LifeSciencesAIAcademy
Track 11Compliance InfrastructureLocked by prerequisiteOptional

Inspection Readiness

Prepare learners to explain, evidence and defend their organisation's use of AI in a regulatory inspection or audit, accurately and without overstatement.

5 lessons · 4 frameworks · 3–4 hours · 0/5 complete · 0/5 exercises recorded

Locked by prerequisite

This track opens once its prerequisites are complete. Prerequisites are sequenced deliberately: each one supplies a competency this track assumes you already hold.

  • Track 01 — AI Fundamentals
  • Track 02 — AI Governance & Regulatory Expectations
  • Track 07 — Human Accountability & Oversight
  • Track 10 — Documentation & Audit Trails

Orientation

Why this matters

Inspectors increasingly ask about AI directly. The difference between a manageable question and a finding is usually whether the person answering can describe the control set calmly and produce the evidence.

What you will be able to do (5)

  • Anticipate the questions an inspector is likely to ask about AI use
  • Explain your own AI use accurately and within scope
  • Retrieve the supporting evidence within inspection timeframes
  • Answer without speculation, overstatement or prohibited claims
  • Escalate a question you are not the right person to answer

Aligned with (4)

FDA — inspection expectations for computerised systemsEU GMP Annex 11 — inspection of computerised systemsMHRA — data integrity inspection approachICH E6(R3) — inspection and audit readiness

Maps to published expectations. Competency demonstrated through assessment.

Regulatory alignment indicates that curriculum topics map to published regulatory expectations. It does not constitute agency approval, certification, legal advice or a determination of organizational compliance.

View source evidence, status and applicability

FDA — inspection expectations for computerised systems

Draft regulatory guidanceUnited States
Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products ↗
Relevant provisions
Risk-based credibility assessment framework and context-of-use analysis
Status and date
January 2025. Draft; not for implementation and non-binding.
Why it maps
Maps the lesson to FDA's context-of-use and credibility concepts without treating draft recommendations as law.
Applicability limit
Applies to AI used to produce information or data supporting FDA regulatory decisions for drugs and biological products. It is not a general AI-use mandate.

Primary source last verified 2026-08-24

EU GMP Annex 11 — inspection of computerised systems

GMP requirementEuropean Union GMP
EudraLex Volume 4, Annex 11 — Computerised Systems ↗
Relevant provisions
Sections 1, 4, 7–9, 11–13 and 16–17
Status and date
Revision January 2011. Current Annex 11; came into operation 30 June 2011.
Why it maps
Supports the track's stated mapping to EU GMP Annex 11 — inspection of computerised systems without transferring duties beyond the source's scope.
Applicability limit
Applies to computerised systems used as part of GMP-regulated activities. Applicability follows the regulated process and intended use.

Primary source last verified 2026-08-24

MHRA — data integrity inspection approach

Regulatory guidanceUnited Kingdom GxP
MHRA GxP Data Integrity Guidance and Definitions ↗
Relevant provisions
Data governance and ALCOA+ expectations across the data lifecycle
Status and date
March 2018; page updated September 2021. Current MHRA resource; OECD guidance takes precedence for UK GLP as stated by MHRA.
Why it maps
Supports the track's stated mapping to MHRA — data integrity inspection approach without transferring duties beyond the source's scope.
Applicability limit
Used for data-governance and inspection expectations. Its scope and MHRA's stated GLP qualification must be preserved.

Primary source last verified 2026-08-24

ICH E6(R3) — inspection and audit readiness

Harmonised guidelineICH regions; implemented through regional frameworks
ICH E6(R3) — Good Clinical Practice ↗
Relevant provisions
Principles and Annex 1 provisions on roles, data governance, records and oversight
Status and date
Principles and Annex 1, Step 4, 6 January 2025. Implementation depends on regional adoption and the clinical-trial activity.
Why it maps
Supports the track's stated mapping to ICH E6(R3) — inspection and audit readiness without transferring duties beyond the source's scope.
Applicability limit
Applies to clinical trials within its scope. It should not be transferred to manufacturing or other domains without an independent basis.

Primary source last verified 2026-08-24

Full source register and editorial method →

Credential

AI Inspection Readiness Badge

Duration

3–4 hours

Audience

  • Anyone who may be interviewed during an inspection or audit
  • Quality, regulatory and manufacturing professionals
  • System owners and process owners

Prerequisites

  • Track 01
  • Track 02
  • Track 07
  • Track 10

Behaviours practised (3)

DocumentVerifyEscalate
An inspector asks a manufacturing supervisor, 'Do you use artificial intelligence in this process?' The honest answer is yes, in one narrow way, with defined controls. The unprepared answer is a hesitation followed by 'I'd have to check', and the inspection widens.

Badge requirements (5)

  1. Complete all five lessons and their knowledge checks
  2. Achieve at least 80% across the final badge assessment
  3. Answer every safety-critical question correctly
  4. Use only approved regulatory language in every prepared statement
  5. Build an evidence map with measured retrieval times

Lessons (5)

Final badge assessment

AI Inspection Readiness Badge

  • Inspection question response

    Scenario classificationSafety-critical

    Select the correct response to eight inspector questions, four outside your role.

  • Regulatory language

    Identify the unsupported statementSafety-critical

    Identify prohibited and inaccurate claims across six prepared statements.

  • Evidence gap and correction escalation

    Choose the correct escalation pathSafety-critical

    Select the correct action for four situations involving missing or incorrect information.

  • Practical exercise — evidence map

    Practical exercise

    Build an evidence map for one AI use with measured retrieval times and identified gaps.

Next recommended track

Track 12 — AI Incident Reporting & Response
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