Pharmaceutical companies have enormous, document- and data-heavy workflows that AI can accelerate — and an equally large regulatory apparatus that shapes how. The opportunity is real across R&D, safety, and operations, provided AI fits inside GxP and Part 11. Here’s how, and how dgm implements it. (dgm implements osFoundry, a separate company’s platform — we are not osFoundry; regulatory, quality, and safety determinations stay with your team.)

What AI actually does for pharma

The honest framing: AI is an assistive accelerant across pharma’s document- and data-heavy work — drafting, case processing, quality, and research — while qualified professionals validate output and retain accountability. In regulated processes, AI is a controlled, validated system, not an autonomous decider.

High-value use cases

  • Regulatory and clinical document drafting — first drafts of clinical study reports and submission sections (human-finalized).
  • Pharmacovigilance case processing — draft case narratives, intake, coding, and duplicate checks.
  • Manufacturing quality — deviation detection, automated inspection, batch-record review.
  • Literature review and summarization — synthesizing large bodies of research.

(Treat any specific time-savings figures you see as case-study claims, not industry facts.)

The compliance reality: GxP and 21 CFR Part 11

This is what makes pharma AI different:

  • GxP. GLP (nonclinical), GCP (clinical), and CGMP (manufacturing) govern regulated processes. An AI tool inserted into a GxP process inherits those obligations — it must be validated and documented like any computerized system.
  • 21 CFR Part 11. Electronic records and signatures require validation, secure time-stamped audit trails, and controls. “Validation” of an AI tool means documented evidence it performs consistently as intended — in practice, Computer System Validation (commonly via GAMP 5 industry practice).
  • Assistive with verification. For submissions and safety, AI stays assistive; humans verify output against source evidence and remain accountable. (Even the FDA’s own internal AI tool surfaced hallucination concerns, reinforcing human oversight.)

dgm builds with validation and controls in mind; regulatory, quality, and safety determinations stay with your team.

How to start

Start where AI is assistive and well-bounded — literature review, draft document generation, or quality support — with validation and human verification built in. Keep humans verifying any safety- or submission-critical output. Prove the value, then expand. dgm’s assessment finds the right starting point.

How dgm helps

dgm implements osFoundry and other AI for US pharmaceutical companies — with validation, audit, and human-verification expectations in mind, focused on assistive use cases. Pricing is fixed and public: a $399 assessment and $3,999/month implementation, with no per-seat fees. If you’d rather explore the platform first, go straight to osFoundry; if you want pharma AI done right, that’s where dgm comes in.