7. Schrödinger Inc. (NASDAQ:SDGR)
Schrödinger, Inc. (NASDAQ: SDGR) reaches seventh place because it offers something many speculative AI medicine companies lack: an established software operation that already generates meaningful revenue.
The company combines physics-based molecular modeling with machine learning to help researchers predict how potential drugs may interact with biological targets. Pharmaceutical and biotechnology customers use the software to evaluate molecules before committing time and money to laboratory experiments. The company also applies the platform to its own drug-discovery pipeline.
This dual business model creates two possible sources of long-term value. Software subscriptions can produce recurring revenue, while successful proprietary medicines or collaborations could generate milestones and royalties. The software business also provides commercial evidence that outside researchers find the underlying technology useful.
Total revenue reached $255.9 million in 2025, increasing 23.3%. Software revenue advanced 10.6% to $199.5 million, while drug-discovery revenue more than doubled to $56.4 million. Software gross margin reached 74%, demonstrating the attractive economics of the established technology operation. Cash, restricted cash and marketable securities stood at $418.8 million after the second quarter of 2026. The latest cash position and financial outlook were reported in the company’s quarterly results.
At approximately $20.09 per share and a market capitalization of about $1.5 billion, the market is assigning a relatively modest value to the software platform, proprietary pipeline and cash reserves. Nevertheless, the company continues to report losses, and drug-discovery revenue can fluctuate depending on collaboration milestones.
The stock offers a more balanced approach to computational drug discovery than many clinical-stage competitors. Investors receive exposure to AI-assisted pharmaceutical research without depending entirely on a single experimental treatment, although clinical and execution risks remain high.
