AbCellera vs Aignostics
Side-by-side comparison of AI visibility scores, market position, and capabilities
Vancouver-based antibody discovery platform with 104+ partner programs; $75M FY2025 revenue. Expanding into wholly owned assets with ABCL635 in Phase 1 for vasomotor symptoms.
About
AbCellera Biologics was founded in 2012 in Vancouver, Canada by Carl Hansen, growing out of research at the University of British Columbia. The company built a high-throughput antibody discovery platform integrating microfluidics, genomics, single-cell sequencing, and AI/ML to rapidly identify therapeutic antibody candidates from natural immune responses. AbCellera played a prominent role in the COVID-19 pandemic by discovering bamlanivimab for Eli Lilly in under 90 days.\n\nAbCellera's partnership model operates on a discovery fee plus downstream milestone and royalty structure, having started over 104 partner-initiated programs with downstream participation as of December 2025. Partners include major pharmaceutical companies and biotechs; the company expanded its collaboration with AbbVie in 2025 to develop T-cell engagers for oncology. Total FY2025 revenue was $75 million ($47M from royalties/licensing, $27M from partnered program work), compared to $29 million in 2024—a dramatic increase driven by royalty flows from approved medicines.\n\nIn 2025 AbCellera began transitioning from pure partnership model toward wholly owned therapeutic assets, with ABCL635 (a GnRH receptor antibody for vasomotor symptoms) entering Phase 1. The company maintains approximately $700 million in liquidity, providing a long runway. AbCellera is considered a foundational infrastructure provider for the antibody-based drug discovery ecosystem.
Aignostics is a Berlin-based computational pathology company applying AI to histopathology image analysis for drug development and clinical diagnostics; raised €45M+ total including a €37M Series B in 2024;
About
Aignostics is a Berlin-based precision pathology company founded in 2019 as a spinout from Charité – Universitätsmedizin Berlin, one of Europe''s largest university hospitals. The company develops foundation models and AI-powered image analysis tools for computational pathology — applying deep learning to digitized histopathology slides (whole slide images) to detect, classify, and quantify cellular and tissue features at scale. Its technology enables pharmaceutical companies, contract research organizations (CROs), and diagnostic laboratories to analyze tissue samples faster, more consistently, and with greater quantitative depth than human pathologists alone.
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