AI Tool Comparison
Comparing as AI Medical Research & Clinical Decision SupportRecursion Pharmaceuticals vs Atomwise
Recursion Pharmaceuticals
VS
Atomwise
Verdict by Category
Detailed category analysis is not available for this comparison.
Detailed Comparison
Feature
Recursion Pharmaceuticals
Atomwise
Pricing
CustomRecursion operates through three revenue streams: pharma collaboration agreements, data licensing, and its own internal drug pipeline.
Pharma partnerships (Roche/Genentech, Sanofi) are structured as multi-year agreements with upfront payments and milestone-based payments tied to program progress. Recursion has earned $500M+ in cumulative milestones to date, with $134M from Sanofi alone.
Data licensing allows external researchers and pharma companies to access Recursion's proprietary biology maps and phenomics datasets for their own target discovery programs.
Recursion's own clinical programs (REC-4881, REC-1245, REC-4539) will generate revenue through future partnering, co-development, or commercialization deals as they advance through clinical trials. Total 2025 revenue: $74.7M. Contact Recursion through recursion.com for partnership inquiries.
CustomAtomwise operates through enterprise partnership and co-development agreements — there is no self-serve access or published pricing.
Collaboration types include: sponsored research agreements (pharma/biotech pays Atomwise to run AI-powered hit discovery campaigns), co-development partnerships (shared IP and milestone/royalty structures), and academic program access for universities through the ATOM initiative.
New CEO Steve Worland is also steering Atomwise toward an internal proprietary drug pipeline, which will generate revenue through future licensing and partnering deals as candidates mature into preclinical and clinical stages.
Contact Atomwise through atomwise.com for partnership and collaboration inquiries.
Categories
AI Healthcare ToolsAI Research & Education Tools
AI Healthcare ToolsAI Research & Education Tools
Summary
AI-native drug discovery OS with industrial-scale automated labs and $500M+ in pharma partnerships
Deep learning for structure-based drug discovery — AtomNet screens 16B+ compounds to find hits for any disease target
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
Atomwise Pros & Cons
Pros
- Invented deep learning for structure-based drug discovery in 2012 — true pioneer in the field
- AtomNet screens 16B+ compounds in under 2 days — fastest virtual screening at this scale
- 775+ collaborations and 250+ partners — most validated partnership network in AI drug discovery
- Tackles undruggable targets that traditional methods can't address
- Strong academic program: 40+ universities including Harvard, Stanford, and Duke
- New Foundation Model announced 2026 — next-generation AI for molecular discovery
- $226M+ raised from DCVC, Khosla, Y Combinator, Tencent, B Capital, and Baidu
Cons
- Early-stage company — no FDA-approved drugs from the platform yet
- Shifting focus from platform licensing to proprietary pipeline adds execution risk
- Smaller team (~100-250 employees) compared to larger AI drug discovery peers
- Revenue still modest at $5-25M range — pre-commercial stage
- Deep tech focus means long timelines before patient impact is realized