At Enveda, we’re on a mission to deliver hope to every patient by transforming how the pharmaceutical industry discovers medicine. Our approach begins with a bold realization: over 99% of life’s chemistry may be unknown to science. Yet life itself is the constant transformation of those molecules—millions of chemical reactions taking place in every cell, every second.

We’re using AI to unlock this hidden chemical code, not just of life, but of living. Our platform identifies unknown molecules and deciphers what they might do, translating billions of years of evolutionary intelligence into practical solutions, starting with new medicines. None of this would be possible without modern AI. It’s not a distant promise for us—it’s a core enabler, powering everything from how we uncover new compounds to how our teams work more efficiently.

At Enveda, we see AI in two critical roles: first, as the foundation of our technology, allowing us to explore uncharted chemical territory. Second, as a multiplier—an intelligent tool that enhances the work of every scientist, strategist, and thinker on our team. By leading with the question, “Can AI do this for me?” We’ve created a culture of curiosity, efficiency, and breakthrough discovery.

In the first role, AI goes beyond incremental innovation—it reinvents what’s possible in medicine.

The major challenge that led us to AI was the sheer scale of the problem. On a macro scale, we’ve barely scratched the surface of what it means to be alive in chemical terms. Of the molecules that exist in nature, humanity has only identified a fraction of a percent. Even though nearly half of all FDA-approved small-molecule drugs come from natural sources, science has only cataloged about 300,000 natural compounds.

Faced with the staggering possibility of billions of undiscovered molecules—any one of which could become tomorrow’s medicine—we saw two paths. One was to keep relying on legacy methods, which would take centuries and, even theoretically, could cost trillions. The other was to rethink the entire approach to understanding the chemistry of life. We chose to rebuild the scientific toolkit from the ground up, with AI as the cornerstone.

We knew we were onto something special when our AI platform predicted a completely new molecule—faster, cheaper, and with less material than ever before. When we validated it using traditional methods, it was spot on. Our platform predicted several other previously unknown molecules accurately enough that our chemists were able to sort through the proverbial needles in nature’s haystack, the small fraction of molecules with interesting structures that we could work to turn into a medicine.

Traditionally, discovering the structure of a natural compound meant isolating and analyzing molecules one by one. It’s slow, expensive, and manual. We’ve flipped that model. Now, using mass spectrometry, we generate molecular fingerprints for thousands of compounds at once. Historically, such data were used exactly like we use human fingerprints – to re-identify previously known chemistry discovered using traditional methods by searching a database. On their own, these fingerprints don’t mean much to humans, but they’re exactly the kind of data AI excels at decoding. As it turns out, the “meaning” of each piece of this fingerprint is altered by the other pieces, much like sentences in human language. For example, the meaning of the word “bank” may change whether it is used in the context of a “river” or “money”. In other words, there was a grammar to these molecular fingerprints – and we could understand it using AI trained on a large enough dataset. Because if we understood it, we could translate it.

Today, transformer models translate those fingerprints into full chemical structures—just like language models translate sentences with very high fidelity, even between languages with sparse training data (for example, from Occitan to Asturian). That shift has changed everything. Instead of analyzing one molecule at a time, we can now identify thousands in one go. And we’ve already expanded the catalog of known natural compounds from 300,000 to over 1.5 million in our “Library of Life.”

Identifying molecules is only the starting point. The real challenge in drug development—and the main driver of its high cost—is that most compounds that succeed in the lab fail in people. Today, nine out of ten drug candidates don’t make it through clinical trials, despite years of research and massive investment. This 90% failure rate pushes the cost of bringing a single new medicine to market as high as $6 billion. It’s an approach that simply can’t scale. Today, the industry’s effort largely revolves around identifying new drug targets or “new biology”, ignoring chemistry’s critical role in the equation.

At Enveda, we are changing that. By decoding nature’s chemistry at scale, we’re delivering better molecules into the drug discovery process, ultimately producing and moving drug candidates to clinical trials four times faster and at nearly one-tenth the cost. And because many of our compounds are rooted in natural biology, we believe they’re more likely to succeed in humans. In fact, when we analyzed over 8,000 molecules tested in trials, those that resembled naturally evolved chemistry had a nearly 50% better shot at reaching Phase III trials. Nature still knows best—AI just helps us learn from it faster.

We’ve already seen the results. In just four years, we’ve built a pipeline of more than ten candidate medicines—productivity that rivals large pharma teams with billion-dollar budgets. That kind of scale is only possible because of AI.

But this isn’t just about doing more, faster. The molecules we’re discovering are fundamentally different. Our lead compound, for example, tackles inflammation in an entirely new way, offering powerful results without the toxicity of current drugs—and in a convenient oral form. It has the potential to change the game for conditions like atopic dermatitis (eczema) and asthma that affect millions worldwide.

This is the foundation of everything we do at Enveda. We’re not just discovering more. We’re discovering differently. And while we’re focused on medicine today, this approach could soon transform everything from nutrition to manufacturing—anywhere nature’s chemistry holds untapped solutions.

At Enveda, we’re focused on what comes next. With the power of advanced AI and the support of our partners at Microsoft, we’re scaling discovery in ways that weren’t possible before. Microsoft’s compute resources, tools, and commitment to our mission give us a significant competitive advantage. As both a shareholder and strategic partner, they’re helping us stay at the forefront of AI-driven breakthroughs.

A key lesson we’ve learned through this journey is simple: data matters. The quality, quantity, and structure of your data define the strength of your AI. Investing in cleaning, organizing, and connecting that data is what turns potential into real, usable insight.

The opportunity ahead is enormous. With the right data, technology, and people, we are building a future where understanding life’s chemistry leads directly to better health outcomes for everyone.