AI drug discovery stocks in 2025 offer traders an edge if they understand how to manage risk in volatile sectors. These biotech and pharmaceutical companies use artificial intelligence and machine learning to accelerate drug development, creating opportunities for those who stay informed and disciplined. Below are five stocks worth watching, along with how to evaluate and trade this high-potential segment.
Check out my AI penny stocks watchlist for more picks!
Table of Contents
5 AI Drug Discovery Stocks and Companies to Watch
| Company Name | Ticker | AI Focus Area |
|---|---|---|
| Recursion Pharmaceuticals | NASDAQ: RXRX | AI + Biomolecular Modeling |
| Pfizer Inc | NYSE: PFE | Oncology AI & Data Platforms |
| Schrödinger Inc | NASDAQ: SDGR | AI-Designed Molecules |
| BioXcel Therapeutics | NASDAQ: BTAI | Neurology & Agitation AI |
| AbCellera Biologics | NASDAQ: ABCL | Antibody Discovery AI |
Before you send in your orders, take note: I have NO plans to trade these stocks unless they fit my preferred setups. This is only a watchlist.
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Recursion Pharmaceuticals Inc (NASDAQ: RXRX)
Recursion Pharmaceuticals uses artificial intelligence to map the relationships between biology and chemistry at scale. Its platform, powered by machine learning and high-throughput screening, runs on a supercomputer built with NVIDIA H100 GPUs. The Boltz-2 AI model, released with MIT, accelerates drug discovery 1,000 times compared to traditional methods.
Read more on RXRX: RXRX: Market Moves and Future Projections
RXRX stock remains volatile. In June 2025, the company laid off 20% of its workforce to reduce burn rate, and it still posted negative cash flow from operations at -$131.95 million. That hasn’t stopped speculation, especially after their recent clinical trial updates and institutional backing. Despite a gross margin of only 6.5%, the stock continues to trade at a high price-to-sales ratio of 36.72 due to hype around its AI technology.
Drug-discovery names don’t operate in isolation, they’re part of the broader AI biotech ecosystem. Recursion uses supercomputers and AI to map biology, yet its high price-to-sales ratio and recent workforce reductions highlight the balance between breakthrough potential and financial discipline. Gilead Sciences employs AI for HIV and cancer treatments, boasting 16 late-stage programs and a strong balance sheet. Comparing early-stage innovators to established biopharma helps set realistic expectations. To see how these categories fit together, visit our AI biotech stocks guide.
I’ve seen many traders rush into plays like this without a trading plan, only to get burned. RXRX is a high-risk ticker that demands tight execution, rule-based entries, and quick exits when trades go against you.
Pfizer Inc (NYSE: PFE)
Pfizer has quietly become one of the largest pharmaceutical companies applying AI across R&D, especially in oncology. Its post-COVID reset included a ramp-up of AI-driven initiatives and major acquisitions, such as Seagen, to boost its cancer treatment pipeline. With vast clinical trial data and machine learning investments, Pfizer is positioning AI to help identify better drug candidates faster.
In addition to its AI drug discovery prospects, Pfizer made my best overall healthcare stock watchlist!
PFE shares have been under pressure, but the 7% dividend and long-term data strategy have attracted patient capital. For traders, the appeal lies in potential catalysts—earnings surprises, FDA approvals, or new AI partnerships—that could cause sharp, tradeable moves. While less explosive than penny stocks, Pfizer offers setups with lower downside risk.
In my experience, slower-moving large caps like this are where beginner traders can learn timing and risk management without getting wiped out. It’s about pattern recognition and knowing when to size up or sit out.
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Schrödinger Inc. (NASDAQ: SDGR)
Schrödinger is a pioneer in using physics-based simulations and AI models to design better molecules. The company’s platform enables researchers to predict molecular behavior and improve drug discovery success rates. In June 2025, the FDA granted Fast Track designation to its MALT1 inhibitor, SGR-1505, which could become a key treatment for blood cancers like Waldenström macroglobulinemia.
Revenue from software licenses and collaborations is helping to support drug development programs. SDGR is not yet profitable, but its blend of AI and computational chemistry has drawn comparisons to early-stage biotech innovators that eventually scaled. The company’s partnerships across the pharmaceutical industry, including ongoing deals with Eli Lilly and others, show it’s being taken seriously by major players.
I always tell students: track the news flow, understand the catalysts, and respect the volatility. SDGR has shown patterns that lend themselves to breakout trades around clinical and partnership headlines.
BioXcel Therapeutics (NASDAQ: BTAI)
BioXcel Therapeutics is known for using AI to develop psychiatric and neurological therapies. Its flagship drug, IGALMI, is approved for acute agitation, and it’s currently in late-stage trials for at-home use and possible expansion into Alzheimer’s treatment. The company is racing the clock to hit key milestones before a Nasdaq delisting deadline in September 2025.
BTAI stock is extremely risky. It’s down over 95% from previous highs, trading around $1.70 with a market cap of just $10 million. There’s high upside if the company executes, but it faces serious challenges—low revenue, ongoing losses, and regulatory risk. Still, firms like Lucid Capital are calling for a rebound based on future potential.
This is the kind of setup where I tell traders: don’t guess. Let the stock prove itself. Wait for volume spikes, clear breakouts, or news events, and be ready to cut losses quickly if it fades.
AbCellera Biologics (NASDAQ: ABCL)
AbCellera uses artificial intelligence to speed up antibody discovery by analyzing massive data sets of immune responses. With over $600 million in cash and no debt, the company has a strong cash runway and says it’s on track to hit cashflow breakeven. However, revenue fell 35% year-over-year, and R&D expenses remain high as it pushes toward commercialization.
Its AI platform has attracted top-tier partnerships with pharmaceutical companies like Eli Lilly and Novo Nordisk. The company’s long-term opportunity is in reducing the time and cost of discovering therapeutic antibodies across oncology, infectious disease, and autoimmune disorders.
I teach my students to focus on stocks with catalysts and liquidity. ABCL is one to watch if news hits on new licensing deals or trial progress. The chart has shown periods of strength when volume confirms the story, and that’s when the best trades happen.
The Role of AI in Revolutionizing Drug Discovery
AI is changing how biotech and pharmaceutical companies approach drug development by shortening timelines and lowering costs. Instead of manually testing thousands of compounds, machine learning models can now analyze chemical structures, predict protein binding, and run simulations in minutes. This is especially powerful in early-stage research where failure rates are high and delays are expensive.
In drug discovery, AI platforms use data analytics and automation to speed up hit identification, optimize lead compounds, and improve clinical trial design. Tools like Boltz-2 and Schrödinger’s simulation engine reduce the need for physical testing while maintaining high predictive accuracy. These platforms rely heavily on capital investment, R&D spend, and partnerships with pharma giants to scale.
Over the past 20+ years of teaching and trading, I’ve seen technology shifts like this create short-term hype. But for traders, it’s about spotting which companies are executing, not just talking about AI. Action always beats theory in this market.
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What I’ve learned over 20+ years of trading is that sectors like this will keep producing short-term spikes. But only those who stay informed, focused, and patient can capitalize. You don’t need to trade every name—just wait for the right setup and know the story behind the move.
How to Evaluate AI Drug Discovery Stocks: Key Metrics
Evaluating AI drug discovery stocks starts with understanding how different financial and operational factors impact both short-term trading potential and long-term survival. These companies often rely on venture capital to support high R&D costs, especially when revenue is minimal or non-existent. For traders, it’s critical to track metrics that reveal whether a stock has real growth potential or if it’s just another overhyped play fueled by speculation.
I always teach that traders should look for signs of progress beyond price action—like increases in market share, new healthcare applications, or updates to product pipelines backed by meaningful data. Whether a stock is included in niche biotech ETFs or sees buying interest from institutional investors can influence short-term volume and volatility, especially when companies announce AI collaborations with players like NVDA.
When I review stocks, I focus on how performance lines up with expectations and what catalysts are next on the calendar. That’s where the trades are—not in guessing, but in reacting to real developments with discipline and speed.
Financial Indicators
Evaluating AI drug discovery stocks starts with the basics—look at revenue, cash flow, and capital reserves. Companies like RXRX and ABCL operate at a loss but still attract attention due to their AI infrastructure and runway. Traders should watch price-to-sales ratios, cash burn rates, and debt levels to spot signs of sustainability or distress.
Profitability remains elusive for most AI-first biotech companies, so valuation often reflects future potential rather than current earnings. That’s where risk comes in. A company with a $10 million market cap and no revenue needs major execution just to survive. But if it lands a partnership or gets FDA attention, the stock can spike fast.
I’ve taught thousands of traders how to manage plays like this: size small, stay alert, and always check liquidity before entering a trade.
AI biotech penny stocks have a different set of challenges from bigger players like Tempus AI. Tempus isn’t a traditional drug developer, yet its clinical-data platform could transform how therapies are discovered and prescribed. The company’s real-time recommendations, a $200 million data-licensing deal and revenue growth of 75 % in Q1 2025 point to substantial momentum. Its forward price-to-sales multiple is rich, so watch valuations and wait for consolidation before entering. For a complete breakdown, refer to our Tempus AI stock analysis.
For both smaller-cap stocks and large-cap AI biotech stocks, my basic advice remains the same…
Pipeline Strength
A biotech’s pipeline is its heartbeat. AI drug discovery companies with multiple assets in clinical trials offer more upside and lower risk than single-drug ventures. Look for breadth—different stages (preclinical, Phase 1, Phase 2) and different indications across oncology, neurology, and infectious diseases.
For instance, Schrödinger’s SGR-1505 and BioXcel’s IGALMI expansion show that AI pipelines can mature into real products. Fast Track or orphan drug designations from the FDA are signals that the pipeline is gaining traction. Watch for updates and know what the next data readout means for the stock.
As a trader, I don’t need the science to be perfect. I just need the timing and volume to line up with a real catalyst.
Partnerships and Collaborations
Strong partnerships can legitimize a speculative company. When firms like Eli Lilly or NVIDIA work with smaller biotech companies, it gives traders a reason to pay attention. These collaborations often include funding, licensing deals, or shared development rights—each of which can move the stock.
AbCellera’s antibody discovery deals and Recursion’s MIT collaboration on Boltz-2 are examples of strategic moves that show the company’s tech is being validated. These partnerships are often announced via press releases or earnings calls, making them prime catalysts for short-term trading setups.
Over the years, I’ve seen how market sentiment shifts quickly on news like this. Traders who are prepared with alerts and watchlists can act while others are still processing headlines.
How to Trade AI Drug Discovery Stocks
Trading AI drug discovery stocks requires a strict plan. These are often low-float, news-sensitive stocks that can spike or crash 30% or more in a day. Use level 2 data, premarket scans, and volume alerts to identify where the momentum is building. Focus on catalysts like earnings, trial results, and new partnerships.
Start with small size and scale only when the stock confirms your setup. Avoid holding through uncertain events unless you’re prepared for both outcomes. If a stock fails to hold key support after news, get out. Cutting losses quickly is non-negotiable in this space.
Many AI drug-discovery companies are tiny with limited liquidity. SoundHound AI and Innodata prove how momentum and speculative narratives can drive massive, short-lived moves. Similar volatility exists in pre-clinical biotech; stocks can quadruple on a press release and then retrace once enthusiasm fades. If you’re intrigued by obscure AI names but wary of being left holding the bag, my coverage of under-the-radar AI plays will help you sort opportunity from hype.
I built my 7-step framework around lessons learned from trading thousands of volatile plays. Discipline is your edge. Stick to your rules, not your hopes.
MEMORIZE THIS CHART…ITS A BIG PART OF WHY MY 7-STEP https://t.co/46W8tDBAGj FRAMEWORK WORKS SO WELL! https://t.co/FgAdUFBLAF
— Timothy Sykes (@timothysykes) February 28, 2024
Key Takeaways
- AI is reshaping drug discovery, offering speed and efficiency that’s never been possible before.
- Stocks like RXRX, SDGR, and ABCL are speculative but can offer strong short-term trading opportunities around key news.
- Use fundamentals like cash runway and pipeline depth to evaluate risk.
- Partnerships with major pharma companies often trigger volume and price spikes.
- Follow a proven trading framework. Manage risk. Never trade based on hype alone.
This is a market tailor-made for traders who are prepared. AI drug discovery stocks thrive on volatility, but it’s up to you to capitalize on it. Stick to your plan, manage your risk, and don’t let FOMO drive your decisions.
These opportunities are fast and unpredictable, but with the right strategy, you can make them work for you.
If you want to know what I’m looking for—check out my free webinar here!
Frequently Asked Questions
How is AI used in drug development?
AI is used to model biological interactions, analyze compounds, and predict outcomes in drug discovery. This helps researchers identify viable drug candidates faster and at a lower cost than traditional R&D methods.
How accurate is AI in identifying new drug candidates?
AI models like Boltz-2 can achieve prediction speeds 1,000 times faster than traditional physics-based methods with similar accuracy. However, lab validation and clinical trials are still required before FDA approval.
Are AI drug discovery companies profitable?
Most AI-driven drug discovery companies are not yet profitable. They typically rely on venture capital, partnerships, or secondary offerings to fund ongoing R&D and operations. Traders should watch for burn rate and upcoming catalysts.
What kind of returns can traders expect from AI drug discovery stocks?
Returns from AI drug discovery stocks can be highly variable due to the early-stage nature of many companies and the speculative environment of the biotech sector. Stocks tied to emerging technologies like artificial intelligence, especially those partnered with platforms like NVDA or backed by venture capital, often see sharp price swings around news events. While strong performance is possible, traders must weigh the growth potential against volatility and avoid mistaking short-term spikes for sustainable trends.
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