Proteins are the building blocks of life. Composed of molecules called amino acids, proteins perform an incredible variety of functions, from catalyzing reactions to providing energy, to transporting other molecules. Natural proteins are the result of billions of years of evolution and adaptation within living organisms, allowing them to thrive in their specific environments.
In recent years, the discovery of these natural proteins has become the basis for breakthrough products across multiple industries. TechBio solutions are a powerful route away from petrochemicals, and while these proteins can replace many carbon-intensive inputs and add enormous value to our economy, less than 1 percent of natural proteins have been discovered. This lack of data creates large biases in the datasets required for AI design that fundamentally relies on access to large and unique data.
Natural protein discovery and AI design are increasingly interdependent, and their combined power is much greater than the sum of their parts. As machine learning advances, it continues expanding biological research by enabling the analysis of vast amounts of complex biological data to identify patterns, make predictions, and speed up new product development.
Biodiversity “hotspots” located in pristine geographies where human activity has yet to affect these ecosystems are the ideal sites for collecting and sampling these natural proteins. Unfortunately, human activity has already severely altered 75 percent of land and 66 percent of marine environments. When these diverse habitats are lost, potential solutions to critical human and planetary health conditions can be lost with them. And thus, preserving these ecosystems profoundly enhances our ability to find proteins in the future that can save lives.
With this understanding of both the environmental and economic imperative of preserving biodiversity, when we discovered Basecamp Research we were immediately intrigued by their mission, technology, and talented team.
What is Basecamp Research?
Basecamp Research is revolutionizing protein discovery and design by building the world’s largest protein knowledge graph. Their approach can predict complex protein functions and performances, not just structure, to drive real-world product discovery. Though the company was founded less than four years ago, their team has already increased the number of proteins known to science by more than 50 percent.
Basecamp Research’s platform combines field collection, a knowledge graph of nature-derived proteins, and machine learning techniques for the purpose of bio-discovery and in silico testing.
The company’s knowledge graph, called BaseGraph™, is enriched with environmental and evolutionary contextual information for the proteins they discover, and focuses on the relationships between various data points rather than simply presenting isolated data. By representing this data as a network (‘recreating the network of life in a supercomputer’), they can derive the complex functions, properties and performances of new proteins, which can’t be deduced from their structure alone.
BaseGraph™ is superior to current publicly-available datasets in both its size and the completeness of its metadata. It connects hundreds of millions of protein sequences with their rich environmental contexts, which are recorded by both Basecamp Research and numerous partners around the world, including 22 countries thus far.
This singular, highly practicable metagenomic data capability can have profound implications in driving the next wave of software-enabled biotech innovation.
When AI is designed with accurate computational prediction of protein function and performance, it can be a game changer for product development timelines and reduction of carbon-intensive inputs. According to McKinsey, biological processes could produce roughly 60 percent of physical inputs to the global economy in the next two decades alone.
BaseDiscovery is Basecamp Research’s protein discovery platform. It uses BaseGraph™ data to enable clients to design advanced protein products for a variety of industrial applications, and at an unprecedented speed.
One of the company’s pharmaceutical clients, for example, spent 2 years and millions of dollars searching for an enzyme that would enable them to manufacture a chemical at scale, but couldn’t find one that worked. Basecamp Research’s technology was able to identify a successful enzyme within a week. BaseDiscovery uses continuous feedback to drive optimal outcomes, with input guidance improving as output data is integrated, creating an ongoing cycle.
Basecamp Research’s Role in the Low-Carbon Bioeconomy
The low-carbon bioeconomy possesses great potential for startups, investors and society at large.
In September 2022, the White House committed over $2 billion to advance President Biden’s National Biotechnology and Biomanufacturing Initiative. Half of this funding will be dedicated to developing “bio-industrial domestic manufacturing infrastructure over five years to catalyze the establishment of the domestic bio-industrial manufacturing base.” Many of these new products that use biological inputs remove petrochemical inputs and address biodiversity loss through more sustainable manufacturing practices that require less raw material extraction.
Basecamp Research’s solution also presents a fascinating and economical incentive for biodiversity restoration. The company contributes royalty earnings back to the ecosystem stewards managing the land where sampling occurs. In this way, they’re encouraging ecosystem protection and distributing the shared benefit of local discoveries, which bioprospecting has historically—and notoriously—overlooked. This also supports the Nagoya Protocol, an international agreement aimed at sharing the benefits of genetic resource use in a fair and equitable way.
With backgrounds in biochemistry, engineering, and expedition science, co-founders Oliver Vince, Ph.D., and Glen Gowers, Ph.D., created Basecamp Research with the goal of combining true global exploration of biodiversity with the latest computational AI advances to usher in a new generation of sustainable biological products.
“To date, we have explored far less than 1 percent of all the biodiversity on our planet; of that, we understand an even smaller fraction. This has created a bottleneck for product development in biotechnology companies, meaning only a small number of products can be economically made with biology despite the potential of this industry to move us away from petrochemicals towards more sustainable solutions.” ~ Glen Gowers, Basecamp Research Co-Founder and CEO
Valo’s Investment in Basecamp Research
Through our biodiversity research, we recognized the criticality of biodiversity preservation and wanted to find an economically sustainable business model for investing in its regeneration and protection.
Basecamp Research falls into the larger trend of software-led TechBio startups serving biotech clients, and made sense within Valo’s larger thesis for a few key reasons:
Machine learning supports biology breakthroughs
Major advances in natural language processing (NLP) are making it possible to train models to identify complex protein sequences more efficiently than ever. Insilico Medicine’s Pharma.AI condensed the drug discovery timeline in half from 72 months down to 30 months for a pulmonary fibrosis drug that is now in clinical trials. DeepMind’s AlphaFold predicted the structure of almost every protein known to science, and researchers have already used the system’s data to decipher proteins that impact honeybees’ health and to develop a malaria vaccine. One.Five is using machine learning to discover more ecological packaging, and Amai Proteins used their proprietary computational protein design platform to create a sweet designer protein that replaces added sugar in food products, making them healthier and using fewer natural resources in the production process. Motif FoodWorks looks for proteins that solve for key taste and nutrition targets, then produces the proteins at scale using fermentation; they recently released a breakthrough ingredient that gives plant-based foods a texture and eating experience similar to meat products. Given that all these advances have been made in just the last few years, the transformative possibilities of machine learning in biotechnology in the future seem nearly endless.
The biomanufacturing transition is critical to a low-carbon economy
Compared with chemistry-based processes, biologically-based processes can occur at lower temperatures, requiring less energy. For this reason alone, advancing biomanufacturing will be critical for creating a low-carbon economy. The Biotechnology Industry Organization estimates that biomanufacturing could reduce emissions by at least 80 percent relative to traditional processes for chemicals and consumer products, and (as mentioned above) last September President Biden signed an Executive Order to advance biomanufacturing innovation, citing the technology’s potential to herald new solutions in energy and climate change.
The protein discovery market is substantial and growing
The global protein engineering market was sized at $3 billion in 2020 with a 13 percent CAGR, and is projected to reach $7 billion by 2028. The precision fermentation market size alone is expected to reach $34.9 Billion by 2031, and proteins made using this method are on track to be 5 times cheaper than traditional protein by 2030, and 10 times cheaper by 2035. Even conservative estimates indicate alternative proteins could account for 11 to 22 percent of the overall protein market by 2035. Once a protein is validated for the manufacture of a given food, material, or pharmaceutical ingredient, it can scale up rapidly, as evidenced by the doubling in production output of citric acid by fermentation in the early 2000s.
We’re excited by the many software-enabled solutions that are unlocking the bioeconomy, moving us away from petrochemical-based goods and towards a circular economy that is non-depleting to the many diverse, vital ecosystems of our planet.
We continue to search for companies solving the many challenges associated with growing biomanufacturing and applying it to emissions-intensive industries.
If you’re a biomanufacturing or biodiversity focused startup, we’d love to hear from you. Please reach out to our team at firstname.lastname@example.org.