Qdrant Powers AI Platform Indexing 28 Million PubMed Abstracts to Accelerate Cancer Research

Qdrant, a provider of vector search technology, has announced that its cloud infrastructure is powering the AI research platform of Sapu, an early-stage biopharmaceutical company focused on hard-to-treat cancers. According to a blog post by Daniel Azoulai, Sapu’s platform can now index and query all 28 million abstracts from PubMed in a single searchable collection, significantly accelerating biomedical discovery workflows.

The platform, which evolved from an early prototype into a production-scale system, supports scientific literature review, standard operating procedure retrieval, and AI-assisted research authorship. Sapu reports that the platform has already contributed to seven peer-reviewed research papers and is used broadly across its research operations. The company is also expanding the platform’s capabilities through a robotics partnership with Techforce and evaluating edge deployments for secure, air-gapped laboratory environments.

Qdrant’s hybrid vector and metadata retrieval architecture is central to enabling the scale, speed, and flexibility required for these next-stage applications. Qdrant, founded after co-founders André Zayarni and Andrey Vasnetsov identified a gap in existing vector similarity search tools, offers both open-source and managed cloud vector search solutions. Built in Rust, Qdrant has surpassed 250 million downloads, earned more than 29,000 GitHub stars, and grown to a global team of more than 100 employees across 20-plus countries.

The implications of this announcement are significant for the field of cancer research. By enabling rapid, comprehensive analysis of the vast PubMed database, the platform can help researchers identify patterns, discover new insights, and accelerate the development of treatments for hard-to-treat cancers. The use of vector search technology allows for more nuanced and efficient retrieval of relevant information compared to traditional keyword-based search methods.

For more information about Qdrant, visit Qdrant's website. For details on Sapu’s platform, refer to the full blog post by Daniel Azoulai. This development underscores the growing role of AI and advanced search technologies in life sciences, offering a blueprint for how similar platforms could be applied to other biomedical research areas.