  Purpose: The introduction of artificial intelligence / machine learning
(AI/ML) products to the regulated fields of pharmaceutical research and
development (R&D) and drug manufacture, and medical devices (MD) and in-vitro
diagnostics (IVD), poses new regulatory problems: a lack of a common
terminology and understanding leads to confusion, delays and product failures.
Validation as a key step in product development, common to each of these
sectors including computerized systems and AI/ML development, offers an
opportune point of comparison for aligning people and processes for
cross-sectoral product development.
  Methods: A comparative approach, built upon workshops and a subsequent
written sequence of exchanges, summarized in a look-up table suitable for
mixed-teams work.
  Results: 1. A bottom-up, definitions led, approach which leads to a
distinction between broad vs narrow validation, and their relationship to
regulatory regimes. 2. Common basis introduction to the primary methodologies
for AI-containing software validation. 3. Pharmaceutical drug development and
MD/IVD specific perspectives on compliant AI software development, as a basis
for collaboration.
  Conclusions: Alignment of the terms and methodologies used in validation of
software products containing artificial intelligence / machine learning (AI/ML)
components across the regulated industries of human health is a vital first
step in streamlining processes and improving workflows.
