![\"Image](\"https:\/\/www.europesays.com\/france\/wp-content\/uploads\/2026\/06\/Screenshot-2026-06-15-at-11.53.49-AM.png\")
<\/p>\n<\/p>\n
Image from Owkin<\/p>\n
Over the past two years, software engineering has handed a growing share of its routine work to AI agents. At one end of the spectrum, companies ranging from Google<\/a> to Anthropic use AI to write the bulk of their code. At the other, there are reports of the bills coming due for heavy users at companies like Uber<\/a> and Microsoft. Drug discovery is hoping to capture the speed these agents promise without inheriting the quality and cost problems trailing them, aiming to take the workflows that consume a trained expert\u2019s time and let an agent run them at scale.<\/p>\n A wave of companies now sells versions of that idea under the banner of the \u201cAI co-scientist.\u201d Google DeepMind helped popularize the name and, on May 19, its peer-reviewed standing: Nature<\/a> published the paper documenting Co-Scientist<\/a>, a multi-agent system built on Gemini that generates, debates, and ranks hypotheses, with wet-lab validations in cancer drug repurposing and liver fibrosis, and Google has begun rolling it out to researchers as Hypothesis Generation inside its Gemini for Science<\/a> suite. Lila Sciences<\/a>, a Flagship Pioneering spinout, has raised more than $200 million<\/a> to build what it calls \u201cscientific superintelligence,\u201d pairing models with robotic labs. FutureHouse<\/a> and its for-profit spinout Edison Scientific build autonomous literature-and-reasoning agents, one of which reached Nature the same week as Google\u2019s. At the smaller end, the Seattle startup Potato<\/a>, backed by $4.5 million led by Draper Associates, sells an AI co-scientist named Tater that turns a researcher\u2019s intent into robot-ready experimental protocols.<\/p>\n Jonas B\u00e9al, head of product at Owkin. (Photo: Owkin)<\/p>\n Owkin, the French-American techbio that has raised $300 million across a decade, is the latest entrant, with a platform it bills as an \u201cAI Scientist.\u201d K Pro, built on that decade of Owkin\u2019s biomedical AI work, lets pharmaceutical teams query multimodal patient data in natural language and run AI agents across the pipeline, from early discovery through clinical development. What Owkin argues sets it apart is that data layer, drawn from more than 800 hospitals, which head of product Jonas B\u00e9al calls the difference between real biological insight and, without it, \u201cLLM guesses.\u201d<\/p>\n Owkin focuses on validation through a \u201clab-in-the-loop\u201d system in which the AI designs the experiments needed to confirm or kill its own hypotheses. \u201cThat\u2019s what you would expect from a real scientific copilot,\u201d he said in March, \u201cnot only generating the idea, but generating what you need to make the idea concrete and validated.\u201d<\/p>\n Three months later, Owkin has signed two major K Pro agreements: a five-year license with Sanofi and a three-year license with AstraZeneca. B\u00e9al confirmed by email that neither includes lab-in-the-loop validation from Owkin\u2019s side, and that the initial scope of both is competitive intelligence and decision support. \u201cValidation is absolutely a bottleneck,\u201d he wrote, \u201cbut currently this deal does not include lab-in-the-loop validation from the Owkin side.\u201d<\/p>\n In a recent Q&A, lightly edited for length and clarity, B\u00e9al walked through what the Sanofi deal adds to a relationship that goes back to 2021, what Owkin\u2019s \u201cpurpose-built\u201d agents actually are, and why the bottleneck he flagged in March sits outside the deal\u2019s initial scope.<\/p>\n R&D World: Your 2021 partnership covered target identification, patient subgrouping, and drug positioning. What does this collaboration let Sanofi do that the earlier one did not?<\/p>\n B\u00e9al: The prior agreement was a strategic alliance for target identification in oncology which expanded into drug positioning in I&I. This new collaboration is specifically to license Owkin\u2019s K Pro and build specialized agents on top of the platform. K Pro offers much of the same functionality, from drug discovery to development, with many common capabilities, now packaged into one single platform to make them available at the user\u2019s fingertips with specialized agents. We are not yet disclosing the exact capabilities of the specialist agents.<\/p>\n R&D World: Does \u201cpurpose-built\u201d mean new OwkinZero-style fine-tuned models trained on Sanofi data, new tool-and-recipe scaffolding around frontier models, or both? And who owns the resulting models and weights?<\/p>\n B\u00e9al: OwkinZero is a fine-tuned LLM, we are not building these for Sanofi. We are not disclosing the exact capabilities of the agents, but they will likely function as tool-and-recipe scaffolding that can be called by the K Pro orchestrator around specific use cases of interest. We can\u2019t disclose if they will integrate frontier models, or the ownership of those models\/weights.<\/p>\n R&D World: How do Owkin\u2019s agents interoperate with Sanofi\u2019s existing AI stack? Is this an MCP-based integration, and does data flow back to improve K Pro generally, or stay with Sanofi?<\/p>\n B\u00e9al: K Pro is built in a modular way so that the agentic platform can easily connect to additional capabilities provided by the client, for instance through MCP amongst other ways. In this way Sanofi can connect their internal AI stack to K Pro. Sanofi\u2019s data will remain internal to Sanofi as part of our strict safeguards on partner privacy and data security.<\/p>\n R&D World: You\u2019ve called validation the real bottleneck. Does this collaboration include the lab-in-the-loop validation loop, and where in the pipeline do the first Sanofi agents operate?<\/p>\n B\u00e9al: Validation is absolutely a bottleneck, but currently this deal does not include lab-in-the-loop validation from the Owkin side. Exact validation strategies will be defined specifically for use cases of interest, leveraging the best of Owkin and Sanofi data and capabilities. Yes, the initial scope is competitive intelligence and decision support. I\u2019m afraid we can\u2019t yet comment on where in the pipeline the specialist agents will operate.<\/p>\n R&D World: Owkin frames K Pro as a step toward Biological Artificial Superintelligence and the eventual automation of R&D. For this deal specifically, what does success look like in measurable terms over the coming years?<\/p>\n B\u00e9al: Yes, Owkin\u2019s eventual goal is to automate K Pro (our AI scientist) to allow it to make discoveries humans alone could not make. When we have done this successfully we will have achieved Biological Artificial Superintelligence (BASI). K Pro users (like Sanofi) benefit from our progress towards this on the platform, but the goal of our partnership with Sanofi is not to come closer to BASI. Instead, in the short to mid-term, success looks like delivering three specialist agents to the highest standards and ensuring Sanofi\u2019s satisfied and increased use of K Pro in their work. The validation and trust gained along the way will form the basis for increasingly automatized behavior.<\/p>\n","protected":false},"excerpt":{"rendered":"Image from Owkin Over the past two years, software engineering has handed a growing share of its routine…\n","protected":false},"author":2,"featured_media":35937,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[12983],"tags":[15468,25337,25338,25339,25340,25341,25342,25343,22519,25344,25345,22522,25346,13012,25347],"class_list":["post-35936","post","type-post","status-publish","format-standard","has-post-thumbnail","category-sanofi","tag-ai-agents","tag-ai-co-scientist","tag-ai-in-drug-discovery","tag-astrazeneca","tag-biological-artificial-superintelligence","tag-biomedical-ai","tag-futurehouse","tag-google-deepmind","tag-k-pro","tag-lab-in-the-loop","tag-lila-sciences","tag-owkin","tag-pharmaceutical-rd","tag-sanofi","tag-techbio"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/france\/wp-json\/wp\/v2\/posts\/35936","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/france\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/france\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/france\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/france\/wp-json\/wp\/v2\/comments?post=35936"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/france\/wp-json\/wp\/v2\/posts\/35936\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/france\/wp-json\/wp\/v2\/media\/35937"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/france\/wp-json\/wp\/v2\/media?parent=35936"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/france\/wp-json\/wp\/v2\/categories?post=35936"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/france\/wp-json\/wp\/v2\/tags?post=35936"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"\"](\"https:\/\/www.europesays.com\/france\/wp-content\/uploads\/2026\/06\/1643977271334-300x300.jpeg\")
<\/p>\n