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Gilead Sciences

Public biopharmaceutical company (NASDAQ: GILD) known for HIV and hepatitis C antivirals and Kite cell therapy, and a partnership-first AI adopter: Genesis, Terray, Tempus, Nucleai and Deepcell supply its AI capability. Sells no AI product.

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📋About Gilead Sciences

Updated September 12, 2026

Gilead Sciences is a publicly traded biopharmaceutical company (NASDAQ: GILD) headquartered in Foster City, California, best known for its antiviral franchises in HIV and hepatitis C and, through its Kite subsidiary, for cell therapy in oncology. It appears here not as an AI vendor but as a large pharma AI adopter: one of the strategic priorities in its 2026 proxy statement is to adopt and scale AI to transform how the company works, and its annual report frames AI both as a lever for accelerating research and as a cybersecurity risk to be managed. Gilead sells no AI product.

What distinguishes Gilead from Moderna, which built hundreds of models in-house, is a partnership-first model: it buys specialist AI capability rather than building it. The disclosed deals map the drug-development pipeline end to end. Genesis Therapeutics applies its GEMS generative platform to design small molecules against three Gilead targets, under a research collaboration that paid 35 million dollars upfront (2024). Terray Therapeutics brings its AI-native small-molecule discovery platform, which pairs ultra-miniaturized high-throughput chemistry with machine learning, to a multi-target program (2024). Tempus AI, under an expanded multi-year agreement (2026), gives Gilead enterprise-wide access to its Lens platform of de-identified multimodal patient data for trial design, indication selection and biomarker strategy across the oncology pipeline. Nucleai runs AI-driven analysis of pathology slides across Gilead's antibody-drug-conjugate trials to find spatial biomarkers (2026). And Deepcell is co-developing a foundation model, trained on single-cell images of Gilead's Chinese hamster ovary cell lines, to pick manufacturing cell lines with better yield and stability; the companies say they intend to publish an open-weight version for the wider bioprocessing community, with no date or license yet named (2026). An earlier collaboration with insitro (2019) used machine-learning disease models to hunt for liver-disease targets.

Inside the company the same pattern holds. An Amazon Kendra deployment cut document-search time roughly in half across the pharmaceutical development and manufacturing unit, and Gilead broke ground in 2025 on a technical development center at its Foster City campus, part of a 32 billion dollar United States investment plan running through 2030, designed around digitalization, autonomous robotics and real-time monitoring.

The honest framing: Gilead's value rests on its antiviral, oncology and inflammation franchises and its pipeline, with AI as an efficiency and R&D lever layered on top. For learners it is the clearest example of the partnership adopter, a large incumbent that treats AI as something to procure from a market of specialists, and a useful contrast to Lilly, which productized its own models, and to the AI-native drug-discovery companies whose platform is the product.

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