AI Tool Comparison
Comparing as AI Medical Research & Clinical Decision SupportSchrödinger vs Recursion Pharmaceuticals
VS

Schrödinger
Enterprise

Recursion Pharmaceuticals
Enterprise
Verdict by Category
Detailed category analysis is not available for this comparison.
Feature & Spec Matrix
Detailed Comparison25 Criteria
Complete side-by-side breakdown of specifications, capabilities, and feature parity
Swipe horizontally to compare features
Feature / Spec
Pricing Model
EnterprisePhysics-based molecular modeling & drug discovery suite — Academic site licenses & commercial enterprise quotes on sales consultation
EnterpriseAI-enabled drug discovery and mapping (Recursion OS) — Custom biopharma enterprise partnership agreements only
Starting Price
Custom / Contact Sales
Custom / Contact Sales
Free Plan & Trial Scope
Difference
Academic licensing available at reduced rates; commercial pricing via sales team
No self-serve access — enterprise pharma collaborations and data licensing via partnership team
User Rating Score
Unrated
Unrated
Ideal Workflow / Use Case
Difference
Pharmaceutical scientists and computational chemists needing physics-based molecular simulation for drug discovery, lead optimization, and ADMET prediction
Major pharma companies and researchers needing AI-powered biology mapping, target discovery, and drug candidate generation at industrial scale through the Recursion OS platform
Enterprise & Scalability
Difference
NASDAQ listed (SDGR), enterprise software licensing with volume pricing, cloud-hosted subscriptions, strategic research collaborations with BMS, Sanofi, and Takeda, dedicated scientific support teams, and academic/government licensing programs
NASDAQ listed (RXRX), $500M+ in pharma partnership milestones earned, enterprise collaboration agreements with Roche/Genentech and Sanofi, automated biology and chemistry labs at industrial scale in Salt Lake City and Oxford, and data licensing for external researchers
Core Categories
AI Healthcare ToolsAI Research & Education Tools
AI Healthcare ToolsAI Research & Education Tools
Physics-based molecular simulation: Maestro, Glide, Jaguar, Prime, and FEP+ for drug and materials discovery
Supported
Supported
Bunsen AI co-scientist (July 2026) for hypothesis generation, experiment design, and molecular insight
Difference
Schrödinger Advantage
Not listed
FEP+ for industry-leading binding affinity prediction in lead optimization
Difference
Schrödinger Advantage
Not listed
Structure-based drug design, ADMET prediction, and quantum chemistry in one platform
Difference
Schrödinger Advantage
Not listed
Cloud-hosted software subscriptions with 10-15% ACV growth target for 2026
Difference
Schrödinger Advantage
Not listed
Drug discovery pipeline with BMS, Sanofi, and Takeda — FY26 guidance raised to $65-75M
Difference
Schrödinger Advantage
Not listed
Materials science applications: battery design, semiconductors, and specialty chemicals
Difference
Schrödinger Advantage
Not listed
$255.87M revenue in 2025 with 23% growth — NASDAQ listed (SDGR)
Supported
Supported
500+ enterprise customers including top 20 global pharma companies
Difference
Schrödinger Advantage
Not listed
Founded 1990 by Professor Richard Friesner — 34+ years of computational chemistry leadership
Difference
Schrödinger Advantage
Not listed
Industrial-scale automated labs in Salt Lake City and Oxford generating proprietary multimodal data
Difference
Not listed
Recursion Pharmaceuticals Advantage
REC-4881 for FAP — 53% polyp reduction in Phase 2, FDA registration discussions begun 2026
Difference
Not listed
Recursion Pharmaceuticals Advantage
REC-1245 (RBM39 degrader) in Phase 1/2 DAHLIA study for solid tumors
Difference
Not listed
Recursion Pharmaceuticals Advantage
REC-4539 (LSD1 inhibitor) — first patient dosed in Phase 1 ENLYGHT study 2026
Difference
Not listed
Recursion Pharmaceuticals Advantage
Sanofi partnership — $134M earned to date across 5 milestones
Difference
Not listed
Recursion Pharmaceuticals Advantage
Roche/Genentech Phenomaps — 1 trillion neuronal cells for neuroscience target discovery
Difference
Not listed
Recursion Pharmaceuticals Advantage
$500M+ in cumulative pharma partnership milestones earned to date
Difference
Not listed
Recursion Pharmaceuticals Advantage
Recursion Data — phenomics and biology maps licensed to external researchers and pharma
Difference
Not listed
Recursion Pharmaceuticals Advantage
Schrödinger Pros & Cons
Pros
- 34+ years of computational chemistry leadership — most trusted physics-based platform in pharma
- Bunsen AI co-scientist launched July 2026 — BMS immediately deployed it
- FEP+ delivers industry-leading accuracy in binding affinity prediction
- NASDAQ SDGR — $255.87M revenue in 2025, 23% growth, turning profitable in Q2 2026
- 500+ pharma enterprise customers including BMS, Sanofi, Takeda, Pfizer, and Eli Lilly
- Materials science applications extend reach to battery, semiconductor, and chemical sectors
- Cloud-hosted subscriptions eliminate on-premise infrastructure burden
Cons
- Software is expensive — enterprise pricing puts it out of reach for smaller labs
- Stock (SDGR) has been under pressure — market cap ~$1B despite strong platform
- Drug discovery segment revenue is milestone-dependent and lumpy
- Platform learning curve is steep without computational chemistry background
- Competition from newer, purely AI-native platforms is intensifying
Recursion Pharmaceuticals Pros & Cons
Pros
- $500M+ in pharma partnership milestones — most validated AI drug platform by commercial revenue
- Recursion OS is the most vertically integrated AI drug discovery system — biology to clinic in one platform
- Industrial-scale automated labs generate data no other company can replicate
- Phase 2 FAP clinical proof of concept — 53% polyp reduction — FDA registration discussions began
- Roche/Genentech and Sanofi as partners — two of the world's top 5 pharma companies
- Exscientia acquisition in 2024 added cutting-edge small molecule AI design capabilities
- Cash runway guided into early 2028 — disciplined capital allocation
Cons
- Stock (RXRX) is below $5 — significant market skepticism on timeline to commercial drugs
- Operating cash burn of ~$390M in 2026 — needs continued capital or milestone payments
- Acquired Exscientia in 2024 — integration complexity and added operational overhead
- No approved drugs yet — clinical proof of concept still early stage
- Proprietary platform requires industrial-scale automation infrastructure that can't be self-built
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