4 Best Small-Cap AI Drug Discovery Stocks — May 2026

AI drug discovery splits into three monetization models: software-to-pharma (SDGR), platform-to-partner (ABCL, ABSI), and own-pipeline (RXRX). Each has different unit economics and different bull-case shapes.

AI drug discovery as a public-equity category had its rerating in 2023-2024 — the small-cap names that survived the drawdown now trade at multiples a fraction of their post-IPO levels. The investable thesis splits into three different business models that get bundled together by AI-generated lists, and the bull-case shape for each is meaningfully different.

We scored every small-cap public AI-drug-discovery name. Here are the 5 that scored highest, with explicit framing of their monetization model. Two are platform-to-partner (sell discovery services to big pharma), one is software-to-pharma (sell tools), one is own-pipeline (develop drugs directly), and one is small enough that the model is still in flux.


Why Small-Cap AI Drug Discovery Is Different

  • Three different monetization models — software-to-pharma (SDGR), platform-to-partner (ABCL, ABSI), own-pipeline (RXRX). Each has different ARR-vs-milestone economics and different valuation anchors.
  • 'AI' label has been universally adopted — every drug-discovery company is now AI-something. The differentiator is whether the AI is the core IP (RXRX, ABSI) or a workflow accelerant (SDGR, ABCL).
  • Cash and partnership economics matter more than 'pipeline' — most names will not see commercial revenue from owned programs for 5-7 years. Survivability through trial outcomes is what to underwrite.
  • Big pharma is the customer base for two of three models — concentrated relationships with Eli Lilly, GSK, Sanofi etc. drive economics. One major partner exit can compress the valuation sharply.

Our scoring rewards balance-sheet survivability and capital-efficiency. For pre-commercial biotechs with platform revenue, the relevant metrics are runway-to-Phase-2-readouts, partner revenue diversification, and dilution discipline.


Top 4 Small-Cap AI Drug Discovery Stocks by Fundamental Score — May 2026

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1. Schrodinger, Inc. (SDGR) — Score: 62.4 | Grade: SOLID

MetricValueScore
Revenue Growth YoY+23.3%37
Gross Margin55.7%79
Cash Runway>36 months100
Debt/Equity30.0075
P/S Ratio3.7x83
Rule of 40-41.90
Insider Ownership2.9%23
12m Dilution-11.8%100

What drives the score: Schrödinger is the longest-running physics-based molecular-simulation software vendor for drug discovery (Glide, FEP+, Maestro). Software segment sold to most large pharmas and is gross-margin positive; internal drug-development pipeline drives the corporate-level losses.

Key risk: Software business is genuinely good but small relative to the corporate-level losses driven by internal drug-development programs. Strategic question is whether the drug pipeline produces value or distracts capital from the higher-margin software franchise. Software-segment growth deceleration would re-rate the multiple sharply.

Market cap: $939M. Industry: Health Information Services.


2. AbCellera Biologics Inc. (ABCL) — Score: 60.5 | Grade: SOLID

MetricValueScore
Revenue Growth YoY+160.6%100
Gross Margin38.4%53
Cash Runway12 months39
Debt/Equity14.8188
P/S Ratio14.7x29
Rule of 40-109.90
Insider Ownership22.8%89
12m Dilution+2.5%85

What drives the score: AbCellera Biologics runs an antibody-discovery platform that licenses to big pharma (Eli Lilly, GSK, etc.) for milestone and royalty revenue. Profitable through 2023 on lump-sum licensing; now investing in wholly-owned program development, which is the strategic pivot question.

Key risk: Platform-to-partner model produces lumpy milestone-and-royalty revenue. Pivoting from licensing to wholly-owned development is the strategic shift; the question is whether discovery-licensing royalties continue to flow at scale even as wholly-owned programs expand. Dilution funding the wholly-owned shift is the watch item.

Market cap: $1.10B. Industry: Biotechnology.


3. Recursion Pharmaceuticals, Inc. (RXRX) — Score: 38.9 | Grade: HIGH RISK

MetricValueScore
Revenue Growth YoY+27.0%43
Gross Margin4.4%6
Cash Runway24 months85
Debt/Equity6.8994
P/S Ratio24.6x5
Rule of 40-845.90
Insider Ownership2.9%23
12m Dilution+28.4%2

What drives the score: Recursion Pharmaceuticals does AI-first drug discovery via image-based phenotypic screening on a robotic-cell-imaging platform. Merged with Exscientia (UK) in 2024. Multiple partner-funded and wholly-owned programs in early-stage trials; SBC-heavy and persistently lossy.

Key risk: Post-Exscientia merger integration is still ongoing; geographic and cultural integration of UK/US sites adds operational risk. Multiple shots-on-goal across wholly-owned programs is the bull case but each readout is a binary; runway must outlast multiple Phase-2 timelines.

Market cap: $1.84B. Industry: Biotechnology.


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4. Absci Corporation (ABSI) — Score: 19.6 | Grade: CRITICAL

MetricValueScore
Revenue Growth YoY-20.7%0
Gross MarginN/A0
Cash Runway7 months14
Debt/Equity5.6495
P/S Ratio130.9x0
Rule of 40-2422.30
Insider Ownership13.5%72
12m Dilution+30.3%0

What drives the score: Absci uses generative AI to design antibody candidates de novo, then validates in wet lab. Smaller and more focused than Recursion; revenue model is partner deals (ASP, Twist) and milestones. Pre-commercial at scale, dilution-funded.

Key risk: Smallest of the platform-to-partner names. Concentrated partnership economics; one partner non-renewal would meaningfully impact revenue. Generative-AI antibody design is unproven at clinical-readout scale — pre-clinical activity is plentiful, but Phase 2/3 success rates with AI-designed candidates haven't been demonstrated.

Market cap: $368M. Industry: Biotechnology.


What these 4 stocks have in common

  1. Three different monetization models, three different bull cases. SDGR is a software bet, ABCL/ABSI are partnership bets, RXRX is a pipeline bet, AVTE is now a strategic-cash bet. Investors should match the model to their portfolio thesis.

  2. Score variance reflects monetization stability, not platform quality. SDGR scores highest because the software franchise produces real revenue. RXRX scores in the middle because the platform produces partnership revenue but corporate losses. ABSI scores low because the dilution rate has been high.

  3. Big pharma exposure is concentrated. ABCL has Eli Lilly. ABSI has multiple smaller-pharma partners. Concentration risk is real for the platform-to-partner names.


What's not on this list — and why

  • Recursion is on this list — but its $1.8B market cap puts it at the upper edge of small-cap. Investors should re-check market cap before sizing positions; mid-cap-comparable beta should be assumed.
  • Schrödinger is similarly at the upper edge ($939M as of latest update); bigger than peer ABSI by 2-3x.
  • Insilico Medicine — private; one of the most-cited AI-drug names not available to public investors.
  • Exscientia (EXAI) — merged into Recursion in late 2024; no longer trades as a separate ticker.
  • BenevolentAI (BAI.L) — UK-listed, not in our US-tracked universe but the equivalent European peer.

AI drug discovery as a category is more crowded with private names than with public small-caps. The 5 names on our list represent most of the public small-cap exposure available; outside of these, investors looking for 'AI drug discovery' allocations are typically looking at broader biotech ETF exposure or private-market funds.


How to use this data

These scores measure financial health, not pipeline quality or AI-platform credibility. For each name:

  • For SDGR, software-segment growth (separate from corporate losses) is the metric to track quarterly
  • For ABCL, monitor wholly-owned program disclosures vs. partnership-revenue trajectory; the strategic pivot is the variable
  • For RXRX, watch Exscientia-integration milestones and cash runway through the next two Phase-2 readouts
  • For ABSI, partner-deal renewals and dilution-rate trajectory are the leading indicators
  • For AVTE, this is a strategic-cash story — track the strategic-review outcome

SmallCapScanner scores are calculated algorithmically based on 8 fundamental factors. They measure financial health, not future performance. See /how-it-works for the full methodology.

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