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FlashAnalysis · Clinical Data → Analysis → Submission

From Clinical Data to Analysis and Submission.

FlashAnalysis automates downstream clinical programming and standards workflows while enforcing deterministic execution, independent QC, and traceability from every output back to the source record.

Request a DemoSee the workflow
Illustration of the Clindaddy character at a console showing raw clinical data flowing through SDTM and ADaM to results, with a separate QC rail converging on a match and lineage traced back to source rows.
Illustration. One dataset path from raw data to results, a QC run kept deliberately separate, and every value traceable to the row it came from.

Workflow

What FlashAnalysis does, in order.

Collected data enters at the top. Submission artifacts come out at the bottom, having passed through standards transformation, analysis, and two independent checks.

  1. Clinical Data

    Collected data admitted under a provenance policy.

  2. Provenance Gate

    Real and synthetic data handled under explicit policy.

  3. SDTM

    Deterministic transformation to CDISC SDTM.

  4. ADaM

    Analysis-ready datasets and derivations.

  5. TLFs

    Tables, listings, and figures with source traceability.

  6. Independent QC

    Independent re-implementation and comparison.

  7. Submission Metadata

    Define-XML, aCRF, cSDRG, ADRG, eCTD-lite package.

  8. Audit & Lineage

    Append-only audit log; outputs traced to source.

Capabilities

What it produces.

Transform clinical data into standards, analysis-ready datasets, clinical outputs, QC evidence, and submission artifacts.
  • Data intake
  • Provenance governance
  • SDTM
  • ADaM
  • TLFs
  • Independent QC
  • Cross-artifact QC
  • Define-XML
  • aCRF
  • cSDRG
  • ADRG
  • eCTD-lite package
  • Standards governance
  • Reconciliation
  • Audit trail
  • Data lineage

Data intake

Enforces provenance policies that govern how real and synthetic data may be used, so the origin of a dataset is a first-class property rather than a convention.

SDTM

Transforms clinical data into CDISC SDTM datasets using deterministic processing rather than model-generated values.

ADaM

Creates analysis-ready datasets and the derivations behind them, with each derivation tied to its specification.

TLF generation

Generates tables, listings, and figures with traceability back to the source records that produced each number.

Independent QC

Re-implements the computation independently of production, so QC does not simply reproduce the same implementation and agree with the same defect.

Cross-artifact QC

Checks consistency between datasets, specifications, and outputs — catching the mismatches that per-artifact review misses.

Submission metadata

Generates Define-XML, aCRF, cSDRG, ADRG, and an eCTD-lite package for the submission.

Reconciliation

Compares CRO and vendor deliverables against sponsor outputs and surfaces the differences.

Auditability

Provides append-only audit logging and lineage from any output back to the source records behind it.

Independent QC

A second run of the same code is not a second opinion.

If QC re-executes production, it agrees with production by construction — including when production is wrong. FlashAnalysis separates the two computations on purpose, then compares the results and hands the differences to a reviewer.

Source data

Collected clinical data

Production

Executes the approved specification

Independent QC

Re-implements the computation

Compare

Differences surfaced, never silently reconciled

Review

A person resolves what the comparison found

Production executes the approved specification. Independent QC re-implements the computation from the same specification by a different route. The comparison between the two results is the evidence — not the fact that both runs finished.

Cross-artifact QC extends that check beyond a single output: datasets, specifications, and the documents that describe them are compared against each other, which catches the inconsistencies that per-artifact review cannot see.

Differences are surfaced for review. They are never reconciled silently, and nothing is released on the assumption that a discrepancy was benign.

Demonstration

See the workflow, step by step.

Evidence is more useful than adjectives. Walk the pipeline each product runs, and the artifact it produces at every stage.

FlashAnalysis · Standards pipeline · Study SYN-014

Illustrative

VS · Vital signs

USUBJIDVSTESTCDVSORRESVSSTRESN
1001SYSBP128128
1001DIABP8282
1002SYSBP134134
1002DIABP8686

Load data

Provenance record attached to each delivered dataset.

Illustrative walkthrough. Datasets, tables, and figures shown are synthetic.

Where it is today

A tested platform with a clear path toward productization.

The current FlashAnalysis codebase is covered by approximately 2,500 passing tests, alongside a policy-driven approach to governing real versus synthetic data.

Passing tests describe code health. They are not evidence of commercial traction, and we do not present them as such.

Next step

See FlashAnalysis against your own protocol or dataset.

Bring a study and we will walk through what the platform produces — and where a human still has to decide.

Request a DemoTalk to Clindaddy