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Been watching the AI drug discovery companies space pretty closely lately, and there's something interesting happening that deserves attention.
The reality is that AI is fundamentally changing how new drugs get developed. We're talking about faster patient recruitment, smarter trial designs, better predictive models - basically compressing years off the traditional timeline. Three players really stand out right now: Schrödinger, Recursion Pharmaceuticals, and Exscientia. None of them are printing money yet, but they're all getting serious backing from major pharma, which tells you something.
Let me start with Schrödinger. The stock's been on a run - up over 80% last year if you were paying attention. What's interesting is they're playing both sides of the game. They've got a software platform that other biotech companies license to speed up their own drug searches, and then they're also running their own drug discovery operation using machine learning. They've actually been doing this machine learning thing for like two decades, so it's not just riding the AI hype wave. In Q2, they pulled in $35.2 million in revenue, down a bit year-over-year, but they actually posted a $4.3 million profit - which is notable given they had a $47.7 million loss in the same period the year before. The software side is carrying them right now at $29.4 million, while drug discovery brought in $5.8 million. Not huge numbers, but here's the thing - they're sitting on $554 million in cash. That's years of runway. And they've already gotten two drugs approved through FDA, including Tibsovo and Idhifa for blood cancers. Their partners read like a who's who: Bristol Myers Squibb, Eli Lilly, Takeda. Pretty solid validation.
Recursion Pharmaceuticals is a different story. Stock up 10% year-to-date, but this is more of a long-term play. They're betting that you can industrialize drug discovery with AI and data science. The company's running nine programs, three in phase 2, but here's the catch - they're all targeting rare diseases. Their biggest market opportunity is REC-3964 for a specific infection affecting around 730,000 people in the US, but that's only in phase 1. So we're probably looking at years before they see meaningful revenue from their own products. That said, they're already making money from partnerships - Nvidia dropped $50 million on them, and they've got deals with Roche and Bayer. In Q2, they reported $11 million in quarterly revenue and $405.9 million in cash, though they also had a $76.7 million net loss. The AI-powered platform is clearly resonating with bigger players even if the company itself isn't at profitability yet.
Exscientia is the most speculative of the three. Stock up 6% this year. They're focused on AI for cancer drugs specifically, and they just opened an automation lab in the UK to handle more of the experimental work. All five of their pipeline programs are early-stage - phase 1/2 or earlier. They've got two blood cancer therapies in preclinical testing and partnerships with Evotec, Bristol Myers Squibb, and some Chinese biotech firms. The financials are tighter here - Q2 revenue was $3.8 million (down 58% year-over-year) and they posted a $42 million loss. But they've got $508.6 million in cash, so they're not going anywhere soon. The risk is higher with so many early-stage candidates, but the cash position and focus on oncology gives them some cushion.
If I had to rank them by risk, Schrödinger looks like the safest bet. They've already proven they can get drugs to market and actually make money. The stock's had quite a run though, so maybe worth waiting for a pullback. Recursion is solid for patient long-term investors - good pipeline depth but years away from real revenue. Exscientia is the wildcard - highest risk but the oncology focus and cash runway could pay off if things break right.
The bigger picture? AI drug discovery companies are clearly reshaping pharmaceutical development. Whether you're betting on one of these three or just watching the sector evolve, it's worth paying attention to what's happening here.