LifeSciencesAIAcademy

Track 13Role-Based CapstoneLocked by prerequisiteOptional

Role-Based Certification & Competency

Bring every competency in the curriculum together in a single role-based end-to-end scenario, and demonstrate that the learner can carry an AI-assisted task from first consideration to closed record.

5 lessons · 6 frameworks · 5–6 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 03 — Approved AI Systems
Track 04 — Data Privacy & Confidentiality
Track 05 — Risk Assessment & Risk Recognition
Track 06 — Context of Use
Track 07 — Human Accountability & Oversight
Track 10 — Documentation & Audit Trails
Track 12 — AI Incident Reporting & Response

Orientation

Why this matters

Competency in twelve separate areas is not the same as competency in the work. The capstone exists because the failures happen at the joins — between context of use and prompting, between review and documentation, between suspicion and report.

What you will be able to do (5)

Apply the whole curriculum to a realistic task in your own role
Exercise decision authority and know its boundaries
Demonstrate all five behaviours in a single connected workflow
Produce a defensible record of an AI-assisted task from start to finish
Maintain competency as regulation, policy and tooling change

Aligned with (6)

EU AI Act — human oversight and role obligationsFDA — credibility assessment and human review expectationsICH Q9(R1) and Q10 — risk management and quality systemEU GMP Annex 11 and draft Annex 22 — computerised systems and AI21 CFR Part 11 — electronic records and signaturesISO/IEC 42001 — AI management system

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

EU AI Act — human oversight and role obligations

Binding lawEuropean Union

Regulation (EU) 2024/1689 — Artificial Intelligence Act ↗

Relevant provisions: Articles 14 and 26 — human oversight and deployer obligations
Status and date: Official Journal, 12 July 2024. Entered into force 1 August 2024; phased application through 2 August 2027.
Why it maps: Connects the lesson to the Act's conditional duties while preserving classification, role and application-date limits.
Applicability limit: Specific duties depend on system classification, actor role, territorial scope and the applicable date. No duty should be extended beyond those conditions.

Primary source last verified 2026-08-24

FDA — credibility assessment and human review expectations

Draft regulatory guidanceUnited States

Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products ↗

Relevant provisions: Seven-step risk-based credibility assessment framework
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

ICH Q9(R1) and Q10 — risk management and quality system

Harmonised guidelineICH regions; implemented through regional frameworks

ICH Q9(R1) — Quality Risk Management ↗

Relevant provisions: Sections 4–6 and Annexes I–II
Status and date: Step 4, 18 January 2023. Implementation depends on the relevant regional authority and regulated activity.
Why it maps: Supports the track's stated mapping to ICH Q9(R1) and Q10 — risk management and quality system without transferring duties beyond the source's scope.
Applicability limit: Supplies quality-risk principles. It does not independently classify an AI system or prescribe one universal control set.

Primary source last verified 2026-08-24

EU GMP Annex 11 and draft Annex 22 — computerised systems and AI

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 and draft Annex 22 — computerised systems and AI 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

Draft regulatory guidanceEuropean Union GMP

Proposed EudraLex Volume 4, Annex 22 — Artificial Intelligence ↗

Relevant provisions: Draft lifecycle, data, model performance, change and human-oversight expectations
Status and date: Stakeholder consultation opened July 2025. Draft consultation text; not effective as of 24 August 2026.
Why it maps: Included to teach prospective change control; the track must preserve its draft, non-effective status.
Applicability limit: Used only as a prospective signal. It must not be presented as a current binding GMP requirement unless and until adopted and applicable.

Primary source last verified 2026-08-24

21 CFR Part 11 — electronic records and signatures

Binding lawUnited States

21 CFR Part 11 — Electronic Records; Electronic Signatures ↗

Relevant provisions: §§ 11.10, 11.30, 11.50, 11.70 and 11.100–11.300
Status and date: Current electronic Code of Federal Regulations. Applies when predicate-rule records are maintained or submitted electronically and Part 11 scope is met.
Why it maps: Supports the track's stated mapping to 21 CFR Part 11 — electronic records and signatures without transferring duties beyond the source's scope.
Applicability limit: Part 11 does not make every electronic output a regulated record. Predicate rules and record use determine applicability.

Primary source last verified 2026-08-24

ISO/IEC 42001 — AI management system

Consensus standardInternational consensus standard

ISO/IEC 42001:2023 — Artificial intelligence management system ↗

Relevant provisions: Clauses 4–10 and Annex A controls
Status and date: December 2023. Voluntary unless adopted by contract, policy, certification scheme or applicable authority.
Why it maps: Supplies a recognised management or assurance practice; it is identified as non-binding unless separately adopted.
Applicability limit: Specifies requirements for an AI management system. Use of the standard does not itself establish regulatory compliance.

Primary source last verified 2026-08-24

Full source register and editorial method →

Credential

Certified Life Sciences AI Practitioner — [Role]

Duration

5–6 hours

Audience

Learners who have completed the tracks required for their role
All ten role pathways, with the scenario adapted to each
Anyone seeking the full practitioner certification

Prerequisites

Track 01
Track 02
Track 03
Track 04
Track 05
Track 06
Track 07
Track 10
Track 12

Behaviours practised (5)

UnderstandApplyVerifyDocumentEscalate

You are asked to use an approved AI assistant on a real task in your area. Between the request and the closed record sit thirteen decisions: whether the use is permitted, what data may go in, what the prompt must constrain, what you verify, what you record, what you escalate, and what you do when something looks wrong. The capstone walks all thirteen.

View badge requirements (8)

Requirements for this credential

Complete every track required for your role pathway and earn its badge
Complete all five capstone lessons and their knowledge checks
Achieve at least 80% across the final badge assessment
Answer every safety-critical question correctly
Produce evidence at all thirteen capstone steps
Halt and escalate at every stop point rather than continuing
Demonstrate all five behaviours with distinct evidence
Submit a competency maintenance plan with renewal and update triggers

Lessons (5)

Integrated capstone

End-to-end role-based scenario

The entitled capstone contains 13 assessed steps that bring the pathway competencies together in one end-to-end scenario.

Credential assessment

Certified Life Sciences AI Practitioner — [Role]

Governing sequence and authority
Ordering workflow steps and match a control to a riskSafety-critical
Order the governing sequence for an AI-assisted task and identify which decisions exceed role authority.
Stop-point handling
Choose the correct escalation pathSafety-critical
Select the correct action at four stop points in the end-to-end scenario.
Behaviour evidence
Select all that applySafety-critical
Identify the evidence appropriate to each of the five behaviours.
Capstone — thirteen-step end-to-end scenario
Practical capstone
Carry a role-adapted task through all thirteen steps and submit the assembled record.