Advanced AI And ML Will Transform Biotech Drug Discovery

Key Takeaways

• Advanced AI-driven platforms and large proprietary datasets are enhancing R&D efficiency, competitive positioning, and attractiveness for pharmaceutical partnerships.
  
• Strategic focus on internal pipeline progression and industry digitization trends positions the company for sustainable revenue growth and long-term commercial upside.
  
• Heavy dependence on pharma partners, early-stage pipeline risk, cash constraints, AI competition, and regulatory scrutiny all threaten long-term revenue stability and profitability.

Catalysts

Operates as a clinical-stage biotechnology company, engages in the decoding biology and chemistry by integrating technological innovations across biology, chemistry, automation, data science, and engineering to industrialize drug discovery in the United States.

• Rapid integration and iterative improvement of the Recursion OS 2.0 platform, incorporating advanced AI and ML tools (such as Boltz-2 and causal AI for clinical trial design), are expected to drive faster, more cost-effective drug discovery and development-improving R&D efficiency and supporting long-term margin expansion.
  
• Increasing digitization and utilization of large, proprietary, multimodal biological and patient datasets (e.g., phenomaps, multi-omic data) enables Recursion to strengthen its competitive position and become more attractive to big pharma partners, supporting potential growth in collaboration revenue and gross profit.
  
• Acceleration of internal drug candidates-especially in oncology and rare diseases-toward key clinical inflection points (e.g., late-stage trial data in FAP, CDK7, RBM39) creates opportunities for value realization through milestone payments, licensing revenue, and-eventually-commercial product sales, directly impacting topline growth.
  
• Major demographic shifts and aging populations are increasing demand for innovative therapies targeting chronic and rare diseases, expanding Recursion's addressable market and enhancing the long-term commercial upside of its internal drug pipeline, supporting sustainable revenue growth.
  
• Automated, data-driven approaches to drug discovery and clinical development are addressing industry-wide needs to decrease development timelines and costs, positioning Recursion to capitalize on the pharma industry's widespread shift toward AI-based R&D-potentially leading to greater market share and improved long-term earnings power.

Recursion Pharmaceuticals Future Earnings and Revenue Growth

Assumptions

• Analysts are assuming Recursion Pharmaceuticals's revenue will grow by 49.5% annually over the next 3 years.
• Analysts are not forecasting that Recursion Pharmaceuticals will become profitable in next 3 years. To represent the Analyst Price Target as a Future PE Valuation we will estimate Recursion Pharmaceuticals's profit margin will increase from -1004.9% to the average US Biotechs industry of 14.1% in 3 years.
• If Recursion Pharmaceuticals's profit margin were to converge on the industry average, you could expect earnings to reach $30.5 million (and earnings per share of $0.06) by about August 2028, up from $-649.1 million today.
• In order for the above numbers to justify the analysts price target, the company would need to trade at a PE ratio of 138.2x on those 2028 earnings, up from -3.6x today. This future PE is greater than the current PE for the US Biotechs industry at 16.9x.
• Analysts expect the number of shares outstanding to grow by 7.0% per year for the next 3 years.
• To value all of this in today's terms, we will use a discount rate of 6.78%, as per the Simply Wall St company report.

Recursion Pharmaceuticals Future Earnings Per Share Growth

Risks

• Persistent reliance on milestone and collaboration payments from large pharma partners (Sanofi, Roche, Bayer, Merck KgAa) creates revenue concentration and partnership risk; if these collaborations underdeliver or end, reported revenue and the company's long-term sustainability could be adversely affected.
  
• Although management highlights significant R&D pipeline momentum, most internal programs (including CDK7 and RBM39) remain in early or mid-stage clinical development, creating substantial risk of delays, clinical failures, or indefinite timelines before realizing meaningful revenue or earnings.
  
• Despite recent efforts to reduce projected cash burn, Recursion remains a cash-burning company with a runway only through Q4 2027, making it vulnerable to tighter capital markets, rising interest rates, or a biotech funding contraction that could lead to unfavorable dilution or compromised R&D progress-impacting both net margins and earnings.
  
• The rapid open-sourcing and commoditization of key AI technologies (e.g., Boltz-2) may erode Recursion's technological edge over time, particularly as competition from both traditional pharma adopting AI and well-funded AI-native biotechs intensifies, pressuring long-term gross margins and market share.
  
• Growing industry and regulatory scrutiny of AI-based healthcare, combined with evolving healthcare pricing pressures, may increase compliance costs and constrain the commercial upside of Recursion's pipeline-potentially limiting top-line growth and compressing future profitability.

Valuation

• The analysts have a consensus price target of $6.5 for Recursion Pharmaceuticals based on their expectations of its future earnings growth, profit margins and other risk factors. However, there is a degree of disagreement amongst analysts, with the most bullish reporting a price target of $10.0, and the most bearish reporting a price target of just $3.0.
  
• In order for you to agree with the analyst's consensus, you'd need to believe that by 2028, revenues will be $215.7 million, earnings will come to $30.5 million, and it would be trading on a PE ratio of 138.2x, assuming you use a discount rate of 6.8%.
  
• Given the current share price of $5.41, the analyst price target of $6.5 is 16.8% higher.
  
• We always encourage you to reach your own conclusions though. So sense check these analyst numbers against your own assumptions and expectations based on your understanding of the business and what you believe is probable.