Top US Pharma Regulatory Operations — AI Regulatory Drafting Copilot: 311 hours per major filing collapses into a citation-grounded first draft
Client · Regulatory Affairs
Top US Pharma Regulatory Operations
ClientTop US Pharma Regulatory Operations
SectorRegulatory Affairs
IndustryPharmaceutical & Life Sciences
RegionUnited States

AI Regulatory Drafting Copilot: 311 hours per major filing collapses into a citation-grounded first draft

A typical FDA major filing takes 311 hours of regulatory affairs time to prepare. HomoDeus's drafting copilot opens the document vault, recommends a complete draft based on product type, jurisdiction, template, and label changes, and inserts citations and comparables highlighted in yellow for human review.

Designed for US and international pharma regulatory affairs teams. Active pilot conversations under NDA.

Regulatory affairs teams in pharma are small, deeply expert, and impossibly stretched. A major FDA filing routinely consumes hundreds of hours across drafting, citation lookup, template matching, and comparable retrieval. The team that holds the institutional memory of every prior submission is the same team writing the next one from scratch each time. HomoDeus built a regulatory drafting copilot that opens the vault and writes the first draft against the same precedents the team would have pulled by hand.

Outcomes

311 hrstypical FDA major filing prep time (industry baseline)
73%estimated drafting time reduction with the copilot
5 minutesfrom vault open to first AI-drafted document
37+regulatory template types supported across jurisdictions

A 3-person regulatory team that was writing every filing from a blank page now works a highlighted, citation-grounded draft. The expertise is reallocated from drafting to judgment.

The problem

Every major filing is a precedent search across years of prior submissions, label changes, and jurisdictional templates. The work is highly templated but not automated. A 3-person regulatory team handling 5 submissions a month can spend the majority of its capacity on the drafting and citation steps that an LLM with the right vault and the right templates could collapse into minutes. The team's expertise is wasted on the rote part.

What we built

HomoDeus built a regulatory drafting copilot that ingests the company's document vault, the relevant jurisdiction templates, and the product label change set, then drafts a complete first-pass submission with comparables and citations inserted as yellow-highlighted, reviewer-friendly annotations. The team works the highlighted draft instead of starting from a blank page. Built for medium and large regulatory operations where the volume justifies the tool. Output is audit-trailed and version-controlled by design, because regulatory work is.

Stack

  • Regulatory document vault ingestion
  • Template + label change matcher
  • Citation and comparable retrieval
  • Yellow-highlight annotation layer
  • Audit-trail and version control

Time to production

Productised copilot, deployable per regulatory operation

Questions a C-suite leader will ask

Can AI draft FDA regulatory submissions?

AI can draft the first pass with citations and comparables already inserted, then the regulatory team works that highlighted draft instead of starting from a blank page. HomoDeus's drafting copilot ingests the document vault, matches templates and label changes, and produces a citation-grounded first draft in around 5 minutes.

How does an AI regulatory copilot differ from a generic LLM?

It is grounded in the company's own document vault and the relevant jurisdiction templates, with citations and comparables annotated for reviewer-grade auditability. Generic LLMs hallucinate citations. This system retrieves them.

Who is HomoDeus's regulatory drafting copilot built for?

Medium and large regulatory operations where the volume of submissions justifies the tool. Small teams with only a few submissions per month often do not have enough volume to justify the learning curve. Production-grade auditability is baked in by design.

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