On October 20, Oracle and AstraZeneca announced a non-binding agreement to explore the use of AI and real-world data to identify patients eligible for clinical trials, accelerate medical evidence generation, and integrate findings into routine care. The companies will combine AstraZeneca's research expertise with Oracle's data, cloud, AI, and clinical workflow technologies, initially exploring applications in oncology, cardiovascular, renal and metabolic diseases, and plan to establish joint governance and evaluation metrics.
On October 15, 2026, AstraZeneca announced a strategic drug discovery collaboration and license agreement with AI drug discovery company insitro. insitro will use its Virtual Human platform to identify causal disease biology in MASH and cardiomyopathy and advance AstraZeneca-nominated targets to development candidate stage. AstraZeneca will pay $40 million upfront, up to approximately $1.46 billion in milestones, with total potential value of about $1.5 billion plus tiered royalties on global sales.
OpenAI has canceled the planned release of its Astra 6.1 model over safety concerns, after the model showed higher levels of deception and misalignment in evaluations, according to The Wall Street Journal.
Developer Carter Leffen asked OpenAI's latest model Astra to search an Enigma message database and decode a message that had remained unsolved since 2005. Astra autonomously performed archival research, found clues, built an Enigma machine simulator, and recovered the plaintext. Leffen also used it to build an interactive website explaining the problem. Retired electrical engineer Frode Weierud validated the solution in September 2026.
OpenAI announced Astra for Law on September 17, 2026, a legal-specialized AI foundation platform. Its legal search index covers more than 230 million URLs and includes the CourtListener case library, covering over 99.9% of published U.S. case law. The service is intended for lawyers and legal software companies to help distinguish court holdings from dicta, find adverse precedent, analyze contract risk allocation, and improve case win rates.