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Regulations/Good AI Practice/AI Governance
AI Governance · Good AI Practice

AI Governance for Good AI Practice.

This page focuses on AI governance implications inside regulated work. It shows where AI changes evidence needs while keeping quality, regulatory, data, supplier, and human accountability controls in view.

Source basis: Guiding principles for Good AI Practice in drug development and related lifecycle guidanceUse: evidence-readinessBoundary: not legal advice
Good AI Practice TRACE FDA/EMA GOOD AI PREMA/HMA AI LIFECFDA AI DRUG DEVEGMLP MEDICAL-DEV
/ AI governance

AI changes the evidence pattern, not the need for control.

Good AI Practice
Control 01

Context of use

Document where the AI output enters a scientific, clinical, quality, or regulatory decision.

Control 02

Data provenance

Data source, representativeness, bias, and limitations should be reviewable.

Control 03

Model evidence

Validation and performance should match the use context and risk.

Control 04

Human accountability

A named human or function remains responsible for decisions and escalation.

/ Adjacent controls

AI governance must connect to existing regulated systems.

not isolated
Evidence 01

AI use-case statement

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.

Evidence 02

Context-of-use record

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.

Evidence 03

Data provenance file

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.

Evidence 04

Bias/representativeness review

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.

Evidence 05

Model development record

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.

Evidence 06

Validation protocol and report

Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.

Source anchors

Current public sources for Good AI Practice.

official first

These links are the public source anchors for this workspace. Interpretation, checklists, and future assets should point back here before being reused outside iFeed.

Official FDA page

FDA guiding principles for Good AI Practice in drug development

2026-01-14 · FDA page for common Good AI Practice principles in drug development.

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Official EMA news

EMA and FDA common AI principles news

2026-01-14 · EU-facing publication context for the common principles.

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Official EMA/HMA reflection paper

EMA/HMA AI in medicinal product lifecycle

2024-09-30 · Broader medicinal-product lifecycle reflection layer for AI use and governance.

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Official regulator principles

FDA/Health Canada/MHRA GMLP principles

2021-10-27 · Ten guiding principles for Good Machine Learning Practice for medical device development.

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