Bio brings amazing new developments for healthcare, industrial and consumer products. But despite many technological advancements, Bio is still very expensive. Just look at some of the products’ price tags: a cure for blindness priced at $425,000, or treatment for life-threatening disease at $272,000; Memphis Meats, a startup company developing lab-grown meat, synthesizes burgers at a cost of $2,400 per pound.
To make Bio more impactful on people’s lives, costs need to go down. In healthcare, taking costs down would allow therapies become accessible to more patients. In Bio consumer applications, the cost challenge is even bigger: prices need to be comparable to everyday commodities, far lower than what they are today.
Production has a leading role in driving up costs, with scalability being one of the biggest challenges in Bio. Production in Bio is expensive because of the investment required in capital and time to set up the equipment and production process, which are typically unique to each product.
Most research in Bio is made today in a petri dish. This is a very small environment, where researchers can control the growth of the organisms that produce the Bio product and extract the desired product relatively easily. But what works in a petri dish does not work in a bioreactor, the scaled-up counterpart of a petri dish. Bio production occurs inside bioreactors, where there is a closed environment filled with millions of bacteria or yeast that have been genetically modified to produce the desired Bio product. Bioengineers need to control their growth, supply nutrients and other life support, and eventually purely extract the end product. This micro-cosmos is very challenging to maintain and control. Unsurprisingly, designing a bioreactor is a complex engineering task. The significant differences between a petri dish and a bioreactor pose a risk in Bio product development. Successfully scaling up a Bio production process is considered a major milestone for a company.
Bio products have to be scaled up from the petri dish long before they reach the market. Large quantities are needed to test a product. In the case of therapeutics, large quantities are needed to test the effects of the product on animals, even before clinical trials. In the case of consumer applications, such as lab-grown meat, initial testing of a product usually requires pounds of material.
This means there is a high financial threshold for Bio innovation. A small group of developers cannot build a prototype without raising significant capital. As a result, Bio development is currently confined to the realm of well financed startups and large corporations.
We believe the financial threshold to develop Bio products has a detrimental effect on Bio innovation. Making Bio development more accessible will bring more developers and ideas to the field. It will risk less capital being risked, which will also bring more investors to the field. All these will allow Bio therapies to become more common, and Bio to become commercially viable and impactful in areas beyond healthcare.
Compared to Bio, Tech no longer suffers from this cost threshold problem. The barrier to entry for Tech developers is low. A small group of developers with their laptops can code an MVP and even launch a scalable product with very little cost or infrastructure setup.
We think two major landmarks made Tech development the way it is today, and we believe Bio will follow similar evolutionary steps.
In the late 1970s computers were big and expensive, and mostly used by and focused on enterprises. The next evolution of computers did not come from large corporations like IBM, but from hackers. It was enthusiastic homebrewing computer hobbyists that adopted the latest technology in electronics and built computer kits for the “home user”. They started with kits and homebrewed computers, and building more accessible hardware. Within that group, two hackers named Steve, working out of their garage in Los Altos, built the world’s first computer with an accessible price point, a machine truly made for the home user.
We believe the same innovation will occur in Bio. Smaller scale Bio production and equipment will become more accessible for users and have a lower price point. Example of this emerging trend are companies like the Belgian company Univercells, which received funding from the Bill & Melinda Gates Foundation to develop modular bioreactors.
But it will also be done by outsiders to the biotech industry. These outsiders include bio-hackers and the DIY-bio movement. The biohacking movement is fueled by scientists that promote bioengineering at home and in DIY labs. They believe Bio should be accessible to all and promote sharing, openness and access to Bio, reminiscent of the hacker ethic code present in the computer revolution. Some of the biohackers are motivated by lowering the high prices of Bio, specifically that of therapeutics, and wish to use their knowledge to promote at-home production of therapeutics, like the $30 EpiPencil that came as a response to the rising price of the EpiPen. Others are motivated by spreading education and hands-on experience with Bio to promote innovation, like Genspace in Brooklyn, NY.
Some biohackers, like Josiah Zayner, have started companies to sell kits for homebrew Bio, like Gene editing tools sold for $120. This, in our view, is similar to the homebrew computing hackers in the 1970s. We believe this will result in an advent of small, affordable Bio-engineering tools, similar to early personal computers. Eventually, these innovations will reach the mainstream Bio, and the end result will be more developers and more Bio-engineering innovation.
In addition, we believe biohackers will soon face the challenge of scalability and need more production volume at a lower cost. This will push them to innovate and build new tools that will allow for the production of Bio at meaningful volumes without the need for expensive investment in infrastructure. This leads to our second landmark.
Simply put, a cloud is just a collection of similar, managed servers. Before cloud computing, a Tech startup company needed to purchase its own servers and pay ongoing maintenance costs. It also needed to invest in infrastructure in order to have enough network bandwidth to handle incoming traffic. When a startup’s user base expanded, the company needed to further invest in servers and infrastructure to handle the increased load. In the 1990s, an internet startup needed to invest $10-$20M in infrastructure to have a scalable product. Twenty years later, the cost was reduced to below $100/month per server, allowing Tech startups to launch a scalable MVP with less than $1M. The advent of cloud computing platforms made this even easier to do. Linking multiple servers together in a managed farm turned capital expenditure into payment for a dynamic service, allowing scaling up and down according to needs.
We believe a similar revolution will occur in Bio, and will drive its next evolution. For example, we envision an aggregation of bioreactors into a single managed facility, using automation software and robotics. Newer bioreactors will be developed with smaller footprints and integrated data gathering that will later be analyzed and controlled by software. AI software will respond to the continuously changing micro-environments and better control each bioreactor with a faster response time, while robotics will allow the needs of multiple bioreactors to be addressed simultaneously. The aggregation and efficient management of large numbers of bioreactors will allow us to create the equivalent of a managed “Bio-server farm”.
Today, we can see a somewhat parallel trend in what is called “cloud biology”. In contrast to the Bio production we envision, cloud biology startups are focused on the discovery phase at the lab. Startups are using robotics, automation software and AI to run lab experiments off-site, in the “cloud”. For example, Transcriptic, with $28M total funding, is developing fully automated assays to help startups run drug discovery experiments in the cloud; Emerald Cloud Laboratory, with $34M total funding, is using a script language to make it easier to plan and execute remotely controlled experiments ; while Vium, with $30M total funding, aims to automate and enable data-intensive monitoring of off-site preclinical testing in mice. These startups attracted investors such as AME Cloud Ventures, Data Collective, Founders Fund, Google Ventures, Lux Capital and OS Fund.
The “Bio-server farms” we envision will allow low cost, dynamic scalability of Bio production. It will allow developers with virtually no investment in infrastructure to produce significant quantities of their prototype for testing.
The “Bio-server farms” will also significantly reduce the risk in developing Bio-therapeutics and Bio products: by quickly allowing the low-cost production of enough quantities for testing and clinical studies, we would risk less capital and learn faster whether a product works. This is a major risk reduction step that cannot be done today, either in labs or cloud biology companies.