[{"data":1,"prerenderedAt":118},["ShallowReactive",2],{"bnrPZW6RSxS1H5b5IRGMeALwM5xNzlf2YL0I935btoE":3,"_apollo:default":116,"_apollo:identified":117},{"seo":4,"posts":15},{"social":5,"openGraph":11,"__typename":14},{"twitter":6,"__typename":10},{"cardType":7,"username":8,"__typename":9},"summary_large_image","dassault3ds","SEOSocialTwitter","SEOSocial",{"defaultImage":12,"__typename":13},null,"SEOOpenGraph","SEOConfig",{"nodes":16,"__typename":115},[17],{"id":18,"slug":19,"title":20,"uri":21,"excerpt":22,"locale":23,"featuredImage":26,"tableOfContents":34,"content":43,"date":44,"translations":45,"author":46,"tags":59,"globalTags":81,"brands":89,"keywords":100,"seo":103,"__typename":114},"cG9zdDozMTcyMDQ=","agentic-ai-meets-the-cmc-dossier-why-trust-starts-with-the-data","Agentic AI Meets the CMC Dossier: Why Trust Starts with the Data","\u002Fbrands\u002Fbiovia\u002Fagentic-ai-meets-the-cmc-dossier-why-trust-starts-with-the-data","\u003Cp>The hard part was never the writing.\u003C\u002Fp>\n",{"locale":24,"__typename":25},"en_US","Locale",{"node":27,"__typename":33},{"large":28,"__typename":29,"medium_large":28,"thumbnail":30,"srcSet":31,"sizes":32},"https:\u002F\u002Fblog-assets.3ds.com\u002Fuploads\u002F2026\u002F10\u002Fmarie-regulatory-blog-768x512.jpg","MediaItem","https:\u002F\u002Fblog-assets.3ds.com\u002Fuploads\u002F2026\u002F10\u002Fmarie-regulatory-blog-150x150.jpg","https:\u002F\u002Fblog-assets.3ds.com\u002Fuploads\u002F2026\u002F10\u002Fmarie-regulatory-blog-300x200.jpg 300w, https:\u002F\u002Fblog-assets.3ds.com\u002Fuploads\u002F2026\u002F10\u002Fmarie-regulatory-blog-1024x683.jpg 1024w, https:\u002F\u002Fblog-assets.3ds.com\u002Fuploads\u002F2026\u002F10\u002Fmarie-regulatory-blog-768x512.jpg 768w, https:\u002F\u002Fblog-assets.3ds.com\u002Fuploads\u002F2026\u002F10\u002Fmarie-regulatory-blog-1536x1024.jpg 1536w, https:\u002F\u002Fblog-assets.3ds.com\u002Fuploads\u002F2026\u002F10\u002Fmarie-regulatory-blog.jpg 1600w","(max-width: 300px) 100vw, 300px","NodeWithFeaturedImageToMediaItemConnectionEdge",[35,36,37,38,39,40,41,42],"The real cost is hidden in the seams|the-real-cost-is-hidden-in-the-seams-0","Why \"just add AI\" makes it worse|why-just-add-ai-makes-it-worse-1","A different model: the controlled co-author|a-different-model-the-controlled-co-author-2","Structure First, then narrative|structure-first-then-narrative-3","Human oversight only counts if it is built into the workflow|human-oversight-only-counts-if-it-is-built-into-the-workflow-4","What this means for the industry|what-this-means-for-the-industry-5","The question to ask|the-question-to-ask-6","See MARIE in action|see-marie-in-action-7","\n\u003Cp>Ask anyone who has helped assemble Module 3 of a CMC dossier what the hardest part was, and you rarely hear “the writing.” You hear about the chase: finding the right stability table, reconciling a value in the report against the one in the LIMS, discovering three weeks later that a spreadsheet was revised after the narrative was drafted.\u003C\u002Fp>\n\n\n\n\u003Cp>The work of regulatory authoring is mostly the work of establishing, and re-establishing, that the numbers are right and that someone can prove it.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"the-real-cost-is-hidden-in-the-seams-0\">The real cost is hidden in the seams\u003C\u002Fh2>\n\n\n\n\u003Cp>Lab data lives in LIMS, ELN, spreadsheets, and a long tail of other systems. A CMC dossier is assembled by people moving that data by hand into a document-centric workflow, where it is interpreted, reformatted, and turned into narrative. Once it lands in a Word file, its history disappears. Where did this value come from? Which calculation produced it? What changed between draft four and draft five?\u003C\u002Fp>\n\n\n\n\u003Cp>Reviewers inherit the consequences. They are asked to approve a document while also acting as forensic auditors, re-verifying numbers, sources and consistency by hand. Highly skilled scientists can spend much of their time on transcription and cross-checking, and the work grows with every new submission, variation and market. Every manual handoff is also a place for an error to enter.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"why-just-add-ai-makes-it-worse-1\">Why “just add AI” makes it worse\u003C\u002Fh2>\n\n\n\n\u003Cp>Drop a general-purpose language model into this process and you get fluent prose, quickly. Fluency is not what a regulator is asking for. A paragraph that reads beautifully but contains a transposed figure, an unsupported trend claim or a number with no traceable origin is worse than a slow paragraph, because it is more likely to be believed.\u003C\u002Fp>\n\n\n\n\u003Cp>In a GxP environment, the real question about AI-generated content is “can we show where every statement came from, who reviewed it and what controls surrounded its creation?” An AI that cannot answer has no place near a submission. The more an AI system can do on its own, such as reaching across data sources and assembling content, the more the question of control matters. Regulators are already drawing this line: the draft EU GMP Annex 22 on artificial intelligence keeps generative models out of critical GMP applications and places clear weight on qualified human review wherever AI is used.\u003C\u002Fp>\n\n\n\n\u003Cp>This is the tension at the heart of AI in regulated work. The industry needs the speed AI offers, and it cannot trade away the scientific integrity and auditability its license to operate depends on.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"a-different-model-the-controlled-co-author-2\">A different model: the controlled co-author\u003C\u002Fh2>\n\n\n\n\u003Cp>The way through is to change what we ask agentic AI to be: a controlled co-author that works inside boundaries set by scientists and quality professionals.\u003C\u002Fp>\n\n\n\n\u003Cp>That framing is the thinking behind \u003Cstrong>\u003Ca href=\"https:\u002F\u002Fwww.3ds.com\u002Fproducts\u002Fbiovia\u002Fmarie\" target=\"_blank\" rel=\"noreferrer noopener\">MARIE\u003C\u002Fa>,\u003C\u002Fstrong> BIOVIA’s scientific Virtual Companion. Its role in authoring a CMC dossier is deliberately bounded: it drafts and summarizes within limits the organization sets, working from the organization’s own data and rules, while human authors and reviewers remain in control. The numbers themselves come from validated, deterministic methods; MARIE writes the narrative around them.\u003C\u002Fp>\n\n\n\n\u003Cp>In practice, that means a section starts from governed data, not a blank page. MARIE can draft an introduction or conclusion, summarize a set of results, flag a trend for a scientist to assess or bring a section into line with the organization’s tone and terminology. The organization’s scientific data stays within its own environment and all content, whether human-written or AI-generated, goes through the same review and approval before anything is published.\u003C\u002Fp>\n\n\n\n\u003Cp>What makes this workable sits underneath the AI.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"structure-first-then-narrative-3\">Structure First, then narrative\u003C\u002Fh2>\n\n\n\n\u003Cp>An AI is only as trustworthy as the content beneath it. If the source material is a pile of documents and spreadsheets, even a well-behaved model is guessing at provenance. If it is structured, reusable content that stays connected to its scientific sources, traceability stops being an after-the-fact reconstruction and becomes a property of the content. On the \u003Cstrong>3D\u003C\u002Fstrong>EXPERIENCE platform, BIOVIA \u003Ca href=\"https:\u002F\u002Fwww.3ds.com\u002Fproducts\u002Fbiovia\u002Fstructured-document-authoring\" target=\"_blank\" rel=\"noreferrer noopener\">\u003Cstrong>Structured Content Authoring\u003C\u002Fstrong>\u003C\u002Fa> provides that foundation, keeping each content component linked to its source data.\u003C\u002Fp>\n\n\n\n\u003Cp>Structure also separates what should be deterministic from what can be generative. In this model, the numbers, calculations, and transformations come from validated methods that return the same result every time, and the AI’s contribution is the narrative built on top of them.\u003C\u002Fp>\n\n\n\n\u003Cp>That changes the reviewer’s job. Instead of re-deriving whether the data is right, they can concentrate on whether the science is sound and the interpretation is defensible, which is where expert judgment matters most.\u003C\u002Fp>\n\n\n\n\u003Cp>None of this is effortless. Getting content into structured form takes upfront work, and even with guardrails, AI-generated content still needs qualified oversight. That is precisely why the review step can’t be optional.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"human-oversight-only-counts-if-it-is-built-into-the-workflow-4\">Human oversight only counts if it is built into the workflow\u003C\u002Fh2>\n\n\n\n\u003Cp>“Human-in-the-loop” is easy to claim and hard to prove. It means something only when review, edit and approval are embedded in the workflow, applied equally to human-written and AI-generated content and recorded in a revision history and audit trail that would stand up to inspection.\u003C\u002Fp>\n\n\n\n\u003Cp>The test is simple. If an inspector asked who approved a given sentence, and whether a person or an AI drafted it, could you answer in seconds? Organizations that can will adopt AI with confidence. Those that cannot will, quite rightly, keep it at arm’s length.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"what-this-means-for-the-industry-5\">What this means for the industry\u003C\u002Fh2>\n\n\n\n\u003Cp>Three shifts are coming, whatever tools get us there.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Content will become more important than documents. \u003C\u002Fstrong>The most valuable asset won’t be the finished CMC dossier but the structured, governed content from which CMC dossiers, annual product quality reviews, continued process verification reports, labeling, and SOPs can all be produced consistently.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Provenance will become a baseline expectation. \u003C\u002Fstrong>As AI-assisted authoring spreads, quality teams will increasingly look for lineage from source data to published statement, and documents that can’t show it will start to look dated.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Scientists will spend their time on judgment, not transcription. \u003C\u002Fstrong>The goal was never to remove experts from the process. Time freed from reconciling numbers can go to what only experts can do: deciding whether a trend is meaningful, challenging a specification, anticipating the questions a reviewer will ask, and planning the next study.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"the-question-to-ask-6\">The question to ask\u003C\u002Fh2>\n\n\n\n\u003Cp>Whenever a new AI capability is pitched for regulated work, the useful question isn’t “how much faster is it?” but “what happens to trust?” Speed that erodes confidence in the content isn’t progress. Speed that comes with stronger lineage, clearer accountability and more room for scientific judgment is.\u003C\u002Fp>\n\n\n\n\u003Cp>The CMC dossier of the future will still take real effort from skilled people. The difference is that their effort will go into the science rather than the seams between systems.\u003Cbr>\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"see-marie-in-action-7\">See MARIE in action\u003C\u002Fh2>\n\n\n\n\u003Cp>Watch the \u003Cstrong>\u003Ca href=\"https:\u002F\u002Fevents.3ds.com\u002Fmeet-marie-writing-dossier\">webinar\u003C\u002Fa> \u003C\u002Fstrong>to discover how MARIE supports AI-assisted CMC dossier authoring, connecting scientific data with submission-ready content.\u003C\u002Fp>\n\n\n\n\u003Chr class=\"wp-block-separator has-alpha-channel-opacity\"\u002F>\n\n\n\n\u003Cp>\u003C\u002Fp>\n","2026-10-20T15:48:39",[],{"node":47,"__typename":58},{"nicename":48,"description":49,"slug":50,"name":50,"firstName":51,"lastName":52,"avatar":53,"__typename":57},"jaya-tikhe","Jaya Tikhe has extensive experience in early drug discovery and project management. As a medicinal and organic chemist, she has a proven track record of delivering high-quality drug candidates across CNS, immunology, inflammation, and oncology. She currently leads product marketing for Dassault Systèmes’ Manufacturing, Quality, and Regulatory solutions.","Jaya Tikhe","Jaya","Tikhe",{"default":54,"url":55,"__typename":56},"mm","https:\u002F\u002Fblog-assets.3ds.com\u002Fuploads\u002F2025\u002F04\u002Fjaya-tikhe-96x96.jpg","Avatar","User","NodeWithAuthorToUserConnectionEdge",{"edges":60,"nodes":73,"__typename":80},[61,68],{"isPrimary":62,"node":63,"__typename":67},true,{"slug":64,"name":65,"__typename":66},"company-news","Company News","Taxonomy_topic","PostToTaxonomy_topicConnectionEdge",{"isPrimary":69,"node":70,"__typename":67},false,{"slug":71,"name":72,"__typename":66},"science","Science",[74,77],{"id":75,"name":65,"uri":76,"__typename":66},"dGVybTo4NTUz","\u002Ftopics\u002Fcompany-news\u002F",{"id":78,"name":72,"uri":79,"__typename":66},"dGVybTo4NjEx","\u002Ftopics\u002Fscience\u002F","PostToTaxonomy_topicConnection",{"nodes":82,"__typename":88},[83],{"id":84,"name":85,"uri":86,"__typename":87},"dGVybTo4ODMy","AI","\u002Ftags\u002Fai\u002F","Taxonomy_tag","PostToTaxonomy_tagConnection",{"edges":90,"nodes":97,"__typename":99},[91],{"isPrimary":62,"node":92,"__typename":96},{"slug":93,"name":94,"__typename":95},"biovia","BIOVIA","Taxonomy_brand","PostToTaxonomy_brandConnectionEdge",[98],{"name":94,"slug":93,"__typename":95},"PostToTaxonomy_brandConnection",{"nodes":101,"__typename":102},[],"PostToTaxonomy_keywordConnection",{"title":104,"metaDesc":105,"opengraphAuthor":106,"opengraphDescription":105,"opengraphTitle":20,"opengraphUrl":107,"opengraphSiteName":108,"opengraphPublishedTime":109,"opengraphModifiedTime":110,"twitterTitle":106,"twitterDescription":106,"readingTime":111,"metaRobotsNoindex":112,"__typename":113},"Agentic AI Meets the CMC Dossier: Why Trust Starts with the Data - Dassault Systèmes blog","Discover how AI-assisted CMC dossier authoring with MARIE improves traceability, data integrity, and regulatory compliance while keeping scientists in control.","","https:\u002F\u002Fblog-frontoffice-contrib-prd.itvpc.3ds.com\u002Fbrands\u002Fbiovia\u002Fagentic-ai-meets-the-cmc-dossier-why-trust-starts-with-the-data\u002F","Dassault Systèmes blog","2026-10-20T15:48:39+00:00","2026-10-20T20:43:50+00:00",6,"index","PostTypeSEO","Post","RootQueryToPostConnection",{},{},1792532622470]