While companies like OpenAI and Anthropic continue to popularize the idea of using ordinary language to ask artificial intelligence agents for answers to their questions, write their proposals or draw pictures, a London startup called Basecamp Research has raised $60 million to tackle a new frontier. It’s building an AI agent that not only answers any question related to biology and the biodiversity of the natural world, but produces new insights that humans could not achieve on their own.
“There is an enormous data gap that exists today where people are training [biology] models,” said Glen Gowers, the co-founder and CEO of Basecamp Research, in an interview. “Some of the top pharma companies in the world are training models that simply don’t see enough of the natural world.”
The funding comes on the heels of notable momentum for the startup. To date, Gowers said, Basecamp Research has inked more than 100 partnerships with organizations across 25 countries to expand its database with primary-source information. About 15 of those are using its AI to help build new products. Procter & Gamble is using the models to design enzymes for detergents to clean stains at cold temperatures. Colorifix is working on formulations for new fabric dyes that are more sustainable.
Notably, Basecamp Research claims that its foundational model, BaseFold, outperforms AlphaFold 2 — whose creators at DeepMind just today won the Nobel Prize for Chemistry — when it comes to accurately predicting large, complex protein structures and small molecule interactions.
The startup’s approach to building an AI for biology is incredibly ambitious: It is building its models from the ground up.
Gowers and his co-founder Oliver Vince are both biology PhDs who met back in their undergraduate days at Oxford. The name “Basecamp Research” comes from time they spent living on an ice cap, Vince said, doing DNA sequencing using hardware they had built themselves.
“We pioneered the first mobile DNA sequencing laboratory,” he said.
Basecamp Research has adapted components of that hardware “into very small units” to collect data for the newer startup, he added.
There have been hundreds of books, thousands of pages of research, and petabytes of data generated over decades in the field of biology. The problem is that much of that data is outdated, unstructured and simply inconsistent. So to build its AI, Basecamp Research is meticulously gathering primary data first-hand to build its models from the ground up. The aim is to produce an AI that will be able to have better insights into biology than any human can, simply because of the breadth of data that can be brought to bear.
“We use a combination of exploration — literally going around the world to pick up data, understand hot springs, volcanoes, those sorts of things — and combine that with an artificial intelligence program that is focused purely on training massive language models to build, effectively, a ‘ChatGPT’ for nature,” Gowers said. The startup has also amassed what he said may well be the “largest compute cluster” dedicated to the natural world to power this.
Just as ChatGPT’s superpower is in recalling and formulating natural-language responses to questions, the same goes for what Basecamp Research is setting out to do. The difference is that the breadth of information in the world — Vince estimates that we have only managed to capture some 1% of information about our world’s biodiversity — means that we mere humans don’t even have the capacity to ask the right questions at this point.
Or, as backer Andy Conrad of S32, previously CEO of Verily Life Sciences at Google, puts it: Basecamp Research’s platform can “address questions that the biopharma industry hasn’t even known to ask.”
“So rather than something that understands the language of text or speech, [our platform] understands the language of DNA, understands the language of biology, and therefore can go past what humans can do in the biological design space,” Gowers continued. “We are traditionally very bad at understanding DNA, and therefore these language models, if given enough data, can really, really, really excel.”
The Series B, led by European firm Singular, comes alongside what Basecamp Research is describing as a “multi-year collaboration” with Dr. David R. Liu and the Broad Institute, a major biomedical research center that works across MIT and Harvard. The plan is to use the funding to continue building the startup, both through partnerships with other biomedical and research organizations, and by amassing more data to expand its models.
Beyond this, Basecamp Research’s roadmap includes helping organizations with drug discovery and other large challenges that touch on understanding and making better use of the natural world.
While there are commercial deals being linked, the startup’s work with the Broad Institute sheds light on what form this might take. Right now, the labs run by Dr. Liu are looking at “novel fusion proteins and other large molecules,” used to create genetic medicines, and they are using datasets from Basecamp Research to develop them.
What is less likely, it seems, is an actual “ChatGPT”-style interface for the startup. Right now, Gowers said the company sees more opportunity in working on a B2B basis rather than channeling resources into building a product to engage with the general public. That’s not to say such a product might not be on its roadmap down the line, he added.
This appears to also be the approach that other companies building large “science” models are taking: Jua, which is building a large physics model, initially targeted organizations that need better insights into weather patterns.
Basecamp Research is not disclosing its valuation, except to note that this Series B is an up-round. For some context, the startup has raised $85 million to date, and its previous investors include Hummingbird, True Ventures, and strategic backer Valo. PitchBook put its last valuation, from 2022, at a very modest $71 million.
The Series B also saw participation from S32, redalpine, André Hoffmann, the vice-chairman of Roche; Feike Sijbesma, the chair of Royal Philips and former CEO of DSM; and Paul Polman, former CEO of Unilever.