SOPHiA GENETICS (SOPH) TD Cowen 45th Annual Healthcare Conference summary

Company overview and platform differentiation

• Focuses on democratizing data-driven medicine via a cloud-native platform, SOPHiA DDM, which analyzes diverse digital health data including genomics, imaging, and clinical data.

• Employs a decentralized model, serving 800 customers in 70 countries, with AI-driven analytics learning from 2 million profiles.

• Platform enables rapid, accurate, and scalable analysis, allowing labs to retain data ownership and reduce IT overhead.

• Land-and-expand strategy encourages adoption of multiple applications per customer, driving expansion and stickiness.

• Unique selling points include high accuracy, fast turnaround, and scalability, with proven ability to match central lab results globally.

Financial outlook and growth drivers

• 2025 revenue guidance targets 10%-17% growth, with a focus on onboarding 92 new genomics customers signed in 2024.

• U.S. market remains underpenetrated but is growing rapidly, highlighted by recent wins at Mount Sinai and Mayo Clinic.

• New liquid biopsy offering, MSK Access, has seen rapid adoption with 34 institutions signed in 10 months.

• Margins are improving, with 2023 adjusted gross margin at 72.8% and expectations for further increases.

• Biopharma business not included in current guidance, representing potential upside if new contracts are secured.

Technology and clinical impact

• AI-driven platform delivers 98% concordance with central lab assays, enabling decentralized, high-quality testing worldwide.

• Enables hospitals to perform complex tests locally, reducing turnaround from weeks to hours and improving patient care.

• Supports both clinical and biopharma markets, facilitating clinical trial recruitment and companion diagnostics.

• New offerings like NGS exomes allow for deep variant detection, supporting both oncology and rare disease applications.

• Business model is volume-based, aligning incentives with customer usage and benefiting from rising test complexity.