Slide 1: Pioneering Computational Molecular Design
Pioneering Computational Molecular Design February 2024
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, contained in this
Slide 3: 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 ~1,785 customers worldwide§ • Materials Design 17 drug discovery collaborators* • Drug Discovery & Development 7+ act
Slide 4: Software Business Highlights
Software Business Highlights $159.1M 17.4% 2023 software revenue 2023 software revenue growth vs. 2022 $6.7M 54 98% $3.5M Number of customers with 2023 software customer $1.8M $1.4M ACV ≥$500,000 retention rate with ACV ≥ $500K 1-5 6-10 11-15 16-20 27 ~20X Average ACV of top 20 customers Customers w
Slide 5: Designing Drugs Is a Challenging Multi-Parameter Optimization Problem
Designing Drugs Is a 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 6: Vision for the Future of Drug Discovery
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 Potency ✓ Clea
Slide 7: Physics & Machine Learning Are Complementary
Physics & Machine Learning Are Complementary Physics + Machine Learning Physics-based Training set for ML Machine Learning / Methods generated using Physics Artificial Intelligence ✓ No training set required ✓ Fast ✓ Effective at interpolation ✓ Can extrapolate into novel ✓ Accurate ✓ Fast chemical
Slide 8: Physics & Machine Learning Are Complementary
Physics & Machine Learning Are Complementary Physics used to produce sufficiently large representative training set for Machine Learning Design Compute Select 1 billion properties of Build molecules w/ 1,000 1,000 Machine Generative random Learning molecules w/ model AI & De Novo molecules Physics D
Slide 9: A History of Scientific Innovation & Platform Advancement
A History of Scientific Innovation & Platform Advancement Next Gen Protein Protein Refinement Free Energy Refinement Calculations Enablement of Quantum Enabled accurate Molecular Broadly applicable and proteins without prediction of local protein experimental Mechanics structure Dynamics accurate ca
Slide 10: Platform Validated by Advancing Collaboration Programs
Platform Validated by Advancing Collaboration Programs(1)(2) 8 programs in the clinic (+ 5 in IND-enabling studies) Phase 1 Phase 2 Phase 3 Immuno-oncology Metabolic Diseases*** Psoriasis**** Pulmonary Arterial Hypertension Inflammatory Bowel Disease Oncology** FDA-Approved Oncology TIBSOVO* IDHIFA*
Slide 11: Proprietary Pipeline
Proprietary Pipeline @ Schrédinger
Slide 12: Advancing Multiple Clinical and Preclinical Programs
Advancing Multiple Clinical and Preclinical Programs DISCOVERY PRECLINICAL PHASE 1 SGR-1505 (MALT1) B-cell Malignancies SGR-2921 (CDC7) AML/MDS SGR-3515 (Wee1/Myt1) Solid Tumors PRMT5-MTA Solid Tumors EGFRC797S Solid Tumors NLRP3 Immunology LRRK2 Neurology Undisclosed Programs Multiple Areas 12
Slide 13: MALT1 Protease Inhibition Is Clinically Validated
MALT1 Protease Inhibition Is Clinically Validated Allosteric Inhibition of MALT1 Non-Hodgkin's Lymphoma • Clinically validated by 3rd party MALT1 28% ORR monotherapy1,3,4 inhibitor showing monotherapy and Chronic Lymphocytic Leukemia (CLL/SLL) combination activity in human B-cell 67% ORR in BTK comb
Slide 14: SGR-1505 Status and Next Steps
SGR-1505 Status and Next Steps • SGR-1505 was well tolerated with no dose-limiting toxicities Phase 1 healthy subject and no serious adverse events study completed • Favorable PK and clear evidence of target engagement Phase 1 study in • Primary objectives: Evaluate safety, PK, PD, RP2D advanced B-c
Slide 15: CDC7 Is an S-phase Kinase That Regulates DNA Replication and the Replication Stress Response
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 16: SGR-2921 Status and Next Steps
SGR-2921 Status and Next Steps • Replication stress high 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 17: Wee1 Inhibition Is Clinically Validated in 3rd Party Studies
Wee1 Inhibition Is 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 O
Slide 18: 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 • Superior Wee1/Myt1 potency, selectivity and lower DDI liability in preclinical models Differentiated profile • Profile enables optimized dosing schedule to mai
Slide 19: Advancing Multiple Discovery Programs
Advancing Multiple Discovery Programs EGFRC797S PRMT5-MTA NLRP3 • Optimizing a wild-type-sparing, • Leads display MTAPKO selective • Advancing leads in two series CNS-penetrant molecule anti-proliferative effects, and with excellent in vivo potency favorable solubility and ADME and ADME profiles • P
Slide 20: Materials Science
Materials Science @ Schrédinger
Slide 21: 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 22: 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 that reduce cost,
Slide 23: Financial Overview
Financial Overview @ Schrédinger
Slide 24: 4Q23 Financial Highlights vs. 4Q22
4Q23 Financial Highlights vs. 4Q22 Three Months Ended December 31 2022 2023 % Change Total revenue $56.8 $74.1 30.4% Software revenue $47.8 $68.7 43.6% Drug discovery revenue $9.0 $5.5 (39.4%) Gross profit $38.7 $57.6 48.7% Software gross margin 83% 87% Operating expenses $67.2 $87.2 29.6% Other inc
Slide 25: 2023 Financial Highlights vs. 2022
2023 Financial Highlights vs. 2022 Twelve Months Ended December 31 2022 2023 % Change Total revenue $181.0 216.7 19.7% Software revenue $135.6 $159.1 17.4% Drug discovery revenue $45.4 $57.5 26.8% Gross profit $101.0 $140.7 39.3% Software gross margin 78% 81% Operating expenses $247.8 $318.1 28.4% O
Slide 26: Four-Quarter Trailing Average Quarterly Revenue Trend
Four-Quarter Trailing Average Quarterly Revenue Trend 54.2 49.3 49.8 50 48.4 Drug Discovery 45.2 14.4 42.6 Software 40.8 15.3 15.6 14.9 38.6 11.3 40 34.5 9.3 11.0 8.6 30.2 31.2 28.5 6.2 30 $ Millions 27.0 6.3 25.2 5.6 23.8 4.7 22.7 3.9 3.9 4.2 20 4.8 39.8 33.9 33.7 33.5 34.6 30.0 31.5 31.6 28.3 23.1
Slide 27: 2024 Financial Guidance
2024 Financial Guidance (As of February 28, 2024) 2023 Actual Guidance Total revenue $216.7 Software revenue $159.1 6% – 13% Drug discovery revenue $57.5 $30 – $35 Software gross margin 81% Similar to 2023 Operating expense growth 28.4% 8% – 12% Cash used in operating activities $136.7 Above 2023 (i
Slide 28: Capital Allocation Strategy Built on Proprietary Insights and Competitive Advantages in Computational Chemistry
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 29: Upcoming Milestones
Upcoming Milestones • Submit IND for SGR-3515 in first half of 2024, initiate a Phase 1 study in 2024 • Report initial data from Phase 1 study of SGR-1505 in late 2024 or 2025 • Report initial data from Phase 1 study of SGR-2921 in late 2024 or 2025 • Advance discovery programs to enable an IND subm
Slide 30: Pioneering Computational Molecular Design
Pioneering Computational Molecular Design February 2024
Slide 31: 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