Artificial intelligence is transforming nearly every industry, but few areas hold as much promise — and risk — as drug discovery. One company at the center of this revolution is Recursion Pharmaceuticals (NASDAQ: RXRX). While it’s still a small-cap biotech with a lot to prove, some investors argue RXRX could one day play a role in biology that mirrors what NVIDIA (NVDA) did for computing. But is that comparison justified, or just hype?
The Case for RXRX as the “NVIDIA of Biology”
1. A Data Moat the Size of Biology Itself
NVIDIA’s rise wasn’t just about chips — it was about dominating the GPU market that fueled AI training. Recursion’s edge is its massive proprietary dataset of cellular images. With over 23 petabytes of proprietary biological and chemical data and 3 trillion searchable relationships across biology and chemistry, RXRX has built what it calls the Recursion Operating System (Recursion OS).
This isn’t just raw data — it’s a structured foundation for AI models to learn the “language of biology.” In other words, RXRX’s dataset could be the training fuel for a new generation of biology-focused foundation models.
2. Infrastructure Over End Products
Like NVIDIA, which sells GPUs to power countless AI applications, RXRX isn’t just developing drugs — it’s building the infrastructure for AI-first biology. Its platform combines:
- Automated labs that generate biological data at scale.
- AI models that interpret cellular images.
- Partnerships with big pharma (Roche/Genentech, Bayer) to apply discoveries at scale.
If RXRX becomes the “default engine” for phenomics-driven drug discovery, it could carve out a role as the backbone of the industry — just as NVIDIA did with AI compute.
3. Big Pharma Partnerships Validate the Vision
NVIDIA became a trillion-dollar company by being indispensable to AI developers. RXRX is trying to follow that playbook in pharma. Deals with Roche/Genentech (up to $12 billion in milestones) and Bayer (targeting fibrotic diseases) demonstrate that established drugmakers see value in Recursion’s platform.
These partnerships don’t just bring in revenue; they also validate that RXRX has something unique — a platform big pharma can’t easily replicate in-house.
4. Optionality Beyond Drug Discovery
NVIDIA wasn’t always an AI darling; it started with gaming GPUs. Then deep learning unlocked a much bigger market. Similarly, RXRX may discover that its biological foundation models have applications beyond therapeutics:
- Biotech SaaS licensing — data + AI models sold to partners.
- Cross-industry applications in agriculture, chemicals, or materials science.
- Potential to build a “biological cloud” service similar to what AWS became for computing.
The Bear Case: Why RXRX Isn’t NVIDIA (Yet)
Of course, there are risks:
- Drug Discovery Is Harder Than Training AI Models — biology is messy, and RXRX’s outputs are drug candidates that must pass clinical trials with high failure rates.
- Cash Burn — Recursion is still unprofitable and relies on partnerships and fundraising. If capital markets tighten, survival becomes a challenge.
- Competition — other AI-biotech players like Exscientia (EXAI) and Schrödinger (SDGR) are chasing similar visions.
- Hype vs. Reality — NVIDIA’s dominance came after decades of execution. RXRX still needs a commercial success story to prove its system works end-to-end.
Investor Outlook: Moonshot or Mega-Cap in the Making?
Recursion’s current market cap (under $2B as of 2025) looks tiny compared to NVIDIA’s trillion-dollar valuation. That’s the point: RXRX is a moonshot stock. If its platform becomes the gold standard for AI-driven drug discovery, the upside could be extraordinary. If it fails, investors could be left with little.
For now, RXRX might best fit in a moonshot portfolio allocation — small position sizes, high risk, high reward.
Conclusion
Comparing RXRX to NVIDIA might sound outrageous today, but the parallels are intriguing. Both companies aim to provide the infrastructure layer that unlocks exponential innovation in their fields. NVIDIA succeeded because it was in the right place at the right time, with the right technology.
The big question for Recursion is whether its Recursion OS and biological data moat can do the same for the life sciences. If it can, RXRX could move from speculative biotech to indispensable AI platform.
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