Schrodinger, Inc. · NASDAQ:SDGR
Schrodinger — Investor Presentation (May 2025)
38 slides from Schrodinger's investor presentation, May 2025
Slide 1: Revolutionizing Medicines and Materials Discovery
Revolutionizing Medicines and Materials Discovery May 2025
Slide 2: Cautionary Note and Disclaimer
Cautionary Note and Disclaimer This presentation contains certain "forward-looking statements" within the meaning of the U.S. Private Securities Litigation Reform Act of 1995 that involve substantial risks and uncertainties. All statements, other than statements of historical fact, made by Schröding
Slide 3: Highlights
Highlights 1Q25 Financial Results Phase 1 Data Readouts on 2025 Guidance Highlights • $59.6M total revenue Track • 10% - 15% software growth • $48.8M software revenue • SGR-1505 June 2025 • $45M - $50M drug discovery • $10.7M drug discovery – EHA: June 12 - 15 revenue revenue – ICML: June 17 - 21 •
Slide 4: Pioneering Digital Chemistry
30+ years of innovation Pioneering ~900 employees worldwide; >40% Ph.D. Digital >50% of employees dedicated to R&D Chemistry ~1,752 customers, including top 20 innovative biopharma1 Pipeline of 25+ collaborative and proprietary programs 1 As measured by revenue. 4
Slide 5: Our Target-to-Clinic Digital Chemistry Laboratory
Our Target-to-Clinic Digital Chemistry Laboratory Target Hit Lead Preclinical Validation Identification Optimization Development Protein structure Large-scale virtual Compound Polymorph prediction determination screening enumeration Drug formulation Druggability Fragment screening In silico assays f
Slide 6: Multi-Pronged Business Enabled by Highly Differentiated Computational Platform
Multi-Pronged Business Enabled by Highly Differentiated Computational Platform SOFTWARE LICENSING • Life Sciences COLLABORATIONS • Materials Design • Drug Design PROPRIETARY PIPELINE ~1,752 customers worldwide1 • Materials Design 19 drug discovery collaborators2 • Drug Discovery & Development 8+ act
Slide 7: Our Computational Platform
Our Computational Platform 7
Slide 8: Designing Drugs Is a Highly Challenging Multi-Parameter Optimization Problem
Designing Drugs Is a Highly Challenging Multi-Parameter Optimization Problem Need to identify a molecule that balances many … anti-correlated properties: Potency ✓ ✕ ✓ ✕ ✓ ✓ 33% success Selectivity ✕ ✓ ✓ ✓ ✕ ✓ IND Solubility ✕ ✕ ✕ ✓ ✓ ✕ delivery Bioavailability ✕ ✕ ✕ ✕ ✕ ✕ 66% Clearance / Half-life
Slide 9: Schrödinger's Vision for the Future of Drug Discovery
Schrödinger’s Vision for the Future of Drug Discovery If all properties can be calculated with perfect accuracy, designing drugs would have a much higher success rate, be much faster and cheaper, and would produce much higher-quality molecules. Select THE best molecule “All” synthesizable molecules
Slide 10: Digital Chemistry Laboratory Leverages Physics + AI
Digital Chemistry Laboratory Leverages Physics + AI Physics + AI/ML Physics-based Training Set for AI/ML Artificial Intelligence / Methods Generated Using Physics Machine Learning ✓ No training set required ✓ Fast ✓ Effective at interpolation ✓ Can extrapolate into novel ✓ Accurate ✓ Fast chemical s
Slide 11: Physics-Enabled AI/ML Platform
Physics-Enabled AI/ML Platform PHYSICS + AI PHYSICS + AI PHYSICS MACHINE MAKE & ADVANCE PHYSICS generates generates determines LEARNING TEST BEST computes protein/ligand 1,000,000,000s properties of subset scores 10s of MOLECULE properties of top structures of molecules of molecules 1,000,000,000s m
Slide 12: Advancing the Platform in 2025
Advancing the Platform in 2025 Continuing to Integrate Physics & AI/ML Target Hit Lead Preclinical Validation Discovery Optimization Development High Resolution Protein Biologics Informatics Formulation & Crystal Structure Prediction Structure Prediction AI/ML Integration in Informatics Platform Vir
Slide 13: Schrödinger's Predictive Toxicology Initiative
Schrödinger’s Predictive Toxicology Initiative Cyp3A4 • Predictive Toxicology Initiative: Develop structure-based computational assays for off-targets hERG • Predictive computational advantages: – Early de-risking – Faster ligand evaluation Cyp2D6 – Greater throughput – Lower cost PXR – Improved saf
Slide 14: Our Therapeutics Pipeline
Our Therapeutics Pipeline 14
Slide 15: A Broad Portfolio of Advancing Collaboration Programs
A Broad Portfolio of Advancing Collaboration Programs(1)(2) Phase 1 Phase 2 Phase 3 FDA-Approved TIBSOVO4 Immuno-oncology Metabolic Diseases3 Psoriasis3 IDHIFA4 Myelofibrosis Inflammatory Bowel Disease5 Undisclosed Undisclosed Obesity Undisclosed Undisclosed Additional programs in discovery and prec
Slide 16: Proprietary Pipeline Approaching Key Clinical Milestones
Proprietary Pipeline Approaching Key Clinical Milestones DISCOVERY PRECLINICAL PHASE 1 SGR-1505 (MALT1) R/R B-cell Malignancies* SGR-2921 (CDC7) R/R AML/MDS* SGR-3515 (Wee1/Myt1) Solid Tumors SGR-4174 (SOS1) Solid Tumors EGFRC797S Solid Tumors NLRP3 Immunology LRRK2 Neurology Undisclosed Programs Mu
Slide 17: MALT1 Protease Inhibition Clinically Validated in 3rd Party Study
MALT1 Protease Inhibition Clinically Validated in 3rd Party Study Allosteric Inhibition of MALT1 Non-Hodgkin's Lymphoma (NHL) • Clinically validated by 3rd party MALT1 28% ORR* monotherapy1,3,4 inhibitor showed monotherapy and Chronic Lymphocytic Leukemia (CLL/SLL) combination activity in human B-ce
Slide 18: SGR-1505 Status and Next Steps
SGR-1505 Status and Next Steps • SGR-1505 was generally well tolerated with no dose-limiting Phase 1 healthy subject toxicities and no serious adverse events study completed • Favorable PK and evidence of target engagement Phase 1 study in • Primary objectives: Evaluate safety, PK, PD, RP2D* advance
Slide 19: CDC7 Is an S-phase Kinase That Regulates DNA Replication
CDC7 Is an S-phase Kinase That Regulates DNA Replication and the Replication Stress Response CDC7 • Maintains DNA replication fork progression, activates fork protection and restart mechanisms1,2 • Activates BRCA1-A and Cohesin complexes1 • Required for protection and restart of stalled replication
Slide 20: SGR-2921 Status and Next Steps
SGR-2921 Status and Next Steps • High replication stress in AML Strong preclinical • Potent and selective CDC7 inhibition shows strong rationale anti-proliferative activity in AML samples, including those resistant to standard-of-care therapies • Primary objectives: Evaluate safety, tolerability and
Slide 21: Wee1 Inhibition Clinically Validated in 3rd Party Studies
Wee1 Inhibition Clinically Validated in 3rd Party Studies Head and Neck Cancer Breast Cancer 50% ORR (chemo combination)7 SGR-3515 Combines 26% ORR (cisplatin combination)1 Schrödinger Wee1/Myt1 Wee1 Inhibitor SchrödingerActivity Wee1 Inhibitor Lung Cancer Program •Program Objectives Objectives Oppo
Slide 22: SGR-3515 Status and Next Steps
SGR-3515 Status and Next Steps Strong mechanistic • Clinically validated target rationale • Potential benefit in wide range of tumor types • Potentially superior Wee1/Myt1 potency, improved selectivity and lower drug-drug interaction liability in preclinical models Differentiated profile • Profile e
Slide 23: Materials Science
Materials Science @ Schrédinger
Slide 24: Leveraging Platform Synergies: Materials Science
Leveraging Platform Synergies: Materials Science • Materials Science business launched in 2012 • Leverages 30+ years of innovation in atomic-scale simulation solutions Initial Collaborations: Next-Gen Batteries • Developing atomistic simulations to improve battery performance • Agreement renewed for
Slide 25: Platform Has Broad Application Across Industrial Materials Design and Development
Platform Has Broad Application Across Industrial Materials Design and Development Consumer Catalysis & Energy Alloys, Organic Polymeric Semi- Complex Packaged Reactive Capture & Metals & Electronics Materials conductors Formulations Goods Systems Storage Ceramics Tailored solutions designed to reduc
Slide 26: Financial Overview
Financial Overview @ Schrédinger
Slide 27: 1Q25 Financial Highlights vs. 1Q24
1Q25 Financial Highlights vs. 1Q24 Three Months Ended March 31 1Q 2024 1Q 2025 % Change Software revenue $33.4 $48.8 46% Drug discovery revenue $3.2 $10.7 237% Total revenue $36.6 $59.6 63% Gross profit $18.9 $31.1 Software gross margin 76% 72% Operating expenses $86.3 $82.0 (5.0%) Other (expense)/i
Slide 28: Four-Quarter Trailing Average Software Quarterly Revenue Trend
Four-Quarter Trailing Average Software Quarterly Revenue Trend 50 48.9 45.1 42.3 39.8 40.1 41.6 40 33.9 33.7 33.5 34.6 30.0 31.5 31.6 30 28.3 $ Millions 23.8 24.6 24.9 23.1 21.3 19.6 20 18.0 10 0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 2020 2020 2020 2020 2021 2021 2021 2021 2
Slide 29: Hosted Contracts Are a Growing Share of Total Software Revenue
Hosted Contracts Are a Growing Share of Total Software Revenue Hosted Contracts as % of Software Revenue (Trailing Hosted Contract Revenue 4-Quarter Average, %) 20% Hosted Software Share of Software Revenue ($M) 15% Revenue (%) 10% 5% 0% 2020 2021 2022 2023 2024 2025 2020 2021 2022 2023 2024 2025 Gr
Slide 30: Full Year 2024 Key Performance Indicators (KPIs)
Full Year 2024 Key Performance Indicators (KPIs) Software KPI 2023 2024 Total annual contract value (ACV) $154.2M $190.8M ACV of Top 10 Customers $51.0M $73.1M Number of customers with ACV ≥$5M 4 8 Number of customers with ACV ≥$1M 27 31 Number of customers with ACV ≥$500k 54 61 Number of customers
Slide 31: Continued Opportunity for Growth and Adoption within Large Biopharma
Continued Opportunity for Growth and Adoption within Large Biopharma* 0.15% 2024 Schrödinger ACV as % of 2024 R&D spend 0.10% 0.05% 0.00% $1 $5 Schrödinger 2024 ACV ($M) * Each dot represents the top 30 publicly-traded companies by total R&D expenditure for FY 2024. The X-axis represents each compan
Slide 32: Growth in Top Customer Average ACV By Customer Ranking Group Over Time
Growth in Top 20 Customer Average ACV By Customer Ranking Group Over Time *Represents the average ACV per customer for the top 5, 10, 15 and 20 customers for each year. This figure represents the growth in ACV by each group but does not represent the growth of any individual customer or customers as
Slide 33: Software and Drug Discovery Revenues: 2019-2024
Software and Drug Discovery Revenues: 2019-2024 250 Software products and services Drug discovery Drug discovery 200 $58 $27 2019-24 CAGR 7.6% Revenue ($millions) $45 150 $25 100 $16 $180 $159 $19 $136 $113 Software $50 $93 $67 2019-24 CAGR 22.0% $0 2019 2020 2021 2022 2023 2024 Cash is supplemented
Slide 34: Capital Allocation Strategy Built on Proprietary Insights and Competitive Advantages
Capital Allocation Strategy Built on Proprietary Insights and Competitive Advantages in Computational Chemistry Aiming to Generate Positive Returns from Deployment of Technology, Expertise and Capital Opportunities that leverage: Commercially Validated Target or Useful Development Goal Innovation •
Slide 35: 2025 Financial Guidance
2025 Financial Guidance (As of May 7, 2025) 2024 Actual 2025 Guidance Software revenue $180.4 +10% – 15% Drug discovery revenue $27.2 $45 – $50 Software gross margin 80% 74% – 75% Operating expense growth 7.3% Less than 5% Cash used in operating activities $157.4 Lower than 2024 (in millions) For th
Slide 36: Strategic Priorities
Strategic Priorities • Increase customer adoption of computational technology • Deliver planned major enhancements to the platform • Present initial clinical data from the Phase 1 study of SGR-1505 in June 2025 • Present initial clinical data from the Phase 1 study of SGR-2921 in 2H 2025 • Present i
Slide 37: Revolutionizing Medicines and Materials Discovery
Revolutionizing Medicines and Materials Discovery May 2025
Slide 38: Appendix
Appendix Annual Contract Value (ACV). With respect to contracts that have a duration of one year or less, or contracts of more than one year in duration that are billed annually, ACV is defined as the contract value billed during the applicable period. For contracts with a duration of more than one