Pharmaceutical companies cut CTD authoring time 60–65% with Accenture's AWS generative AI solution

A pharmaceutical companies (unnamed, via Accenture) deployed Large Language Models & Generative AI for Clinical Trials & Research in Pharmaceutical & Life Science. As reported by aws.amazon.com: 60–65% ctd authoring time reduction.

Maintained by Peter Korpak, Lead EditorHow evidence is checked
60–65%CTD Authoring Time Reduction
Up to 100,000 hoursAnnual CTD Authoring Hours (typical large pharma)

Source-reported figures (cited source: aws.amazon.com)

What the pharmaceutical companies (unnamed, via Accenture) was trying to fix

Pharmaceutical companies face an extraordinarily labor-intensive process of manually creating Common Technical Documents (CTDs) for FDA submissions, requiring up to 100,000 hours per year for a typical large pharma company. The CTD contains over 100 highly detailed technical reports compiled during drug research and testing, making the process both time-consuming and prone to errors.

What the pharmaceutical companies (unnamed, via Accenture) deployed

Accenture built a generative AI-based regulatory document authoring solution on AWS that automatically extracts key data from testing reports and generates CTDs in the required format using Amazon SageMaker JumpStart with AI21 Jurassic Jumbo Instruct and AI21 Summarize models. The system is built on AWS Well-Architected principles with encryption and auditability controls, and allows users to review and edit computer-generated documents before submission.

Results

Early testing demonstrated a 60–65% reduction in the time required for authoring CTDs, exceeding preliminary estimates of 40–45% reduction. The solution accelerates new drug approvals by compressing the document compilation process while maintaining compliance with FDA format requirements.

Key Takeaways

  • Generative AI can eliminate the majority of manual effort in regulatory document creation, potentially saving tens of thousands of hours annually per large pharma company
  • A human-in-the-loop review layer is essential for regulated industries, even with high automation fidelity
  • AWS Well-Architected principles (security, auditability, encryption) are table-stakes for handling sensitive pharma submission data

Evidence for the pharmaceutical companies (unnamed, via Accenture)'s Clinical Trials & Research deployment

Reported outcome metrics
2 cited below
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Limitation: The cited source does not identify the company.

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Pharmaceutical companies (unnamed, via Accenture)

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