What We’ve Learned Since 2012: Biology as a Technology Platform

In September 2019, we published the blog post “Founder-Focused Investing in Human Health and Biology” to share how True was thinking about biology as an investment category.

We weren’t traditional biotech investors. But we began deeply believing in a new type of entrepreneur: scientist-Founders who were more like the technical leaders we’d previously backed in consumer, infrastructure, and enterprise software. And these Founders were starting to work on problems at the intersection of software, data, and biology.

 What we got right was the thesis: Back ambitious Founders with unique cross-discipline expertise building at the edge of emerging markets.

What we underestimated at the time was the pace: More than six years later, we think we’re at an inflection point — one that is harder to see from the outside than it appears from where we sit — and we want to describe what we’re observing across our portfolio.

The same forces, compounding

We made our first investment in 2012 in a company called Moleculo. Over the next half decade we continued to see incredibly talented teams pair together different types of technologies in new and novel ways that could fundamentally change how we treat diseases, study human health, and manufacture better, healthier products. The same enabling technologies driving software (falling costs to experiment, open platforms, and bottoms-up distribution) were starting to apply to biology.

That argument has only gotten stronger — and it’s moved faster than we expected. The cost to sequence a genome has fallen roughly a million-fold since The Human Genome Project. Protein structure prediction, which for 50 years was considered one of the hardest open problems in biology, was largely solved in the span of a few years. Foundation models trained on biological data are now producing outputs that rival or exceed what teams of human researchers can generate.

The long-term potential is greater than we could have ever imagined.

What we’re building toward

Across the True portfolio, we’ve now made more than 30 investments in companies at the intersection of biology and computation. Rather than simply describe the category as it’s expanded, here are a few of the companies and what they’re building:

• Deep Genomics: We backed Brendan Frey and Deep Genomics at the seed stage in 2015, well before “AI drug discovery” became an investable category. Brendan spent his career at the intersection of deep learning and human genetics. Deep Genomics has since built AI systems that predict how mutations in DNA and RNA cause disease. Its BigRNA platform is a foundation model for RNA biology that represents a genuinely new kind of instrument for understanding genetic function at scale.
• Fauna Bio: Ashley Zehnder left a veterinary career because she believed hibernating mammals had already solved some of the hardest problems in human medicine. No one was systematically mining the experiments that evolution has been running for millions of years, so Fauna Bio built Convergence AI to identify therapeutic targets for human disease by studying the genomics of extreme biology in other species. The company’s collaboration with Eli Lilly validates not just the company but the founding insight. This is one of our favorite portfolio examples of a Founder with genuine scientific expertise seeing something the market hasn’t priced.
• Enveda Biosciences: Viswa Colluru bet his personal savings on the idea that medicinal plants — the source of some of the most important drugs ever discovered — contained a largely unexplored chemical library. Enveda’s platform combines knowledge graphs, metabolomics, and machine learning to translate plant chemistry into drug candidates at a pace that is roughly four times faster than industry norms. The company is now dosing patients in three separate clinical programs spanning atopic dermatitis, obesity, and inflammatory bowel disease. More than 99% of plant chemistry has never been characterized, and Enveda is systematically working through it.
• Basecamp Research: Glen Gowers and Oliver Vince met at Oxford, but their first significant sequencing project was in a tent on an Arctic icecap. They’ve worked with more than 150 partner organizations across 28 countries to sequence the planet’s protein diversity, resulting in BaseData, a dataset that contains over 10 billion novel protein sequences. EDEN, the company’s family of AI models, can design new proteins and genomes with a level of novelty and controllability that public databases can’t match. Basecamp has even demonstrated the first AI-designed enzymes for programmable gene insertion, a potential alternative to CRISPR. It’s all because of the founding insight: the natural world has already solved many of our problems.

Although each of these companies is doing something different, together they illustrate a portfolio building the infrastructure for a new era of biological discovery and medicine.

What we’ve learned since 2019

The north star from our 2019 blog post still holds: find the best Founders, wherever they’re spending time, and back them early.

Founders who built early intuitions about the latest tools are now years ahead, in part because the tools changed faster than expected. AlphaFold, large language models trained on biological data, spatial biology, and single-cell sequencing are not incremental improvements. They represent qualitatively new instruments for reading and understanding biological systems. 

The best Founders see the convergence before the market does: Ashley saw that hibernating animals held secrets worth billions, Viswa saw that medicinal plants had been abandoned too soon, and Glen and Oliver saw that the biodiversity of the planet was an unmined database. In every case, the insight was only obvious in retrospect.

Looking forward

We ended our 2019 blog post with a line from the book Complexity: The Emerging Science at the Edge of Order and Chaos by M. Mitchell Waldrop: that the magic of new ideas lives at the intersection of two or more fields of study. We still believe this, but the intersections are multiplying: AI and genomics, evolutionary biology and drug discovery, spatial biology and delivery, planetary biodiversity and protein design, veterinary science and human therapeutics, and so on.

Each new intersection is a new potential company led by a Founder, who – if successful – makes the adjacent intersections more legible. 

If you’re a founder working to fix a big problem in human health, and your work lies at a compelling intersection of multiple fields across computation and biology, we’d love to talk and see what we might help you unlock.

Share