ins-$0.9M · 13F 21+/2-×0.0 · short↑0.39
Current snapshotRecursion Pharmaceuticals
AI Discover · Healthspan Infrastructure
AI Discover exposure in Healthspan Infrastructure.
AI Discover / Phenomics, merged Exscientia: Drug discovery's binding constraint is the *cost and failure-rate* of turning biology into a validated lead (industry norm: ~4–5 years, thousands of compounds, ~90% Phase 2/3 attrition). Recursion's thesis is that a proprietary data + compute + automated-lab flywheel compresses that cycle — it does NOT own a physical toll-road like a foundry or a qualified part; it owns an *unproven-but-accumulating* data asset that is expensive and slow to replicate.
Catalysts
Recursion Pharmaceuticals Q2 2026 earnings; AI drug discovery pipeline milestone (clinical program advancement); partnership (Roche/Sanofi) progression; Phenomap platform updates
Invalidation
Thesis weakens if insider selling (Form 144/4s 08-07 to 08-21) becomes systematic, revenue -60% YoY stays lumpy/declining, -98% GM and $2.324B cumulative deficit persist, or $300M ATM dilution (19% of mkt cap) overhangs. (vault 2026-08)
Latest change
· Target moved from $7.00 to $7.62.
Mapped funds and investors
Direct relationships supported by published evidence.
Reported holdings as-of
| Fund / investor | As of | Fund portfolio weight | Evidence |
|---|---|---|---|
| ARK Genomic Revolution ETF ARKG | 2.82% | Source | |
| ARK Innovation ETF ARKK | 1.46% | Source |
Disclosed investment history
No sourced relationships mapped yet.
Showing up to four relationships in each group. ETF weights describe the fund’s portfolio, not ownership of this company. Private investment history does not establish current ownership.
Bullish — Bullish on AI genomics breakout with 373-379% upside to wedge top and 50WMA flip; noted in $RXRX +10% surge and genomics value capture list with $TEM/$ILMN peers (Aug 22-25 2026 posts). [X search Aug 2026]
Lower-confidence snapshotTarget price: $7.62
Dated research targetMoat & position
- Evidence Grade
- Inferred
- Moat Durability
- Durable IP
- Toll Road Tier
- Weak proxy
Deep research update
3,256 words · Updated 19 Oct 2026 · 9 sources
Recursion Pharmaceuticals is an AI-native ("TechBio") drug-discovery platform, not a single-drug biotech. It combines a proprietary phenomics data flywheel (petabytes of high-content imaging from millions of automated wet-lab experiments), the BioHive-2 NVIDIA-GPU supercomputer, and AI foundation models (Phenom, in NVIDIA's BioNeMo ecosystem) to industrialize target discovery, hit-to-lead, and lead optimization. The 2024 acquisition of Exscientia added generative chemistry + automated synthesis. Lead program REC-4881 is a repurposed MEK1/2 inhibitor for familial adenomatous polyposis (FAP); REC-1245 (RBM39 degrader) and REC-7735 (mutant-selective PI3Kα) are platform-origin oncology assets.
- monetization model: Collaboration/license revenue from pharma partners — upfronts, research funding, milestones, royalties; no product sales. (10-K Item 1; Note 3. sec.gov ; acc. 0001601830-24-000014)
- revenue mix: FY2023 total revenue ~$44.6M; 100% collaboration. Bayer ~50%, Roche/Genentech ~43%, Takeda ~7%; no product revenue. (10-K Item 1; Note 3. same URL; acc. 0001601830-24-000014)
- who pays: Pharma/biotech R&D partners: Bayer, Roche/Genentech, Takeda. (10-K Item 1; Note 3. same URL; acc. 0001601830-24-000014)
- margin_value_capture: No product gross margin; operating losses (FY2023 net loss ~$328M on ~$44.6M revenue). Value accrues via partner milestones/royalties if pipeline succeeds. (10-K Item 7/8. same URL; acc. 0001601830-24-000014)
- customer classes: Pharma & Biotech
Recursion does not report multiple reportable segments in the way a typical software or product company does. The revenue model is contract- and milestone-based, not unit-based product sales.
- Product revenue: Recursion has no approved drug product and therefore reports no product sales revenue. The 10-K for fiscal 2023 describes the company as a clinical-stage biopharmaceutical company that has not generated revenue from product sales and does not expect to do so for the foreseeable future.
Source: Recursion Pharmaceuticals, Inc. 10-K FY2023 — EDGAR issuer page: sec.gov ; accessed 2026-04-26; qualitative claim from filing; exact accession/exhibit not verified in this session.
- Collaboration and service revenue: This is effectively 100% of reported revenue. Collaborations with Roche/Genentech and Bayer are the named material agreements.
Source: Recursion Pharmaceuticals, Inc. 10-K FY2023 — business/risk disclosures; EDGAR URL above; exact accession/exhibit not verified in this session.
- Segment mix: Because the company is effectively a single-segment, clinical-stage company with collaboration revenue, a revenue-mix table like “software vs. services vs. product” does not apply. The valid statement is: 100% of current reported revenue is collaboration/service revenue, no product revenue.
Recursion monetizes its platform in three ways, in order of current importance:
- Upfront and milestone payments from strategic collaborators. Pharmaceutical companies pay Recursion to apply its platform to targets or disease areas. Payments can include upfront fees, research funding, milestone payments tied to pipeline progress, and royalties on any resulting products.
- Potential internal pipeline value. Recursion retains some internal programs and could eventually monetize them through out-licensing, partnerships, or commercialization.
- Data/technology licensing? Recursion does not operate a broad enterprise SaaS licensing model. If anything, it enters into bespoke collaborations. This is a key difference from Schrödinger’s software-like revenue.
Traditional gross margin is not meaningful here because there is no cost of goods sold for a drug product. Recursion has large R&D and G&A expenses that dwarf collaboration revenue.
- FY2023 total revenue: $44.6 million [NPSV]
This figure is from my prior knowledge of Recursion’s FY2023 disclosures and is not independently verified in this session. Primary source should be Recursion 10-K FY2023, EDGAR CIK 0001601830; exact accession/exhibit not verified.
- FY2023 net loss: $328.1 million [NPSV]
Primary source should be Recursion 10-K FY2023; exact accession/exhibit not verified.
- Q1 2024 revenue: $13.5 million [NPSV]
Primary source should be Recursion 10-Q Q1 2024; exact accession/exhibit not verified.
- Q1 2024 net loss: $91.8 million [NPSV]
Primary source should be Recursion 10-Q Q1 2024; exact accession/exhibit not verified.
- Operating margin: negative; the operating loss is substantially larger than revenue. If the above figures are correct, FY2023 net loss is roughly 7.4× revenue, meaning operating leverage is not present. This is a clinical-stage, cash-burning platform company.
Only pharmaceutical collaborators and, to a lesser extent, public research grantors pay Recursion today. The two named large pharma partners from SEC filings are:
- Genentech, a member of the Roche Group — entered a collaboration with Recursion to deploy the Recursion OS across neurology and oncology indications. The agreement was announced in December 2021. Recursion reported receiving $150 million upfront [NPSV] and was eligible for significant milestone payments.
Source: Recursion 8-K/company disclosure; EDGAR 8-K search: sec.gov ; accessed 2026-04-26; exact accession/exhibit not verified in this session.
- Bayer AG — entered an earlier platform collaboration; the deal was smaller than the Genentech/Roche deal and is described in Recursion’s 10-K.
Source: Recursion 10-K FY2023, business and collaboration agreement section; EDGAR URL above; exact accession/exhibit not verified in this session.
Do not infer additional customers from news or marketing pages. From the issuer’s own filings, the only large, named strategic collaborators I can cite are Genentech/Roche and Bayer. Recursion may have other research collaborations, but the material, SEC-disclosed partners are those two.
The customer base is pharmaceutical and biotechnology companies that need drug discovery capacity or target validation. Recursion is also indirectly selling to its own future pipeline via internal programs.
- Large pharma strategic partner: Roche/Genentech — has paid upfront and will pay milestones if programs progress.
- Large pharma partner: Bayer — earlier collaboration, also milestone-based.
- Internal discovery organization: Recursion itself is a “buyer” of its own platform for internal pipeline programs.
Do not infer other named customers. The SEC filings name the material partners; everything else is not source-bound.
Q2 2026 (ended 06-30, 10-Q filed 08-05) revenue $7.7M (−60% YoY from $19.2M — lumpy collaboration milestones, Roche/Genentech-driven). R&D $89.6M (down from $128.6M YoY); net loss $131.0M (improved ~24% YoY). Cash + restricted cash $556.8M; runway guided into early 2028. FY26 cash opex guidance lowered to <$375M (from <$390M). Market cap ~$1.58B at $3.50/share; 534.12M shares; accumulated deficit −$2.324B. Gross margin −98% (lab/compute costs expensed against thin milestone revenue). [10-Q CIK 0001601830]
- Discovery-cycle compression = the value claim. REC-1245 (RBM39 degrader): biological discovery → development candidate in ~18 months (vs ~4–5-yr industry norm). REC-7735 (PI3Kα H1047R): delivered in ~10 months using only 242 compounds (vs industry norm of thousands, years). Compressing ~3 years of discovery saves ~3 yrs of fully-loaded medicinal-chemistry R&D (≈$25–50M/yr/program → $75–150M/program), but — the honest counterweight — speed does NOT by itself raise Phase 3 success rates, which is where the real value lives.
- Cost of the moat vs moat it defends. Cumulative accumulated deficit $2.324B (the capital shareholders funded to build the flywheel) vs ~$400M external validation to date (Roche-Genentech ~$213–216M, Sanofi ~$134M, NVIDIA $50M) → the flywheel has consumed ~5.8× what external partners have paid in. The moat is real but expensive; partners have validated it but not yet funded it.
- R&D intensity / flywheel cost. Q2 R&D $89.6M vs revenue $7.7M = 11.6× R&D/revenue; annualized R&D ~$358M vs FY25 revenue ~$66M = ~5.4×. This is a platform investment posture, not a profitable business.
- Runway + dilution cost-of-moat. $556.8M cash ÷ ~$94M/qtr guided cash opex = ~6 quarters (early 2028, matching guidance). $300M ATM facility ÷ $1.58B market cap = ~19% potential dilution at current prices.
| Parameter | Value | Source | Confidence |
|---|---|---|---|
| Q2 2026 revenue | $7.7M (−60% YoY) | 10-Q 08-05 | measured |
| Q2 2026 R&D | $89.6M | 10-Q | measured |
| Q2 2026 net loss | $131.0M | 10-Q | measured |
| Cash + restricted cash | $556.8M | 10-Q | measured |
| Shares outstanding | 534.12M | 10-Q | measured |
| Accumulated deficit | −$2.324B | 10-Q | measured |
| Market cap | ~$1.58B ($3.50/sh) | picks_log | measured |
| FY26 cash opex guidance | <$375M | EX-99.1 | measured |
| Roche-Genentech milestones to date | ~$213–216M | company IR | measured |
| Sanofi payments to date | ~$134M | company IR | measured |
| REC-4881 Phase 2 response | 75% of patients (median ~43% polyp reduction) | company IR | measured |
| REC-1245 discovery→candidate | ~18 months | company IR | measured |
| REC-7735 hit→lead | ~10 months / 242 compounds | company IR | measured |
| NVIDIA investment | $50M (2023) | SEC/IR | measured |
\[
\$44.6\text{M} / 2 = \$22.3\text{M}
\]
Below are the key parameters for modeling RXRX. Every exact figure marked [NPSV] must be checked against the filing. None are confirmed in this session.
| Parameter | Value | Source | Tier | Measured/Derived/Assumed | Cross-verified? |
|---|---|---|---|---|---|
| FY2023 total revenue | $44.6M [NPSV] | Recursion 10-K FY2023, EDGAR CIK 0001601830; accession not verified | Tier 1 (unverified in session) | Measured in issuer filing, recalled | No |
| FY2023 net loss | $328.1M [NPSV] | Recursion 10-K FY2023, EDGAR CIK 0001601830; accession not verified | Tier 1 (unverified in session) | Measured in issuer filing, recalled | No |
| Q1 2024 revenue | $13.5M [NPSV] | Recursion 10-Q Q1 2024, EDGAR CIK 0001601830; accession not verified | Tier 1 (unverified in session) | Measured in issuer filing, recalled | No |
| Q1 2024 net loss | $91.8M [NPSV] | Recursion 10-Q Q1 2024, EDGAR CIK 0001601830; accession not verified | Tier 1 (unverified in session) | Measured in issuer filing, recalled | No |
| Cash and cash equivalents at Dec 31, 2023 | $391.6M [NPSV] | Recursion 10-K FY2023, EDGAR CIK 0001601830; accession not verified | Tier 1 (unverified in session) | Measured in issuer filing, recalled | No |
| Roche/Genentech upfront payment | $150M [NPSV] | Recursion 8-K / company disclosure; EDGAR CIK 0001601830; accession not verified | Tier 1 if 8-K; Tier 2 if only press release | Measured in issuer disclosure, recalled | No |
| Number of material named partners | 2 (Genentech/Roche, Bayer) | Recursion 10-K business section | Tier 1 (unverified in session) | Derived from filing | No — single-source |
| Schrödinger software revenue gross margin | not verified; expected positive | Schrödinger 10-K FY2023, EDGAR CIK 0001490978; accession not verified | Tier 1 (unverified in session) | Derived from competitor filing | No — single-source |
| Recursion operating margin | negative, loss >> revenue | Recursion 10-K FY2023 | Tier 1 (qualitative) | Derived | No — single-source |
Drug discovery's binding constraint is the cost and failure-rate of turning biology into a validated lead (industry norm: ~4–5 years, thousands of compounds, ~90% Phase 2/3 attrition). Recursion's thesis is that a proprietary data + compute + automated-lab flywheel compresses that cycle — it does NOT own a physical toll-road like a foundry or a qualified part; it owns an unproven-but-accumulating data asset that is expensive and slow to replicate.
- Proprietary phenomics data — >46M cellular images, whole-genome CRISPR knockout in >1 trillion iPSC-derived neurons; years of automated-lab output (Recursion IR / Q2 2026 earnings EX-99.1). This is the scarce asset: you cannot buy 8+ years of accumulated proprietary biological data.
- BioHive-2 supercomputer (NVIDIA GPUs) + Phenom foundation models, integrated into NVIDIA BioNeMo. NVIDIA invested $50M (2023) and is a strategic compute partner — credibility signal, not a moat (GPUs are commoditized).
- Integrated discovery engine (post-Exscientia): phenomics + generative chemistry + automated synthesis + "agentic AI" (Drug Design Agent, Clinical Strategy Orchestration Agent claimed 1.3–1.6× enrollment vs benchmark).
- Patent/IP — portfolio across the platform and programs, but the differentiated moat is the data flywheel, not a single blocking patent.
- Bypass (1/3): Pharma can trivially bypass — Insilico Medicine, Isomorphic Labs (Google DeepMind), Schrödinger, Xaira, and every major pharma's internal AI. No customer must buy from Recursion.
- Concentration (1/3): Recursion does not concentrate a critical input; its data/models are proprietary but not yet indispensable to any buyer.
- Hyperscaler exposure (2/3): NVIDIA is a partner/supplier (not a threat today), but Google (AlphaFold/Isomorphic) and NVIDIA (BioNeMo) are direct entrants into AI biology.
- Composite = 4/9 → WEAK PROXY. Not a bottleneck; a platform with an optional, not yet-toll-commanding, position.
- product_service: Recursion OS — integrated drug discovery platform plus internal pipeline. (10-K Item 1. sec.gov ; acc. 0001601830-24-000014)
- technical function: Automated wet-lab phenomics + ML/computer vision maps biological/chemical relationships to nominate drug candidates. (10-K Item 1. same URL; acc. 0001601830-24-000014)
- why it is hard: Proprietary large-scale biological image/chemical data and integrated iterative wet-lab/compute loop; costly to replicate. (10-K Item 1; Item 1A. same URL; acc. 0001601830-24-000014)
- substitutes: Traditional pharma R&D, CROs, academic screening centers, other AI/ML drug discovery platforms. (10-K Item 1A. same URL; acc. 0001601830-24-000014)
- pricing power: UNPROVEN — no product sales; revenue concentrated in few large partners; collaboration economics negotiated. (10-K Item 1; Item 1A; Note 3. same URL; acc. 0001601830-24-000014)
Recursion sells access to its Recursion Operating System (Recursion OS) through collaborations, plus the optionality of its internal clinical pipeline.
The actual “product” has four components:
- Wet-lab automation and high-content screening. Recursion uses automated microscopes, liquid handlers, and cell-culture systems to run large-scale phenotypic experiments. It can generate imaging, transcriptomic, proteomic, and other data at scale.
- Proprietary biological datasets. Over years, Recursion claims to have built a large, proprietary dataset of biological images and associated measurements. The exact size is often described in 10-K language as “uniquely large” or “proprietary,” but any precise number should be taken from the 10-K and is [NPSV] unless verified.
- Machine-learning models. The company trains models to infer relationships between chemical perturbations, disease-relevant phenotypes, and targets. It then uses these models to prioritize compounds or predict toxicity/efficacy.
- A clinical pipeline. Recursion advances internal programs, including candidates like REC-994 for cerebral cavernous malformation, REC-2282 for NF2-mutant meningiomas, and REC-4881 for familial adenomatous polyposis, among others. These are development-stage assets, not marketed products.
The core loop is:
- Design and run high-throughput wet-lab experiments.
- Extract features from images and multi-omics data.
- Build or refine ML models of biology.
- Generate a prediction or target hypothesis.
- Test the prediction experimentally.
- Feed the result back into the model.
This iterative loop is the core technical distinction that Recursion describes in its SEC filings. It is harder to replicate than a pure software model because it requires both laboratory automation and proprietary data, not just computational tools.
Substitutes for Recursion’s platform from the perspective of a pharma partner include:
- Traditional CROs and screening vendors for hit discovery.
- In-house pharma AI/data science units.
- Other AI-native drug discovery companies such as Schrödinger, Exscientia, Absci, and Relay Therapeutics.
- Academic collaborations or public consortia.
The substitute is not a direct replacement for Recursion’s exact data asset, but pharma partners can choose other ways to spend the same collaboration budget.
The hard-to-replicate elements are:
- Proprietary, iterative dataset. Recursion has spent years generating data from its own wet-lab system. The data asset is not publicly available and cannot be easily reverse-engineered.
- Wet-lab + dry-lab integration. Many AI drug discovery companies are more computational. Recursion owns and operates automated laboratory capacity, which creates an operational moat.
- Regulatory/technical validation. Clinical-stage assets and partner-funded programs create some validation, though not yet proof of commercial success.
That said, the moat is not proven. It depends on the platform generating clinical-stage or patentable output that a partner could not easily obtain elsewhere. If the ML models do not materially improve hit-to-lead success or clinical probability of success, the moat is weak.
Recursion does not have traditional pricing power because it has not yet demonstrated a commercial product. Its collaboration terms are negotiated one deal at a time. It cannot raise prices on an existing installed base like a SaaS company can.
Pricing power would emerge only if:
- Recursion has validated clinical-stage assets that a partner wants to license;
- Recursion’s platform generates candidates with clearly better success rates;
- The cost and time of replicating Recursion’s data asset are high.
Today, a pharma partner could likely walk away to Schrödinger, Exscientia, or an internal group. Therefore, Recursion’s pricing power is currently limited and unproven.
- Heavy insider selling post-earnings — multiple Form 144 + Form 4 filings 08-07 through 08-21, with the stock near $3.50 lows. If this is discretionary (not 10b5-1/tax), it contradicts the "platform inflection" narrative — monitor whether it becomes systematic.
- Revenue −60% YoY: collaboration revenue is timing-lumpy and declining, not yet a durable base.
- −98% gross margin and −$2.324B cumulative deficit: a capital-intensive platform, not a self-funding moat.
- $300M ATM facility = ongoing dilution overhang (19% of market cap).
- The core bear thesis is unanswered: AI has demonstrably accelerated discovery speed, but has NOT yet shown it raises clinical success rates. If the Nov 2026 REC-4881 readout or REC-7735/REC-1245 Phase 1 fail to differentiate, the "platform re-rating" thesis deflates to a cash-burning biotech.
- Competitive crowding: Isomorphic Labs, Insilico, Xaira, and every major pharma's in-house AI all chase the same "AI + biology" claim.
Hypothesis verdict: INTACT — the AI-native discovery platform thesis is structurally intact and externally validated (NVIDIA + Roche/Genentech + Sanofi), and the discovery-compression claim is quantitatively real (18-mo / 10-mo / 242-compound data points). But it remains a WEAK PROXY (4/9) toll-road with −98% GM and an unproven value proposition: this is an enabling-layer option on AI biology, not yet a bottleneck that commands tolls. The position should stay research_only WATCH; the re-rating trigger is evidence (not speed) of higher clinical success rates.
- Insider-sale cluster persists post-note: Form 4s continue 09-02 and 09-10 after the 08-07→08-21 cluster the 08-23 note flagged. 10b5-1-planned vs discretionary remains unresolved from filings alone — the recurring near-$3.50-low selling is the single most important monitorable against the "platform inflection" narrative.
- Revenue −60% YoY and −98% GM unchanged; the platform remains a capital-consuming option, not a self-funding moat.
- The core bear thesis is still unanswered: AI has compressed discovery speed (18-mo / 10-mo / 242-compound) but has not yet shown it raises clinical success rates. REC-4881 (Nov 2026), REC-7735 (Phase 1/2 2H26), REC-1245 (Phase 1) are the readouts that will answer it.
The thesis on RXRX is likely something like: “Recursion’s proprietary data + automation platform can generate higher-probability drug candidates and attract milestone-heavy partnerships, creating option value and eventually pipeline value.”
The thesis would be disproven or materially weakened by:
- Collaboration attrition. If Roche/Genentech or Bayer terminates or does not renew, revenue concentration becomes existential. This is directly checkable in future 8-Ks and 10-Qs.
- Clinical failure of internal pipeline assets. If candidates like REC-994, REC-2282, or REC-4881 fail in clinical trials, the internal pipeline option value falls.
- No new pharma partners. If Recursion cannot sign new large collaborations despite growing data, its platform value claim is undermined.
- Competitor filings showing better efficiency. If Schrödinger, Exscientia, or Absci reports faster hit identification, lower cost per lead, or stronger partner economics, Recursion’s moat is less convincing.
- Persistent cash burn without business-model conversion. If collaboration revenue remains under $100M while annual net losses remain above $300M, the company will require repeated dilutive financing, hurting per-share value.
- Platform does not improve hit-to-lead success. If Recursion’s internally disclosed R&D productivity metrics, if any, do not improve over time, the ML/data moat is not working.
- SEC filing restatement or revenue recognition change. If revenue from upfront payments is recognized more slowly or deferred revenue grows without cash conversion, the reported revenue quality would be weak.
Sources
9 sources preserved from the latest qualified research update.