Worked Example  ·  Trinzo AI Operating System

Regulatory Submission Drafting

Where every sentence has to trace to an approved source

Status: illustrative

This is a worked example, not an account of a named client engagement. It shows how the AI and LLM Implementation Playbook applies to a representative workflow. All figures are illustrative and are not measured outcomes. Any organisation applying this method must generate its own evidence for its own workflow, sources, configuration and people.

Submission writing is the case where the failure mode named in the third whitepaper is most exposed. The output is prose, the reader is a regulator, and the characteristic defect of a drafting model is an unsupported claim that reads exactly like a supported one. There is no build that fails, no test that goes red. The only thing standing between a fluent invention and a regulatory filing is whether somebody traced the sentence back to a source.

That makes the verification design the whole engagement. Everything else is arrangement.

Section 1The example at a glance

WorkflowDrafting defined sections of a regulatory submission from approved source documents and study reports
Front Door dispositionFD2 Controlled Regulated Workflow.
Regulatory relationshipR1 supports regulated work. Regulatory positioning and strategy remain unassisted.
OverlaysOverlay C (US pharmaceuticals and biological products), with Overlay E (clinical development and regulatory evidence) where clinical data is drawn on.
Amplification intentExtend regulatory writer capacity for argument construction by reducing time spent assembling and cross-referencing source content.
Configuration baselineModel, prompt and retrieval index versions are recorded at evaluation. A change to any of them re-opens evaluation at a defined scope.
Pilot boundaryTwo section types, one submission, one therapeutic area, three named writers.

Section 2Front Door and regulatory routing

Routing returned R1 without redesign, but with a boundary that had to be drawn carefully. Drafting a section from approved sources supports regulated work. Deciding what position to take with a regulator, which arguments to make and which weaknesses to address directly, is regulatory reasoning and stays unassisted. The distinction is not always obvious in the text itself, because a drafting instruction can smuggle a positioning decision into it.

The design handles this by requiring the writer to set the argument structure before any drafting occurs. The framing gate is not a formality. It is where the regulatory judgement actually happens, and if it is skipped the route is no longer R1.

Section 3Material-step map

#Material activityTask classAllocationConsequence
1Select and confirm approved source documents and versionsRetrieveHuman-ledTier 2
2Define section purpose, argument structure and prohibited positionsHuman judgementUnassisted gateTier 3
3Retrieve supporting content and locate relevant passagesRetrieveCollaborativeTier 2
4Extract data points, results and study parametersExtractCollaborativeTier 2
5Tabulate and convert units, populations and derived valuesTransformCollaborativeTier 3
6Draft section narrative within the approved structureDraftCollaborativeTier 3
7Trace every claim to an approved sourceHuman judgementUnassisted gateTier 3
8Verify every numerical value and derivationHuman judgementUnassisted gateTier 3
9Approve section for submission assemblyHuman judgementUnassisted gateTier 3

Consequence tiers are assessed before crediting any control. Tier 3 means an unchallenged error could affect patient safety, product quality, release or a regulatory position.

Section 4Substantive human gates

GatePositionRequired human contributionArtefact
Source gateBefore retrievalWriter selects and confirms the approved source and version set, and records where the source estate is silent on a point the section must address.Approved source list and corpus-silence note.
Framing gateBefore draftingWriter defines the argument structure, the positions that may be taken and those that may not. This is the regulatory reasoning step and cannot be delegated.Argument structure and prohibited-position statement.
Claim-trace gateAfter draftingWriter decomposes the draft into individual claims and traces each to a specific approved source passage. Claims that cannot be traced are removed, not softened.Claim-by-claim trace with source and page reference.
Numerical fidelity gateAfter draftingWriter recomputes every derived value and checks every unit, population, denominator and rounding decision against the source.Recomputation record and correction log.
Approval gateBefore submission assemblyWriter confirms the section states the intended position, addresses known weaknesses and contains no content beyond the traced set.Approval decision, limitations and residual-issue note.

A gate is substantive only when passing it requires the person to produce something the machine did not. Approval alone is not a gate.

Section 5Prohibited use

The configured workflow must not:

  • Determine regulatory position, strategy or how a weakness is addressed.
  • Produce a claim that is not traceable to an approved source.
  • Generate, estimate or infer a numerical value not present in the source.
  • Draft in a section type or therapeutic area outside the pilot boundary.
  • Substitute a summary of a source for the source itself during tracing.

Section 6Evaluation approach

The evaluation described here produces the evidence that feeds validation for intended use. It does not replace it.

The evaluation weighted Draft and Transform heavily, because those carry the Tier 3 consequence. Draft was assessed by claim decomposition against seeded unsupported claims, contradictions between sources, and cases where the correct behaviour was to report that the source estate did not support the point. Transform was assessed by recomputation, with seeded unit errors, denominator substitutions and rounding drift.

The affordability question in Part 3 mattered more here than in most workflows. Claim tracing is slow. If the ratio of verification effort to drafting effort exceeds one, the workflow costs more than writing the section by hand, whatever the drafting time saved. That measure was treated as a pass condition rather than a metric.

The pilot boundary was written as a context of use in the sense used in the FDA draft guidance of January 2025 on AI supporting regulatory decision-making: the specific question the workflow addresses, the section types in scope, and the influence the output has on the eventual regulatory decision. Model risk follows from that influence and the consequence of the decision, which is why the same configuration would need re-assessment for a section type carrying different weight.

Section 7Illustrative evaluation results

MeasureUnassisted baselineAI-assisted result
Evaluation set and period18 representative sections plus 21 constructed boundary and failure casesSame set, ten-week window
Median writer effort per section11.5 hours unassisted7.4 hours AI-assisted
Verification Effort RatioNot applicable0.71
Seeded unsupported claims detected at claim-trace gateNot applicable18 of 18
Seeded numerical errors detectedNot applicable11 of 12
Corpus-silence cases correctly reported as unsupportedNot applicable7 of 9
Untraceable claims removed rather than rewordedNot applicable23
Positioning decisions originating outside the framing gateTarget: noneNone observed

These figures are constructed to illustrate the shape of a defensible result. They are not measured outcomes and must not be cited as evidence of performance.

Section 8Capability and authorisation

RoleMinimum levelRequired capability
Writers operating the workflowLevel 2Prepare approved inputs, operate the configured workflow, recognise stop conditions.
Gate operatorsLevel 3Draft and Transform verification competencies, claim decomposition and recomputation, within a Tier 3 ceiling.
Regulatory approverLevel 4Challenge the evidence base, restrict scope, suspend or retire the workflow.
ManagersRole dutyProtect tracing time. This is the control most likely to erode first under submission deadlines.

Section 9Disposition

Progression decision

Acceptable for a bounded pilot.

Two results prevented a stronger disposition. One seeded numerical error was not detected, which for Tier 3 content is a material finding rather than a rounding of the score. And two of nine corpus-silence cases produced content where the correct output was an explicit statement that the sources did not support the point. Both were accepted as open residuals by the regulatory approver, with defined monitoring and a re-test condition, rather than averaged into an overall pass.

The measure that decided this was the Verification Effort Ratio, not the time saving. A workflow that halves drafting time and doubles review time has moved effort rather than reduced it, and in submission work it has moved effort from a step people are good at to one they are worse at. The ratio is the only number in the results table that would have stopped the pilot on its own.

Records and retention, supplier and platform qualification, audit trail and signature controls, and the linkage to corrective action are all in scope for the method and are handled in the playbook itself. They are deliberately out of scope here so this remains readable in ten minutes.

The method described here is set out in full in the Trinzo AI and LLM Implementation Playbook. The reasoning behind it is developed across the three whitepapers in The AI Capability Series, particularly the third, which deals with verification and gate design.

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