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Pharmaceuticals & R&D

Pharmaceutical and life-science R&D organisations apply AI across discovery, trials, safety and manufacturing, in an environment defined by validation discipline and regulatory scrutiny. Gamut gives R&D, quality, safety and regulatory-affairs teams a structured way to govern these models and produce the documented, traceable assurance the sector expects.

AI systems typically in scope

Section titled “AI systems typically in scope”
  • Drug-discovery and target-identification models.
  • Clinical-trial design, recruitment and monitoring AI.
  • Pharmacovigilance and adverse-event detection.
  • Manufacturing quality and process-optimisation models.
  • Research and regulatory copilots over scientific and patient data.

Governance drivers

Section titled “Governance drivers”
  • Validation discipline. A culture of documented validation that maps naturally onto control testing.
  • Patient safety and pharmacovigilance. Demonstrable oversight of safety-relevant models.
  • Data sensitivity. Trial and patient data require strict handling.
  • ISO/IEC 42001 and impact assessment. Management-system rigour and documented impact on patients and subjects.

Use cases

Section titled “Use cases”

Validate a pharmacovigilance model

Section titled “Validate a pharmacovigilance model”

How Gamut solves it: register and model-card the model, tier it via intake, route to GTSAF and ISO/IEC 42001, and evidence validation, monitoring and human oversight with control tests that record operating effectiveness.

Govern a clinical-trial AI with an impact assessment

Section titled “Govern a clinical-trial AI with an impact assessment”

How Gamut solves it: route to ISO/IEC 42005 to assess impact on trial subjects, with intake’s affected-persons and special-category-data signals driving the risk tier.

Keep research copilots inside policy

Section titled “Keep research copilots inside policy”

How Gamut solves it: for tool-using or agentic research assistants, govern them through Agentic CISO and Gateway so they never reach data or tools outside policy, with Claw holding no credentials.

Quick start

Section titled “Quick start”
  1. Register the system in AI System Records with a model card.
  2. Run intake, flag special-category data and oversight, confirm the tier.
  3. Route to GTSAF, ISO/IEC 42001 and ISO/IEC 42005.
  4. Evidence validation, safety and monitoring in the Evidence Tracker and Testing Centre.
  5. Track gaps on the Remediation Roadmap.
  6. Produce assurance for quality, safety and regulatory affairs from reporting.

Frameworks that apply

Section titled “Frameworks that apply”

GTSAF, ISO/IEC 42001, ISO/IEC 42005, EU AI Act and NIST AI RMF.

Next

Section titled “Next”