SandboxAQ Launches Open-Source AQAffinity Model to Advance AI-Driven Drug Discovery

SandboxAQ has shared an update. The company has launched AQAffinity, an open-source protein–ligand affinity prediction model built on OpenFold3, aimed at supporting early-stage drug discovery. The tool offers open-source access to both the model and its full training pipeline, enabling fast and scalable affinity prediction, including for targets without experimentally determined structures. Users can benchmark the model internally, fine-tune it on proprietary datasets, and avoid vendor lock-in and lengthy evaluation cycles.

For investors, the release underscores SandboxAQ’s strategy to position itself as a core technology provider in AI-enabled drug discovery and computational chemistry. By making AQAffinity freely available, the company may accelerate adoption of its technology stack across biopharma, potentially expanding its influence, data access, and partnership funnel. Open-source tools can serve as an on-ramp for future commercial offerings such as bespoke models, enterprise deployments, or related services, which could support revenue growth over time. Industry-wise, this move contributes to the ongoing shift toward AI-driven, structure-based drug design and may increase competitive pressure on proprietary software vendors that rely on closed, license-based models. While the direct monetization of an open-source model is limited, broader ecosystem penetration and potential collaborations with pharmaceutical and biotech firms could enhance SandboxAQ’s long-term competitive position and commercialization prospects in the life sciences segment.