For centuries, people had chewed willow tree bark to relieve pain, but it wasn’t until the 19th century that scientists at the chemical company Bayer isolated and eventually patented the active ingredient. Its modified version is like aspirin.
Aspirin is just one example of a drug derived from natural sources. In fact, the World Health Organization estimates that About 40% of modern pharmaceutical products It has roots in the treatments used by our ancestors.
Even with this remarkable success in harnessing nature’s bounty, scientists estimate that they have discovered only a small fraction of natural chemical compounds that can be developed into powerful medicines.
This is partly because identifying, isolating and testing molecules from nature is complex and takes longer than synthesizing new compounds in the laboratory.
Viswa Colluru, one of the early employees at Recursion Pharmaceuticals, which went public in 2021, decided that artificial intelligence and other technologies could speed up the process of discovering new drugs from nature.
In 2019, Colloro left Recursion to start Enveda Biosciences, a biotechnology company based in Boulder, Colorado, that analyzes plant chemistry to discover potential medicines.
Colluru told TechCrunch that Enveda tapped into all the digital information in the world about how humans across cultures use plants to treat pain and disease.
“We discovered that geographically separated cultures from around the world were more likely to use similar plants for similar diseases and symptoms, even though they never spoke to each other,” he said. “They’ve discovered that a certain plant helps with a stomach ache, or a certain plant helps like a fever or a headache, and that’s literally thousands of years of empirical human wisdom.”
Today, the company’s database includes 38,000 medicinal plants associated with approximately 12,000 diseases and symptoms.
Once Enveda’s AI identifies plants with the highest likelihood of providing a treatment, it collects the materials and tests them using the company’s AI model. Unlike traditional methods of studying single molecules, Nvida’s transducer model can decipher the “chemical language” of the entire sample.
“Once we know what it looks like, we can prioritize the right combinations of molecules and say, ‘This is going to be a drug someday,’” Colloro said.
Nvida’s approach is starting to pay off. Two of the company’s drugs — one to treat eczema and one to treat inflammatory bowel disease — are expected to begin clinical trials later this year, according to Colloro.
The company’s scientific progress has attracted the attention of investors. Enveda announced Thursday that it has raised an additional $55 million Series B from new investors, including Microsoft, The Nature Conservancy, Premji Invest, Lingotto Investment Fund, and existing backers Kinnevik, True Ventures, FPV, Level Ventures and Jazz Venture Partners. The new financing brings the company’s total capital to $230 million.
The extension round allows Enveda to add long-term strategic partners to its cap table, and the company plans to raise a Series C later this year after clinical trials begin, Colloro said.
Microsoft is also offering some cloud credits as part of the deal, but this is separate from its cash investment, according to Colluru.
While sampling plants to find medicines is an old approach, Enveda is one of the few companies doing it with the help of artificial intelligence. UK-based Pangea Bio also studies plants to discover drugs to treat neurological conditions.
Naturally, much of the attention in this area has gone to marijuana and natural sources have been known to produce psilocybin in so-called “magic mushrooms” or other psychedelic substances that have the potential to treat mental health disorders, but Envida is not. Interested in studying its compounds.
“Everyone is focused on cannabis and drugs, and it’s just a small part of the natural world,” Colloro said. “The natural world is so rich in chemical diversity and biological effects that studying just 100 plants is enough to yield so many potential medicines that we don’t know what to do with them.”