Schrödinger (SDGR) investor relations material

Platform innovation and AI integration

• Platform leverages first-principles physics to generate massive, high-quality training sets, amplifying the impact of machine learning and AI in drug discovery.

• Automation agents and workflows are being developed to enable efficient use of complex technologies, addressing expertise shortages.

• AI's effectiveness in chemistry is limited by available data, but the platform overcomes this by simulating experimental data at scale.

• The software licensing model allows scalability by tying usage to the number of calculations and molecules explored.

• Retention rate for high-value customers is nearly 100%, and software is cited in over 2,000 industry patents.

Regulatory and industry landscape

• FDA's push for computational tools to reduce animal testing has driven interest in predictive tox initiatives, supported by a Gates Foundation grant.

• Regulatory changes are fostering broader adoption of AI and computational methods in drug development.

• The evolving stance of the FDA on AI has made industry engagement easier and increased platform adoption.

• Strategic partnerships, especially with Chinese biotech firms, are seen as important for global competitiveness.

Pipeline and clinical development

• SGR-1505, a MORT1 inhibitor for B-cell malignancies, showed a strong safety profile and early efficacy, with no dose-limiting toxicities.

• The molecule represents a new, well-tolerated mechanism in a space dominated by BTK and BCL2 inhibitors.

• Strategic alternatives are being explored for SGR-1505, with a focus on partnering for mid- and late-stage development.

• Combination studies with BTK and BCL2 inhibitors are planned to maximize commercial potential.

• SGR-2921 was discontinued in AML/MDS due to patient immunosuppression risks, not molecule quality.