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.

Badge requirements (8)

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

Lessons (5)

Step 9 · Role-based capstone

End-to-end role-based scenario

You receive a request to use an approved AI system on a real task in your own area. The task is adapted to your role pathway. You will carry it from the request to a closed, defensible record, producing evidence at every step and halting where a stop point requires it.

0/13 steps recorded

  1. 01

    Receive and characterise the request

    Understand

    State the task, the decision it supports and the consequence if the output were wrong.

    Draws on Track 01 · Track 05

    0/60 characters minimum

  2. 02

    Confirm the system is approved for this use

    Apply

    Identify the system, its approval status and its documented context of use. Halt if the task falls outside it.

    Draws on Track 03 · Track 06

    0/60 characters minimum

  3. 03

    Classify the risk of the use

    Understand

    Assess model influence and decision consequence, and state the resulting risk level.

    Draws on Track 05 · Track 09

    0/60 characters minimum

  4. 04

    Determine what data may be supplied

    Apply

    Identify the data required, classify its sensitivity and confirm it may lawfully and contractually be supplied. Halt if it may not.

    Draws on Track 04

    0/60 characters minimum

  5. 05

    Construct the controlled prompt

    Apply

    Write the prompt with role, source, task, constraints and output format, including a licensed way for the model to decline.

    Draws on Track 08

    0/60 characters minimum

  6. 06

    Capture the raw output and system identity

    Document

    Retain the output exactly as received, with the system and model version and the timestamp.

    Draws on Track 08 · Track 10

    0/60 characters minimum

  7. 07

    Verify every claim against source

    Verify

    Trace each value, citation and conclusion to authoritative source. Remove what cannot be verified. Halt if the conclusion depends on it.

    Draws on Track 07 · Track 08

    0/60 characters minimum

  8. 08

    Apply your own judgement to the conclusion

    Verify

    Decide whether you accept the conclusion, and record the reasoning — including any override of what the system produced.

    Draws on Track 07

    0/60 characters minimum

  9. 09

    Assemble the contribution and verification record

    Document

    Record which content the system produced, what you verified against what, and every correction with its reason.

    Draws on Track 10

    0/60 characters minimum

  10. 10

    Route for review and approval

    Document

    Route the work through the correct authority chain, confirming that preparation, verification and approval are appropriately separated.

    Draws on Track 07 · Track 10

    0/60 characters minimum

  11. 11

    Raise any escalation

    Escalate

    Escalate anything unresolved — an undocumented limitation, a near miss, a context question — through the named channel, or state a reasoned judgement that none arose.

    Draws on Track 12

    0/60 characters minimum

  12. 12

    Prepare the inspection answer

    Document

    State, in approved regulatory language, what you did and what evidence supports it, marking the boundary of your role.

    Draws on Track 11

    0/60 characters minimum

  13. 13

    Close the record and set the maintenance obligation

    Document

    Confirm retention, retrievability and the curriculum version, and record the competency maintenance triggers this task revealed.

    Draws on Track 10 · Track 13

    0/60 characters minimum

Passing criteria

Evidence produced at all thirteen steps, every stop point handled by halting and escalating rather than continuing, all five behaviours demonstrated with distinct evidence, and the assembled record traceable end to end.

Remediation

Any step without evidence is remediated by completing the source track's practical exercise and rerunning that step. A stop point handled incorrectly requires the full scenario to be rerun with a second task.

Final badge 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.

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