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    Earnings call· Jun 2026(Q2 FY26)

    RECURSION PHARMACEUTICALS Q2 FY26 earnings call RXRX

    Aug 5, 2026 Source

    Executive summary

    Recursion Pharmaceuticals, Inc. Q2 FY26 — AI-Native Engine Drives Pipeline Progress and OpEx Efficiency

    Recursion Pharmaceuticals reported a strong quarter, highlighting the maturation of its AI-native product engine into a system capable of generating differentiated programs and medicines. The company demonstrated significant progress across its internal clinical pipeline and external partnerships, notably advancing a novel neuroscience target with Roche-Genentech. Management also emphasized substantial operational efficiencies, leading to a significant reduction in full-year operating expense guidance, while maintaining a focus on high-value asset development.

    Highlights

    5

    • Advanced to 5 clinical stage programs, including REC-4881 with promising Phase II data in FAP, a disease with a nearly $10 billion TAM.

    • Achieved over $500 million in realized inflows from partnerships, including a significant milestone with Roche-Genentech for a novel neuroscience target.

    • Reduced 2026 full-year cash operating expense guidance to $375 million, representing a nearly 40% reduction from comparable 2024 pro forma expenses.

    • Received IND clearance for REC-7735, positioning it to enter Phase I later this year, expanding the clinical oncology pipeline.

    • Demonstrated significant efficiency gains in drug discovery, advancing candidates in ~1.5 years using ~330 compounds compared to industry benchmarks of 4 years and 2,500 compounds.

    Guidance & targets

    2
    CategoryTargetConfidence
    Full-year cash operating expense
    $375M
    high materiality
    High
    Operating runway
    Through early 2028
    medium materiality
    High

    Operational metrics

    10
    Cash and equivalents balance
    $557M
    Q2 FY26

    Balance at the end of the quarter, providing an operating runway through early 2028.

    Partnership realized inflows
    $500M
    to date

    Achieved through collaborations with leading biopharma partners, including more than a dozen successful discovery milestones.

    Compound synthesis efficiency
    330 compoundsvs. industry benchmark of 2,500 compounds
    per candidate

    Advancing candidates using significantly fewer compounds and in a shorter timeframe compared to industry benchmarks for small molecules, demonstrating improved speed and capital efficiency.

    Clinical trial enrollment improvement
    1.3 to 1.6-foldvs. historical benchmarks
    current

    Improvements in enrollment speed and patient matching achieved through AI-driven trial design and Agentic workflows.

    Chemistry design cycle compression
    30 minutesvs. ~4 hours
    per structural analysis

    AI agents help scientists prioritize design hypotheses, reducing the time for structural analysis and compressing design cycles.

    G&A as percentage of total cost
    relatively low
    current

    Maintained at a relatively low percentage to maximize the scientific ROI of every dollar spent.

    REC-7735 selectivity
    100-fold
    preclinical

    Precision designed to be highly selective for the H1047R mutation, aiming for an improved safety profile regarding hyperglycemia and expanded patient populations.

    Proprietary multimodal biological data
    50 petabytes
    to date

    One of the largest proprietary datasets in the industry, designed to train models and discover novel biology.

    iPSC-derived neuronal cells generated
    1 trillion neurons and hundreds of billions of microglia
    to date

    Generated at an unprecedented scale to create a rich disease-relevant Atlas for neuroscience target discovery.

    Experiments per week
    2 million
    weekly

    The rate at which experiments are conducted in Recursion's labs, contributing to the growing data moat.

    Industry KPIs

    3
    MetricValueDetails
    Peak long term sales guidance$10BUSD
    Clinical trial efficacy safety data43%%
    Collaboration milestone royalty revenue$260MUSD

    Deals & partnerships

    2
    SanofiCollaboration on developing novel lead series for challenging first-in-class oncology targets and oral I&I development candidates.

    Partnership focuses on designing differentiated small molecules against challenging targets with potential to impact multiple immune-mediated diseases.

    Roche-GenentechCollaboration to discover novel neuroscience targets using Recursion's AI-driven map of biology.$260M

    Genentech advanced the collaboration's first neuroscience target into a joint early discovery program, validating Recursion's platform in discovering new biology.

    What to watch in Q3 FY26

    5

    REC-4881 additional Phase II data

    November
    CurrentPromising initial Phase II data (43% median polyp burden reduction)
    TargetPresentation of updated data at CGA-IGC Conference

    Why it matters

    Provides further clinical evidence and contextualization for REC-4881, which is in a disease with no approved therapies and a large addressable market.

    We are pleased to share that additional REC-4881 data will be presented during the Presidential Plenary session at the CGA-IGC Conference in November.

    Q&A highlights

    5

    How does the Roche-Genentech collaboration serve as a transferable template for leveraging Recursion's platform with other partners, highlighting 2-3 key aspects?

    Najat Khan explained that the core Lab-in-the-Loop process, from novel data sets to compound design and clinical validation, is scalable for all partners. Key differentiators include the proprietary data factory (50 petabytes, 1 trillion iPSC-derived neuronal cells), the integrated Lab-in-the-Loop for experimental validation, and the ability to produce differentiated assets. She emphasized the difficulty of replicating the data generation and validation expertise built over years.

    “Big picture, the way we develop our novel data sets for creating novel maps, and then we take those novel targets and design compounds all the way into the clinic, that sort of Lab-in-the-Loop is something we use for both our internal programs and for our partner programs.”

    asked by Alec from BofA, Sean from Morgan Stanley · answered by Najat Khan

    2 min read5 chapters

    Detailed Narrative

    01

    AI-Native Product Engine and Differentiation

    Recursion emphasized its AI-native product engine as a continuous learning system, powered by proprietary multimodal data and Frontier AI models. The company highlighted three reinforcing capabilities: generating proprietary biological and molecular data at scale (50 petabytes), connecting models to experimentation through a Lab-in-the-Loop system, and converting these capabilities into differentiated assets. This approach is positioned as a key differentiator against other AI drug discovery companies, focusing on high-quality data and rigorous experimental validation.

    02

    Internal Pipeline Maturation and Key Programs

    The internal pipeline has matured to 5 clinical stage programs. REC-4881 for FAP showed promising Phase II data with a 43% median polyp burden reduction, and further data will be presented at the CGA-IGC Conference in November. REC-1245 is undergoing dose escalation in Phase I for solid tumors, with an update expected later this year. REC-7735, a precision-designed PI3-kinase inhibitor, received IND clearance and is set to initiate its Phase I ZINNIA trial later this year, with initial data expected in H1 2028.

    03

    Roche-Genentech Neuroscience Collaboration Breakthrough

    A significant milestone was announced with Roche-Genentech, advancing the collaboration's first neuroscience target into a joint early discovery program. This represents a proof point for Recursion's platform in discovering novel, biologically-validated targets in an area with high unmet need and historically slow progress. The collaboration has already generated over $260 million in upfront and milestone payments, with potential for over $300 million in additional milestones per future small molecule program.

    04

    Operational Efficiencies and Financial Discipline

    Recursion demonstrated increased return on investment through multiple levers, including using its Cleantech platform for more efficient clinical trial enrollment and leveraging AI systems for internal discovery. The company reduced its 2026 full-year cash operating expense guidance to $375 million, a nearly 40% reduction from comparable 2024 pro forma expenses, while still advancing its pipeline and partnerships. G&A expenses are maintained at a low percentage of total cost, maximizing scientific ROI.

    05

    AI Strategy and Competitive Advantage

    The company addressed the rapidly evolving AI landscape, asserting its durable competitive advantage lies in its proprietary data factory (50 petabytes, 1 trillion iPSC-derived neuronal cells), its integrated Lab-in-the-Loop operating model, and the differentiated assets it produces. Recursion also highlighted its strategy of rapidly adopting the best AI advances, whether internal (e.g., Nesso-1 model) or open-source, and strengthening its leadership team with key hires in AI and drug design.

    AI-generated summary of the company’s earnings call. Not investment advice.