.

3. The VectorSelect process is run at scale in a bioreactor, meaning 64x is finding optimal variants under the same conditions in which the vector is actually produced. This is in stark contrast to current standards which are checked in a much smaller multi-welled plate format and provide no data on whether the cells or instruction manual will scale well.

4. VectorSelect is designed to work with any vector generation process. Whether you’re working with the tried and true vectors generally used in the field, a weird subtype that has a particularly advantageous property for your therapy, or even a niche vector that is only beginning to be used, 64x can adapt to make sure the maximum vector is generated.

5. VectorSelect only captures well formed, fully functional vectors. Other methods optimize on the production of vector particles, meaning they count malformed and non-functional vectors, leading to a lower quality cell or gene therapy. 64x only takes into consideration those particles that are operational and ready to provide benefit to a patient.

64x will be at the forefront of the gene and cell therapy explosion, enabling the viral vectors that underpin them to quickly and cheaply scale-up. They will not only enable cures for ultra-rare diseases, but also for diseases with huge populations like those related to aging. Even more excitingly, they will massively enable the design-build-test cycle of future vector-based therapies that have shown promise in redesigning immune cells, exploding tumors, and vaccinating against infectious diseases.

At Fifty Years, our sweet spot is supporting founders at the earliest stages building deep tech companies that can generate huge financial outcomes and create massive positive impact.

1. Deep tech: Lex has leveraged her enormous synthetic biology skills and deep understanding of how to recode organisms to make a proprietary platform that optimizes virus production faster, cheaper, and easier than any one else can.

2. $1B yearly revenue potential: Cell and gene therapies are exploding into medicine and have the potential to touch every disease we could imagine. 64x is poised to become the de facto scale-up company that enables these therapies to move from bench to bedside.

3. Massive positive societal impact: Therapies that rely on viral vectors have huge value but are only able to touch the lives of very few people. 64x’s platform technology not only allows more people to be treated with the medicines we have, but also opens the possibilities for novel ones to be created that are currently too difficult to even imagine.

Inspired by their technology and vision for its future, Fifty Years was excited to co-lead 64x’s seed round with our friends at First Round Capital. We’re grateful to deepen the partnership in their $55M Series A, led by Lifeforce Capital, with support from Northpond Ventures, First Round Capital, Alix Ventures, and Refactor Capital. 64x is a model for how brilliant inventors can move their work from academia to industry and completely transform a niche into the de facto standard; a narrative that inspires us here at Fifty Years.

Goofy knows a shocking amount about drug discovery. In this short (watch it!) Goofy goes through endless keys on a keyring to find the right one to unlock a door. In the early stages of drug discovery, pharma’s keyring – their arsenal of molecules – is full of keys that unlock nothing. Sometimes their keyring looks like Goofy’s, where they know what the keys do but they clearly aren’t useful for the door they’re trying to open. Other times they might see a door but can’t find the keyhole. Unfortunately, Mickey’s sentiment is true for many drug discovery endeavors: searching for the right key leaves us disappointed and confused, especially when none of the molecules in the existing arsenal work. The complexity of this problem is a big reason why drug discovery is such a complex and expensive endeavor, and why it takes an average of $1B to get a new drug to market.

Yet, almost every drug on the market was found in this cartoonish way. Pharma spends huge amounts of time, people power, money, and material synthesizing chemicals that go into their expansive libraries – the enormous number of keys on the keyring – and then more time and money testing these experimentally to see if they work. The libraries they use are optimized to create a large diversity of chemical structures and physical properties in order to represent as much “chemical space” as possible. These ever-growing and massive chemical libraries are carefully stored in large warehouses of well-plates (like the one shown below) awaiting the moment pharma finds a new door. For example, Bayer’s library has around 4 million different compounds it can use to screen against new targets.

With molecules in hand and chemists working around the clock to expand the library, pharma must look for high quality targets – in our Goofy analogy, the doors that open to effective treatments. Targets are usually proteins that a disease-causing cell expresses. For cancer, the target could be a receptor that helps the cancer grow. For a metabolic disease, it could be a mutated enzyme that no longer functions properly.

Target and chemical library in hand, pharma begins attacking the problem like in the cartoon. They create cellular models of disease that can tell scientists when the target has been disrupted (i.e. the door unlocked) and grow the cells in super tiny well-plates. Using robots, the molecules are added to the cells, one molecule to one well, and measured one-by-one to see if the molecular perturbation produced the desired effect at the target. It’s a very brute force process and in the best of cases only 1 out of 1000 of the molecules may be hits that do anything interesting. In the worst cases, against the most challenging targets, they might turn up empty handed. 

To complete the discovery process before testing in living organisms, the most promising hits (known as leads) undergo further chemical optimization, called lead optimization, that aims to improve their properties without compromising their ability to hit the target. For example, by adding different chemical subgroups onto each hit, chemists can enhance the molecules by making them more “drug-like” – changing properties such as solubility, likelihood of being metabolized, and molecular weight – without sacrificing potency at the target.

The search problem pharma undergoes in finding hits, iteratively turning hits to leads, and optimizing the leads experimentally is extremely laborious and resource intensive. Thankfully, we now live in a time where search, design, and optimization problems can be solved in silico. We’ve long hoped to leverage our knowledge of chemistry, biology, and computation to reduce the earliest parts of drug discovery into a computational problem. Using the latest deep learning tools, the vast amount of data that pharma and academia has created can now feed predictions to accelerate the process, reduce the failure rate, and unlock targets that may be difficult or impossible to drug using conventional approaches.

Deep learning typically requires extremely large amounts of data to kick off the learning process. There have been great companies founded over the last decade aimed at just this problem – generating huge amounts of quality biological data with robotics and high throughput techniques to feed into machine learning algorithms in order to improve the drug discovery process. The issue is the sheer amount of data needed.

The space of potential chemicals alone is estimated to be around 10⁶⁰. The combinations of potential chemicals and thousands of potential targets is over 10⁶⁶ – that’s more than the number of stars in the universe, by a lot. Existing datasets and deep learning algorithms can help optimize single molecules, or clusters of them, but it’s like exploring one moon of one planet orbiting a single star. It’s effective in understanding that moon, but it tells you next to nothing about other moons in the universe. The traditional data-heavy model of AI drug discovery falls short when you realize 90% of potential chemistries and 97% of targets have no data! Ideally we’d be able to use AI to better understand these unexplored spaces without the need to spin up hundreds of millions of time consuming and expensive biological experiments.

Enter Valence Discovery. Rather than trying to adapt drug discovery to meet the constraints of deep learning, Valence is adapting deep learning to the constraints of drug discovery. Given the sparsity of data available and the intractability of broadly exploring the drug-target space, Valence realized that drug discovery is a “low data problem,” not a “big data problem”.

Valence is creating machine learning systems that enable them to design vastly better molecules with much less (or even no) data, against some of the pharmaceutical industry’s most challenging and high-value targets. By rethinking the way deep learning is applied, they have pioneered multiple approaches that together solve drug discovery’s data problem.

They start by tackling featurization – the way a molecule is represented in an ML model. Featurization attempts to distill the essence of each molecule such that a computer can understand its properties. While this step is essential to translating the physical to the digital, the quality of that translation can have profound effects on how successful the algorithm is at predicting drug efficacy and other key properties. Valence has developed best-in-class methods for molecular featurization. For example, Valence can encode 3D properties directly from 2D structure and better capture key molecular interactions that increase the accuracy of their predictions. These featurization approaches allow Valence to predict drug efficacy with fewer molecularly similar examples, which is especially important for novel or challenging disease targets. The flexibility of these approaches also enables Valence to look beyond classical small molecule chemistry into degraders, molecular glues, macrocycles, and more. 

Building on this featurization, Valence leverages their founding team’s pioneering research in few-shot learning against novel targets with limited (or no) existing data. This approach allows their algorithms to extrapolate far beyond the training data – much farther than they ever could with traditional methods. With it, Valence reaches into the vast regions of unexplored chemical and target space that no one else can, finding more potent hits quicker than ever. Even in situations with extremely limited quantities of data, Valence has already shown that they can predict key drug parameters such as potency, selectivity, and toxicity with a level of precision that matches experimental results.

Valence has also innovated on physics-based approaches to simulate how drugs generated by the computer (but never actually synthesized by a chemist) bind to a target of interest. Combining this with state-of-the-art optimization techniques, Valence designs novel hits and improves their drug attributes entirely in silico, bypassing the need for the huge amount of iterative experimentation that can be time-consuming, noisy, and expensive. The power of this approach is already apparent – Valence was able to design a better drug in 2 weeks than pharma could in 2 years (see below).

The last piece of Valence’s approach solves the final major challenge in AI-driven drug discovery: can chemists even make the molecule the algorithm designs? 

Traditional deep learning approaches often suggest molecules that might hit the desired target but are impossible to manufacture. To ensure they can translate the digital asset to a physical one, Valence created a method that takes a library of molecules that have already been synthesized and uses features of these accessible drugs to train the computer on which molecular additions, building blocks, and chemical reactions are acceptable. It’s like watching chess: after a few games, you can understand how each piece is allowed to move. Once you know how the pieces move, you can begin to imagine what your opponent might do in the future, and start thinking a couple steps ahead. Valence’s method does the same thing, so that when a suggested hit pops out of the algorithm, chemists know they can actually make the molecule.

The most exciting part: it’s already working! Valence’s platform – used by pharmaceutical and biotech companies including Charles River Laboratories, Repare Therapeutics, and Servier – has enabled rapid design of novel chemical matter against extremely challenging disease targets. Valence has demonstrated impressive commercial traction and is actively deploying its platform across multiple target classes and indications through collaborations with leading biotech and pharmaceutical companies, CROs, and academic centers. 

These enormous strides in AI applied to drug hunting are only possible because of the expert team behind Valence. Co-founder and CEO Daniel Cohen brings his expertise in cognitive science, computer science, and machine learning from his research as a graduate student at McGill University. Co-founder and COO Therence Bois brings deep experience in molecular and cellular biology from his PhD work in cancer resistance at the Montreal Clinical Research Institute. Co-founder Prudencio Tossou is a PhD in machine learning and a researcher at Mila who pioneered few-shot learning approaches applied to drug discovery. Co-founder Sébastien Giguère is a PhD in machine learning and computational biology as applied to the design of pharmaceutical compounds. The Valence founding team has created an incredible culture driven by science and innovation that keeps them at the forefront of their field.

At Fifty Years, our sweet spot is supporting founders at the earliest stages who are building deep tech companies that can generate huge financial outcomes and create massive positive impact.

1. Deep tech: The Valence team is pioneering the use of next generation computational technologies custom-built for biology and chemistry, including geometric deep learning, low/no data deep learning, and physics-informed deep learning, across the entire drug discovery pipeline, allowing them to look deeper into drug target space with vastly smaller amounts of training data.

2. $1B yearly revenue potential: single successful drug can get to $1B+ revenue. Valence is helping create dozens of them across external partnerships with industry-leading discovery organizations as well as an internal pipeline of in-house assets.

3. Massive positive societal impact: Given the number of disease targets that remain undruggable, and diseases that remain untreatable, Valence’s chemistry engine has the potential to power an entire generation of drug discovery, helping bring new medicines to a broader and more diverse set of patients. 

Inspired by their vision for the future of drug discovery, Fifty Years is excited to co-lead Valence’s seed round, along with our friends at Air Street Capital. Amplitude Ventures, Phoenix Venture Partners, and Abcam founder & former CEO Jonathan Milner also participated. We’re looking forward to helping Daniel, Therence, Prudencio, and Seb discover drugs that help billions of people.

1. This $90M is exclusively for founders building insanely ambitious, incredibly hard, and radically important companies to solve the world’s biggest problems.

2. Most of our companies look like Solugen -- grand, hard, important. We help founders build companies like Astranis, Varda, Nobell Foods, and UPSIDE Foods (fka Memphis Meats). All Fifty Years portfolio companies are solving the world’s greatest problems.

3. We consider ourselves company builders more than investors. Our team is full of insanely ambitious former founders. We love partnering with founders at the earliest stages.

4. And we mean early. We were the first VC to partner with Solugen (now valued at $1.8B) and Astranis (now valued at $1.4B) and led both companies' pre-seed rounds.

5. We roll up our sleeves and help. Our motto is: “Always available, never annoying”. You want help wrenching? Invite us over. Need a Founding Chemist? We got you covered. Need a place to stay in SF? Crash at our HQ.

6. Our first core value is “Founders First”. That’s why we’ve decided to raise from the most legendary entrepreneurs of the last decade. We assembled this “League of Giants” to give our portfolio founders the wisdom, expertise, and networks of the world’s best founders. We have 44 founders of unicorn tech companies valued between $1B and $100B as our LPs, including the founders of:

   • Skype

   • Spotify

   • GitHub

   • Klarna

   • Dropbox

   • Snowflake

   • Zendesk

   • Twist Bioscience

   • Supercell

   • Minecraft

   • Google Brain

   • The Climate Corporation

   • AmRest

   • Sprout Social

   • Rovio

   • Kahoot!

   • Stemcentrx

   • Wise

   • Bolt

   • Google Maps

   • Mercury

   • Jazztel

   • Viatel

   • Eolia

   • Automattic / Wordpress

   • Upstart

   • Gluu Mobile

   • Virgin Group

   • Solugen

   • Astranis

   • Opentrons

   • UPSIDE Foods

7. We’re proud that every single founder of our own unicorn portfolio companies chose to join as an LP.

8. Fifty Years is trying to change venture capital by bringing it back to its roots of backing technically ambitious teams building real, meaningful things instead of the latest avatar making AI whatever.

9. We're sector agnostic and keen to support founders in any vertical building companies that can generate huge financial returns while creating real social or environmental impact. We particularly love supporting teams in climate tech, synthetic biology, platform therapeutics, healthcare, connectivity, and space. We’re also excited by possibilities enabled by Web3.

10. We love helping translate breakthrough research into world positive companies, and we run multiple programs for PhDs interested in starting companies or getting into venture. We also host a podcast on translating science.

11. We want to prove that backing only truly important companies solving the world's biggest problems is a great way of generating huge profits. We've done a great job so far, with our Fund I at ~10x and our Fund II off to a similar start. But we’re only just getting started.

Are you trying to solve one of the world’s biggest problems via entrepreneurship? Do you want the most mission-aligned, value-add investors backing you? Do you want to join our team? Drop us a line: hello@fiftyyears.com.

Are you as excited about this as we are? 😁👇

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The first recorded use of currency was 3,200 years ago. Ancient Chinese societies used cowrie shells as a replacement for bartering. Being part of this “shell network” was really helpful, since bartering required having the perfect number of sheep to trade for rice at the same time the merchants were meeting. This original currency had regional network effects. If every merchant in your town was using shells, you could easily go to a marketplace and get your shopping done without needing the perfect barter match. And the more buyers using shells, the better it would be for merchants to accept the shells. This meant every additional person in the shell payment network added value to the shells. 

Early currencies also facilitated the accumulation of wealth. Managing value was easier, so merchants, lenders, and governments could more easily accrue wealth and have a predictable medium to pass on that wealth to their children. Whereas a farmer couldn’t pay a piece of his cow in taxes, he could pay in shells. One African king collected 30 million shells a year, by taxing each ox at 1,000 shells (~$17, inflation-adjusted for 2021).

Fast forward 3,200 years. Currency systems have grown more complex but the basic principles that began in ancient China still remain. Popular currencies like the US dollar or the Euro have a ton of utility, partially because you can go to almost any bank in the world and trade your USD for the local currency. Central banks hold 59% of their currency reserves in USD and have held dollars as a reserve currency since 1944 as a result of the Bretton Woods agreement. Since then, businesses have found it useful to own and use dollars, no matter who you are. E-commerce has created a global network of vendors online, so now it’s useful for every vendor to sign up to services like Stripe to accept USD. 

Despite this proliferation of entities accepting USD, billions of people around the world don’t have access to bank accounts to store dollars and it’s not always easy to transact with USD person-to-person. When cryptocurrencies were first created, part of their promise was to change this by creating an open, fair, and inclusive global financial system. Proponents insisted that with this new kind of payment on the internet, the unbanked could be reached. Moreover, they could benefit from a modern user experience and an automated, lower cost infrastructure. An incredibly exciting idea! So far, however, cryptocurrencies have not lived up to that promise.

Only 1.5% of people on earth own Bitcoin (BTC), the most widespread cryptocurrency, and no more than 3% have ever owned any form of cryptocurrency.1 So it’s usually not easier to transfer money to someone using cryptocurrency than using USD. Because so few people have ever interacted with a cryptocurrency, the network of users is small and therefore the usefulness as global currency is extremely limited. 

It’s also hard to get any cryptocurrencies in many parts of the world. In some countries, you have to use the equivalent of Craigslist to find someone who is willing to meet up and trade your local currency for cryptocurrency -- a risky and antiquated method for a digital currency. In others, distribution is largely accomplished through centralized exchanges (e.g. Coinbase, Square). But nearly half the world’s population has no internet connection! Because so few people have cryptocurrencies -- and since this is so hard to fix -- their promise of widespread financial inclusion has not been realized. 

It’s increasingly likely that intercountry wealth inequality may actually destabilize free and stable societies. The EU nearly broke over relocating and integrating 7 million refugees. An order of magnitude more climate refugees, driven by worsening local conditions and the large disparity in economic outcomes, could strain global governance to the breaking point.

While some hoped that cryptocurrencies would help alleviate this inequality, they’ve almost certainly exacerbated it. The only way to distribute a cryptocurrency equally is at its inception. This is because of the massive value widely adopted currencies accrue over time. For example, if you wanted to distribute bitcoin evenly now, you’d have to purchase it from the owners, and with a $700B+ market cap it would be prohibitively expensive.

Enter Worldcoin. Worldcoin is a new cryptocurrency that began with a simple question: How might we rethink money, using network effects, to embrace economic inclusion and address inequality?

To do that, Worldcoin is creating a new, collectively owned global currency designed to be distributed fairly to as many people as possible. This will create a payments network, far larger than any existing cryptocurrency, that sidesteps the friction of local exchanges and brings humanity together. For the first time in human history, anyone in the world will be able to buy goods from a vendor anywhere in the world in a single currency. The vendor will be able to pay their suppliers in that currency, all the way down the chain. This will smooth out the process of international trade, bringing people across borders closer together.

This requires two steps:

1. Create a new cryptocurrency that’s easy to send digitally and easy to build on.

2. Give billions of humans their free share of the currency while protecting their privacy.

The first of these steps has been enabled by the rise of Ethereum and its developer ecosystem. It’s now possible to spin up new currencies that build on this existing infrastructure. Worldcoin takes best-in-class crypto infrastructure and builds on top of it to a final product that is fast, secure, and scalable. This new coin is called WLD.

The second step is a massive undertaking and difficult for three reasons. 

First, conventional distribution won't allow for reaching every human. Right now, there are roughly 7.9 billion people. To put that in perspective, most hardware startups are happy to get 100s of users in the early days, and even Apple -- the world’s largest company -- only has 1.65 billion devices in the world. It’s also difficult to reach every person on earth, since more than 3 billion people don’t have internet access. To reach those people, Worldcoin is designing and manufacturing an ‘Orb’, a physical device that can be shipped around the world to meet users where they are. 

Orbs are given to entrepreneurial individuals around the globe to onboard new Worldcoin users. Each of these individuals runs their own operation -- hiring and managing teams, marketing, and partnering with local organizations. In Chile, the world’s top Orb operator manages a team of twenty who support sign-ups for 8 hours a day. In a simple thought experiment, assuming 700 sign-ups per week per Orb and a realistic Orb production and distribution of 4,000 devices per month, Worldcoin could reach 2 billion users 2 years after launch.

Second, giving every person their share means no one gets more than that (e.g. by putting on makeup or a wig) -- a difficult problem to solve. This means the Orb has to tell people apart perfectly at a glance, something that even humans often fail to do. 

This type of protocol is called proof-of-personhood. Worldcoin requires a scalable proof-of-personhood protocol that guarantees uniqueness. CAPTCHA, a system to confirm that a human is checking a website, proves personhood but doesn’t prove uniqueness. Other verification protocols which require other users to meet virtually or in-person or to provide a financial stake are difficult to scale. 

One obvious proof-of-personhood protocol is biometric identification. A biometric system for humanity would need to create a detailed enough and immutable biometric record to be able to uniquely identify against the entire human population. Facial recognition technology doesn’t provide enough information to differentiate among billions of users. Fingerprints work -- but are easily changed. DNA isn’t currently scalable.

Worldcoin has solved their proof-of-personhood protocol by developing state-of-the-art hardware that enables a new Worldcoin user to scan their iris, generating a unique hash that enables the user to receive their WLD. The iris is hard to modify and can be checked for liveness -- not so for faces or fingers 😲. This iris scanner can uniquely identify people with an extremely low failure rate, and may enable digitization of systems like voting and passports in the future. It is also easy for a user to scan their iris -- they simply hold the Orb up to their eyes. 

Third, the Worldcoin team has to prevent any fraud that could bring down the network, and uphold user privacy. While Bitcoin and Ethereum have built confidence in blockchains as predictable platforms that are hard to attack, the Orb adds another dimension to the system. Orb design must make fraud difficult, and ensure no one prints a ton of WLD for themselves, or steals WLD from users. Spoofing attacks -- presenting a fake or non-human iris -- are prevented by employing multispectral imaging and anti-fraud algorithms. Tampering attacks are prevented through ground-up software and chip designs to detect tampering. To add an additional layer of security, Orbs will be constantly monitored and compared to other Orbs -- any anomaly or unexpected deviation will trigger a remote deactivation.

Worldcoin is built with user privacy at the core. First, iris scans pass through a one-way function, like a trapdoor you can’t climb back up. This means there’s no generating an image of someone’s iris from the trapdoor function’s output (the iris code). Second, the iris code causes the user’s Worldcoin wallet app on their phone to activate, but the code doesn’t actually get saved in the app or on the Orb, and there’s no way to know which code is linked to which app. This means that users don’t have to worry about their iris being linked to their wallet, while also ensuring that new iris codes can be checked against the central blockchain, to make sure that no one is able to register twice.

Worldcoin’s vision is extremely ambitious and there will be many challenges along the way, but this isn’t theoretical. As of today, Worldcoin has signed up 136,000 people, over half of whom signed up since September, with only 30 devices in the field!

They’ve also come far on the hardware engineering side, from the first v0 Orb used to sign up humans...

...to the current v1 Orb in the field now.

Our eyes are windows to our souls. A company asking you to scan your eyes can feel emotionally intimate in a way that’s hard to articulate. Worldcoin reaffirms our humanness via technology. The share of Worldcoin we each receive is a symbol of our shared humanity that reaches beyond borders, race, gender, age, language, and all the other things that keep us apart. Worldcoin says “Because you are a human, you are entitled to this token, this unit of monetary value.” It says, “Welcome to the human network.”

There is no one better positioned to pull this off than the Worldcoin founders, Alex Blania and Sam Altman. After studying physics and computer science in undergrad, Alex went on to study the application of AI on quantum systems at the Max Planck Institute, and spent time at Caltech researching deep learning to predict quantum systems. He’s been a hardware entrepreneur since high school, when he founded a vertical farming company. Sam is the co-founder & CEO of OpenAI and has been at the cutting edge of technology entrepreneurship for more than 17 years. He’s led companies across the technology stack, from social networking software to nuclear energy. The founders have recruited a world class team, with expertise in regulation, blockchain, hardware, and cryptography.

At Fifty Years, our sweet spot is supporting founders at the earliest stages who are building deep tech companies that can create massive positive impact and generate huge financial outcomes.

1. Deep tech: The Worldcoin Orb represents state of the art hardware and software engineering with incredibly difficult problems to be solved at every level of the stack, from cryptography to device security to blockchain engineering.

2. $1B yearly revenue potential: The value of the Bitcoin network is more than $740B. A payments network encompassing every person in the world that ushers in a new era of global trade could be worth substantially more than that.

3. Massive positive societal impact: Worldcoin has the potential to help the 1.7 billion people who are unbanked get access to a bank account. It will also enable any human to pay any other human, bringing more people into the modern financial system. And if successful, Worldcoin could make the largest dent in global wealth inequality we’ve seen in modern times.

Inspired by their vision for a more fair and more inclusive financial system, Fifty Years is excited to partner with Worldcoin alongside Andreessen Horowitz, Coinbase, 1Confirmation, Variant, Digital Currency Group, Sam Bankman-Fried, and other top Web3 investors. We’re looking forward to helping Alex, Sam, and team connect the world and make a massive dent in global wealth inequality.

Biotech is drinking through a firehose. Next-generation sequencing, CRISPR, and the high-throughput revolution have generated massive datasets that hold the secrets to hacking life. These methods are becoming easier and more standardized every day. While the velocity and volume of biological data is exploding, our ability to analyze it all is not.

Chewing through these databases is no easy feat. Biological data is inherently messy because biology itself is messy. Our high school textbooks led us to believe that life operates on a set of deterministic processes that can be predicted – coding DNA will be transcribed into RNA, plants will turn CO2 into biomass, and specific chemicals will give you cancer. 

But in reality, biology is sampling from a distribution of potential outcomes that can be analyzed statistically but may not be precisely predicted. At the cellular level, there is only a chance DNA is transcribed, CO2 is fixed, or a cell is induced to become cancerous. This lack of precise outcomes – or stochasticity – underpins any biological experiment and therefore the resulting data.

The difficulty of finding signal in the noise has only increased with modern technology. Until very recently, biologists would measure single readouts of their experiment. For example, they would hit cancer cells in a petri dish with a drug and measure how a single gene changed compared to unperturbed cells. But now, we use unbiased approaches that measure all gene expression changes using sequencing. Controlling for experimental error and stochasticity to generate inferences was hard enough when measuring one gene – it has become exponentially harder with measuring thousands.

The messiness and size of these datasets created a need for bioinformatics – a specific skill set that is required to turn -omics data into biological knowledge. Bioinformaticians spend years understanding the rigorous statistics that allow inferences to be made. They master the R libraries and Python packages that have been developed to comb through data. And they form the computational chops that turn one-off scripts into full bioinformatic pipelines or a folder full of sequencing data into an all-out data warehouse.

But herein lies a chicken or egg problem, the catch-22: obtaining the -omics data also requires a ton of training completely orthogonal to bioinformatics. Biologists hone their skills working with the stochasticity generator that is life to create well-designed experiments that feed these vital databases. 

But most biologists don’t have the tools to do bioinformatics. And most bioinformaticians have never held a pipette. Both of these non-overlapping skill sets are essential to both leverage the newest biotechnologies and sift through the data created.

Let’s take an example using the hottest tool in biology – CRISPR. These molecular scissors allow us to make targeted edits anywhere on the genome, effectively turning off any gene we desire. The work that has generated a Nobel prize and multiple breakthrough therapies has birthed CRISPR screens; an entirely new method that combines sequencing, CRISPR, and high-throughput biology. Here, a pool of cells are edited in thousands of different locations on the genome, one edit in one cell, turning off each gene. Combining experimental and computational approaches, scientists can ask questions like “which genes are essential for cancer to metastasize?” or “which genes help T cells inhibit autoimmunity?”. 

To pull this off, biologists leverage their skill sets to learn how to grow the cells of interest, get CRISPR in the cell, and create an experiment that tests the question – all before even starting the screen! While holding most of the parameters constant, they use CRISPR to precisely disrupt a single gene at a time and carefully measure if this perturbation had a biological effect. The process of doing this for thousands of genes is called a genome-wide "screen" and allows a rich characterization of behavior over the whole genomic landscape. Once the experiment is complete, they rip out the cell's genetics and submit it for sequencing.

With data hot-off the sequencer, the bioinformaticians then take over. Sequencers produce files that are too large to look at and aren’t very human readable. They contain hundreds of millions of small stretches of genetic information that were pulled from the cells and now need to be identified and quantified. 

Bioinformaticians use algorithms to map these reads back to places on the human genome, run data pipelines that connect these reads to specific cells, and execute code that tells them which cell got which edit and how much of each gene was expressed in a single cell. Each step requires a new pipeline and new understanding of the statistical framework that makes it work – all to produce a matrix of cells by gene that can be further analyzed and experimentally validated.

The training needed to pull off either the wet or dry portion of a single CRISPR screen is enormous. There are very few people who are excellent at both, creating a problem for anyone looking to leverage this method.

So, should a company, lab, or institute use limited resources to hire biologists to generate data without the ability to effectively analyze it? Or hire bioinformaticians and sacrifice on the ability to generate the data goldmine that will drive the agenda forward?

We think they shouldn’t have to choose. Enter LatchBio.

As undergraduates at UC Berkeley, LatchBio co-founders Alfredo Andere, Kenny Workman, and Kyle Giffin recognized how many potential life-saving therapies, climate improving biomolecules, and novel ways to hack biology were sitting undiscovered in datasets that humanity didn't have the bandwidth to dive into.  Taking the deep expertise in computer science they had gained from working at companies like Asimov, Facebook, Google, and Serotiny; leading Machine Learning at Berkeley; and their bench experience at places like the Joint BioEnergy Institute and the Lawrence Livermore National Laboratory, the trio left their degrees behind and founded LatchBio.

LatchBio’s platform puts analysis back in the hands of biologists, enabling them to leverage the explosion of data they’re generating. LatchBio created intuitive out-of-the-box tools that abstract away all the arcane statistics, code, and computational backend that inhibit biologists from working with data, allowing anyone to build their own data warehouses, analytical tools, and bioinformatics pipelines.

In the CRISPR screen example, any biologist using LatchBio’s platform can upload their data directly from the sequencer with a click of a button. Sequence QC, sequence-to-genome alignment, gene expression quantification, and edit site identification are all run in the cloud without the biologist even knowing – all they see are simple-to-use drag and drop tools neatly assembled into a flow diagram. Data storage and visualization are also just as easy to do, all taken out of a terminal and into a user-friendly web interface.

But don’t worry bioinformaticians – LatchBio is not looking to make you obsolete! Instead, LatchBio wants to empower bioinformaticians to focus on making the tools that give biological data meaning. Instead of wasting time running the same code over and over for biologists, bioinformaticians will be able to use LatchBio’s platform as the next generation of GitHub for computational biology. Unlike current software repositories, the workflows generated through LatchBio will be immediately accessible to biologists, ensuring tools don’t have huge learning curves until they become widely adopted. This accelerates software development by creating a space where biologists with data and bioinformaticians with tools under construction can collaborate and support each other.

And they won’t stop there. LatchBio is initially focused on doing the types of CRISPR workflows described above to accelerate the reach of these important therapies. In the future, they’ll incorporate every workflow computational biology has developed, from single-cell sequencing to metabolomics to phylogenetics, all under one roof. They’ll generate out-of-the-box machine learning to democratize access to these even more challenging algorithms. And they’ll streamline data sharing so well that with a few clicks, data can be reproduced from published work and publicly available databases.

In a future where LatchBio succeeds, all compute power the world has to offer will be leveraged to analyze biological data. LatchBio’s web-based platform will make it incredibly easy and seamless for bioinformaticians to develop and biologists to deploy bioinformatic workflows. By tearing down silos of knowledge that currently inhibit progress, LatchBio can leverage every idle CPU to uncover hidden connections in disparate data centers, radically accelerating biotechnology and medicine.

At Fifty Years, our sweet spot is supporting founders at the earliest stages building deep tech companies that can generate huge financial outcomes and create massive positive impact.

1. Deep tech: Alfredo, Kenny, and Kyle are leveraging their technical expertise in computer science, computational biology, bench science, and machine learning to create a platform that is accessible to everyone in the biology stack.

2. $1B yearly revenue potential: Every single new biology endeavor must hire a computational biology team to build out data-warehouses, analytical tools, and bioinformatic pipelines just to make use of their data, effectively reinventing the wheel each time. LatchBio fills this need, serving anyone who uses biological data – virtually every biology lab, institute, and company.

3. Massive positive societal impact: Currently, data could take weeks to analyze as access to bioinformaticians and compute resources hinder the process. LatchBio democratizes access to these tools, turns this into minutes, and accelerates the development of more sophisticated tools. This means life-saving therapies and environment healing tools are identified exponentially quicker. 

Inspired by their technology and vision for the future of computational biology, Fifty Years is excited to partner with LatchBio in their seed round led by our friends at Lux Capital, with participation from General Catalyst, Haystack, Brian Naughton, and computational biology founders. We’re looking forward to helping Alfredo, Kenny, and Kyle lay the bricks for the biocomputing revolution.

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