Schrödinger is not a biotech company. It is not a SaaS company. It is both — and that hybrid identity is precisely what the market fails to value correctly.
Founded in 1990, Schrödinger built a physics-based computational platform that simulates molecular behavior using quantum mechanics. Where most AI drug discovery companies train models on historical data and predict outcomes statistically, Schrödinger calculates from first principles — the actual physics of how atoms interact, how proteins fold, how small molecules bind to targets. Their core technology, FEP+ (Free Energy Perturbation), computes binding free energies with unprecedented accuracy, allowing chemists to design optimized drug candidates in silico before synthesizing a single molecule.
Think of it this way: most AI drug companies are pattern matchers. Schrödinger is a physics simulator. Pattern matching breaks on novel targets where there's no historical data. Physics doesn't — because physics is physics. This is the moat.
1. Physics + AI Hybrid. Pure AI companies (Recursion, Insilico, Isomorphic Labs) train models on data and predict outcomes. Schrödinger calculates outcomes from quantum mechanical first principles, then enhances with ML. When AlphaFold predicts a protein structure, FEP+ simulates how millions of candidates interact with it at atomic resolution. Physics provides the accuracy floor; AI accelerates the search. No other company has 30+ years of validated physics code layered with modern ML.
2. All Top-20 Pharma Are Customers. Not prospects. Customers. Novartis, Lilly, Pfizer, Roche, Merck, J&J, AstraZeneca, GSK, Sanofi, BMS — every single one. This creates an information flywheel: as more companies use the platform, Schrödinger gains insight into which approaches work, improving the platform, attracting more usage.
3. Dual Revenue Model = De-Risked Biotech. Traditional biotechs burn cash praying for clinical success. Schrödinger generates $160-170M in recurring software revenue while also running a drug pipeline. If every clinical program fails tomorrow, the software business alone justifies $1.3-2.0B at peer multiples. The pipeline is free optionality on top of a real business.
4. Materials Science Expands TAM Beyond Pharma. Neptune ammonia catalyst — 2x yield improvement, 47% capacity increase, 23% energy reduction — proved the physics engine works on industrial chemistry. Catalysts, polymers, battery materials, semiconductors — the TAM expansion from pharma ($70B+) to materials ($200B+) is completely unmodeled by analysts covering SDGR as "healthcare technology."
5. The Jensen Huang Signal. NVIDIA's CEO hosted Schrödinger's CEO at his home and told him to "think bigger." There was "shouting." This isn't casual — it's strategic alignment between the GPU maker and the software that consumes them. Every advance in NVIDIA compute makes Schrödinger's simulations faster. SDGR is a direct beneficiary of Phase 1 infrastructure investment.
$150M upfront + $2.3B in milestone payments + royalties + expanded software license.
Multi-target research collaboration to discover and develop novel therapeutic candidates. Novartis gains industry-leading access to Schrödinger's platform. Schrödinger receives milestone cascade that could generate revenue for a decade. This single deal validates computational drug discovery at the highest level of pharma.
Lilly's TuneLab AI platform integrated into LiveDesign. Participating biotechs access TuneLab through Schrödinger's interface — making LiveDesign the de facto OS for AI-assisted drug design. Prior Lilly relationship yielded $47.6M (Morphic acquisition).
Jensen Huang's $1B AI pharma lab. FEP+ is a primary GPU workload in life sciences. BioNeMo integration. More powerful GPUs = more simulations = Phase 1 → Phase 3 feedback loop.
Co-founded by Schrödinger. Series C complete. AJ1-11095 in Phase 1. Demonstrates the venture-creation model: design molecules, spin out companies, retain equity upside.
Lead asset. 22% ORR across 45 patients. Well-tolerated — no DLTs, no treatment-related deaths. FDA Fast Track + Orphan Drug Designation for Waldenström. Dose escalation complete; recommended P2 dose to be discussed with FDA. Seeking licensing partner for mid/late-stage development — becomes milestone + royalty asset.
Key upcoming catalyst. Initial clinical data expected H1 2026 — within our window. Differentiated mechanism in solid tumors. Preclinical data strong at EORTC-NCI-AACR. This readout is the most important binary event for SDGR in 2026.
Potent against resistant EGFR variants. Strong wild-type selectivity. Robust anti-tumor activity in brain metastases models (ESMO). Addresses massive unmet need — osimertinib resistance in ~40% of NSCLC patients.
Newly selected. NLRP3 inflammasome validated neuroinflammation target. Potential licensing candidate for pharma partners.
Discontinued Aug 2025 after emergent events linked to two patient deaths. Pipeline narrowed to two clinical assets but accelerated pivot to discovery-focused licensing model. The $70M in annual savings improves runway by ~2 years.
| Annual Revenue (FY24) | $207.5M |
| Q3 2025 Revenue | $54.3M (+54% YoY) |
| Software Revenue (Q3) | $40.9M (+28% YoY) |
| Drug Discovery Rev (Q3) | $13.4M |
| Gross Margin | 58.2% |
| Software Gross Margin | 73–75% |
| FY25 Software Guide | +8–13% growth |
| FY25 Discovery Guide | $49–52M |
| Cash + ST Investments | $352–391M |
| FCF (TTM) | -$31.9M |
| Net Margin | -68.5% |
| EPS (TTM) | -$2.39 |
| Cost Savings (Pivot) | ~$70M annual |
| Est. Post-Pivot Burn | ~$80–100M/yr |
| Est. Cash Runway | Through 2027–28 |
| Dilution Risk | Low |
At $870M market cap with $352-391M cash, EV is ~$479-518M. Software revenue at ~$165M growing 28% with 73-75% gross margins would trade at 8-12x for any pure SaaS company — implying $1.3-2.0B for software alone. The market is assigning approximately negative $800M to $1.5B of value to the Novartis $2.3B milestone cascade, the entire clinical pipeline, materials science applications, 30 years of physics IP, and the Lilly/NVIDIA partnerships. That's the dislocation.
= (72×.30)+(78×.25)+(68×.20)+(65×.15)+(68×.10) = 71.0
| Factor | Score | Rationale |
|---|---|---|
| Moat Durability | 72 | 30yr physics codebase. All top-20 pharma customers. FEP+ unmatched by pure-ML. But Isomorphic Labs (Google) and internal pharma AI teams investing heavily. Moat widening from physics side, testable from ML side. |
| Catalyst Runway | 78 | 5 catalysts in window: Q4 ER Feb 25, SGR-3515 Ph1 data H1, SGR-1505 licensing partner, Novartis milestones, Neptune pilot. Majority new-information events. Densest calendar in Phase 3 space. |
| Supply/Demand | 68 | Pharma AI adoption accelerating. Patent cliff driving large pharma to computational approaches. GPU cost decreases expand simulation capacity. But software guide lowered 2pts — demand strong, not explosive. |
| Edge Decay | 65 | At 52w low — generalists have abandoned. Hybrid model confuses both software and biotech analysts. Most institutions have sold. Edge intact because nobody is looking. |
| Regime Alignment | 68 | Biotech outperformance trend (Morgan Stanley). Rate cut tailwinds. Patent cliff driving pharma M&A + licensing. Some FDA uncertainty under Trump creates headwind. |
Probability: 25%
Probability: 40%
Probability: 25%
Probability: 10%
E[V] = (0.25 × $25) + (0.40 × $18) + (0.25 × $9.50) + (0.10 × $6) = $16.43 → +39% expected upside
65% probability of positive outcome. Bull upside (+86-137%) significantly exceeds Bear downside (-7-32%). Cash floor ~$5/share bounds the crash scenario.
The Compute Curve: Every GPU NVIDIA ships feeds into Schrödinger's simulation capacity. FEP+ consumes thousands of GPU-hours per candidate. As compute cost falls ~40% per FLOP annually, molecular simulations per dollar double every 18 months. This doesn't make robots faster — it makes molecular discovery faster. Phase 1 infrastructure compounds directly into Phase 3 speed.
The Data Curve: Biological datasets for ML training double every 12-18 months. Schrödinger's top-20 pharma customers feed results back into model improvement. Each dataset improves the next model, which targets the next simulation, which generates better data. The flywheel accelerates.
The Integration Curve: Schrödinger's FEP+ engine + Lilly TuneLab + NVIDIA BioNeMo + Ginkgo/OpenAI autonomous labs + AlphaFold structures = an ecosystem where each platform amplifies the others. This interoperability creates the step function no linear extrapolation captures.
Implication: If AI compresses target identification from 4 years to 18 months and autonomous labs compress experiments from weeks to days, the market's discount rate on Phase 3 is systematically too high. Clinical events arrive sooner than modeled. Stocks re-rate when speed becomes undeniable — before drugs are approved.
| Entry Zone | $11.00 – $12.50 (current) |
| Target (6-mo) | $18 – $22 (+52–86%) |
| Target (12-mo) | $22 – $28 (+86–137%) |
| Stop Loss | $9.50 (-20%) |
| R:R Ratio | 2.6:1 to 4.3:1 |
| Position Size | 1 – 1.5% ($75 – $115K) |
| Conviction | MEDIUM Phase 3 Option Book |
Tranche 1 (Now): 0.5% position ahead of Feb 25 earnings. Downside bounded by cash floor. Upside from earnings beat could gap stock 15-25%.
Tranche 2 (Post-ER): If earnings confirm software growth + cash runway, add 0.5% to 1% total.
Tranche 3 (SGR-3515 Data): When H1 2026 clinical data releases — add 0.5% if positive (→ 1.5%). If negative, hold existing but tighten stop to $10.
| Date | Event | Impact | Type |
|---|---|---|---|
| Feb 25 ★ | Q4/FY25 Earnings | Software growth, cash update, FY26 guide, pipeline update | New Info |
| H1 2026 | SGR-3515 Phase 1 Data | Biggest binary catalyst. Wee1/Myt1 in solid tumors. Data = pipeline re-rate. | New Info |
| 2026 | SGR-1505 Licensing Partner | Upfront payment + milestone cascade. Validates discovery-to-license model. | New Info |
| Ongoing | Novartis Milestones | Revenue catalyst with zero R&D cost to Schrödinger | Confirm |
| 2026-27 | Neptune Catalyst Pilot | Validates materials science TAM expansion | New Info |
| Q2 2026 | ASCO / Medical Meeting | Potential venue for clinical data presentations | New Info |
The software platform — used by every major pharma company — generates real revenue growing 28% with 73% gross margins. Novartis validates the approach at the highest institutional level. The clinical pipeline retains two active programs with near-term catalysts. Materials science expands TAM beyond pharma. The strategic pivot transforms the cash equation from burning to survive to investing to compound.
At $11.81, the market prices Schrödinger as if computational drug discovery has failed. The evidence says it's just beginning to work. The acceleration thesis — compute, data, and integration curves all steepening simultaneously — means Phase 3 validation events arrive sooner than consensus models. Position accordingly: 1-1.5% in tranches, stop at $9.50, let the catalysts work.