Generate Biomedicines (GENB) investor relations material

Platform overview and differentiation

• Utilizes a tightly integrated dry and wet lab approach to rapidly generate experimental data and train models for novel protein design, enabling efficient and scalable drug discovery.

• Focuses on large molecules and is modality agnostic, working across eight modalities and leveraging advanced cryo-EM for high-throughput structural analysis.

• Key differentiator is the combination of computational and experimental capabilities, creating a feedback loop that refines protein design beyond traditional immunization or biophysical methods.

• Achieves atomistic resolution in protein-protein interactions, solving structures daily with four cryo-EM microscopes.

• Partnerships with Amgen and Novartis are nearing completion, with new collaborations expected in the next 6–18 months.

Clinical pipeline and development strategy

• Lead program GB-0895, an anti-TSLP antibody, entered phase III for severe asthma, aiming for biannual dosing and targeting a 55% reduction in exacerbations across all EOS levels.

• Phase I data supported direct advancement to phase III, showing strong biomarker modulation and comparable or superior target occupancy to tezepelumab.

• Plans to propose a direct phase III trial in COPD, potentially saving two years and significant costs, with regulatory alignment expected soon.

• Oncology pipeline includes a payload neutralizer for MMAE-based ADCs to reduce peripheral neuropathy, with phase I dose escalation underway and data expected by 2027.

• CAR T program targeting MUC16 in ovarian cancer is entering the clinic, leveraging technology to optimize binding and framework for solid tumors.

Market positioning and future outlook

• Biannual dosing aligns with patient visit patterns, potentially improving compliance and offering cost savings over current therapies.

• Technology enables optimization of internalization for ADCs, with preclinical candidates approaching development nomination.

• Exploring broader collaborations and potential spin-offs to monetize platform scalability and modality intellectual property.

• Defensibility lies in the unique integration of experimental and computational capabilities, rather than algorithms alone, creating a virtuous cycle of learning.

• Focus remains on infectious disease, immunology, and inflammatory diseases, with potential expansion into cardiometabolic and neurology through partnerships.