Independent analytical verification for biomedical, clinical, and healthcare research
RIQA provides independent analytical verification of analytical outputs across biomedical, clinical, and healthcare analytics domains — ensuring conclusions drawn from data are internally consistent, transparently derived, and independently reproducible and analytically verifiable under defined conditions.
Core assurance principles
01 / Provenance
Data lineage verification
Source, transformation logic, and analytical inputs traced and documented end-to-end.
02 / Methodological Consistency
Statistical & Methodological Assessment
Reported metrics evaluated against the structure of the underlying data.
03 / Reproducibility
Independent Result Reconstruction (IRR)
Results reconstructed from provided data under standardized conditions.
04 / Transparency
Structured QA report
Structured assurance reports in human-readable and machine-readable formats with full provenance.
RIQA applies the same four-phase verification framework across three primary domains.
Domain 01
Preclinical & Biomedical Research
Laboratory, genomic, imaging, and in vivo workflows where quantitative results support biological conclusions.
qPCR · Flow · RNA-seqExplore →
Domain 02
Clinical Research & Trial Analytics
Clinical endpoint analyses verified by a neutral, non-sponsoring party with direct regulatory implications.
Survival · SAP · ITTExplore →
Domain 03
Healthcare Analytics & Quality Assurance
Claims and risk models where implementation gaps carry financial and compliance consequences.
HCC · Claims · ETLExplore →
What an engagement looks like
Typical RIQA engagements
Every engagement follows the same four-phase pipeline. Scope and deliverables are defined upfront before analysis begins.
Biomedical
Pre-publication verification
A research group submits raw qPCR Cq values. RIQA reconstructs fold changes and p-values. A structured assurance report is referenced in the manuscript methods section.
Clinical
Sponsor-side SAP verification
A sponsor submits patient-level data and the SAP ahead of a regulatory or publication submission. RIQA reconstructs endpoints and delivers sensitivity analyses.
Healthcare analytics
Healthcare analytics implementation review
An analytics team submits model documentation before a quality reporting or compliance submission. RIQA verifies whether implemented logic matches the declared specification.
Research funding
NIH grant preliminary data review
A PI submits preliminary data included in a grant application. RIQA verifies that the statistical conclusions are internally consistent and reproducible from the submitted data.
Translational
Biomarker verification review
A translational group submits biomarker panel data. RIQA evaluates endpoint consistency and assay-to-conclusion traceability.
Institutional
External methodological assurance
A core facility engages RIQA as an external QA layer, providing structured reproducibility documentation to support submissions.
Who RIQA serves
Built for organizations where data integrity is non-negotiable
Preclinical & Biomedical
Academic research laboratories
Core facilities and shared instrumentation
Contract research organizations (CROs)
Translational and pre-clinical research groups
Journal authors seeking pre-submission assurance
Clinical Research
Clinical trial sponsors and biotech organizations
Biostatistics teams preparing regulatory submissions
Regulatory affairs and clinical operations groups
NIH grant applicants with preliminary data
Healthcare Analytics
Healthcare analytics vendors and consultancies
CMS contractors and Medicare Advantage plans
Payment integrity and fraud detection teams
Health system analytics and informatics teams
"RIQA is not intended to function as a gatekeeper or decision-maker, but as an enabling layer that strengthens trust, supports peer review, and improves the integrity of data-driven research."
— RIQA Mission Statement · riqassure.com
Ready to verify your research?
Start with a conversation — no commitment required.
View demonstration studies →
Framework documentation
The RIQA Assurance Framework
A four-phase, modular methodology for independent analytical verification and Independent Result Reconstruction (IRR) across biomedical, clinical, and healthcare analytics domains. Every engagement is pre-specified, version-tracked, and independently reproducible and analytically verifiable under defined conditions.
Four-phase pipeline
How every engagement proceeds
The same four phases apply across all three domains. Domain-specific verification procedures are applied within each phase.
Phase 01
Data Provenance & Transformation Review
Evaluates the lineage and transformation pathway from source data to reported outputs. Covers normalization procedures, batch correction documentation, gating strategy definitions, endpoint derivation files, censoring rule implementations, SAP alignment, ETL logic, look-back window specifications, and crosswalk file versioning.
→ provenance-trace.pdf · transformation-log.json
Phase 02
Statistical & Methodological Assessment
Evaluates alignment between the declared analytical methodology and the structure of the underlying data. Each analytical component is assigned to an IRR class within the RIQA taxonomy. An IRR Methodology Declaration is issued specifying the verification standard to be applied in Phase 03.
Results are reconstructed from source data and documented analytical procedures. For exact and near-deterministic methods, numerical reconstruction is performed. A sensitivity analysis is separately performed to evaluate conclusion stability under reasonable alternate assumptions.
→ irr-findings.csv · sensitivity-analysis.json
Phase 04
Structured QA Reporting
Generates structured QA reports including findings registers, integrity scoring summaries, and machine-readable provenance artifacts. SHA-256 hashes of all input files are recorded in the audit trail. Every finding traces to a specific catalog entry.
Correct methodological implementation verified; seed and version documentation required.
Architectural verification
ML pipelines, CMS-HCC models, federated systems
Logic consistency, population construction, and specification-to-implementation alignment.
Anchor standards
Standards alignment
RIQA's provenance requirements are anchored to established community standards. RIQA goes beyond checklist compliance to provide independent quantitative reconstruction.
MIQE 2.0 — Minimum Information for qPCR Experiments
Bustin et al. 2025, Clin Chem 71:634. RIQA-qPCR Livak v1.1 provenance catalog is structured along MIQE 2.0 sections with severity assignments consistent with the essential/desirable distinction.
MIFlowCyt — Minimum Information about a Flow Cytometry Experiment
Lee et al. 2008, Cytometry A 73A:926. RIQA-Flow Herzenberg v1.1 provenance layer is anchored to MIFlowCyt, covering panel, gating tree, compensation, FMO controls, and viability declarations.
ICH E9(R1) — Estimands and Sensitivity Analysis
The RIQA sensitivity analysis framework for clinical trials aligns with ICH E9(R1) estimand principles, evaluating conclusion stability under alternate analytical assumptions.
RIQA QA outputs include machine-readable JSON artifacts structured for downstream integration, consistent with FAIR data principles for research provenance infrastructure.
Research-use and scope of findings
RIQA provides analytical assurance for research and quality-review purposes. RIQA does not function as a regulatory authority, certifying body, or legal compliance organization. Findings are reproducibility and methodological consistency statements derived from submitted data and declared methodology — not determinations of scientific truth, biological validity, or regulatory compliance.
Download the RIQA White Paper
Full framework documentation · RIQA-WP-001 · 2026 · Open Access CC BY-NC 4.0
View demonstration studies →
Scope of coverage
Three domains. One consistent standard.
RIQA applies the same four-phase verification framework across three primary research and analytics domains, each with domain-specific verification procedures anchored to established community standards.
Domain 01
Preclinical & Biomedical Research
Quantitative experimental and computational workflows from laboratory, genomic, imaging, and in vivo techniques. Two production-ready verification modules currently available.
Clinical endpoint and survival analyses where integrity of outcome reporting has direct regulatory implications, verified by a neutral, non-sponsoring party.
Independent verification of quantitative experimental workflows — from single-cell transcriptomics and flow cytometry to RT-qPCR and imaging — where analytical implementation choices directly affect reported biological conclusions.
Production modules
Available verification frameworks
Stable v1.1
RIQA-qPCR Livak
Anchor standard: MIQE 2.0 (Bustin et al. 2025)
Independent reconstruction of fold changes via 2^−ΔΔCt from submitted per-replicate Cq values. Evaluates reference gene stability, statistical methodology, and MIQE 2.0 provenance.
Reconstruction of frequency endpoints in percentage-point space and MFI in log₂-ratio space. Unique gating tree arithmetic coherence layer verifies parent-child consistency across every gate transition.
Frequencies (pp space)MFI (log₂ space)Gating tree coherencePath A and Path B
Pilot framework
RIQA-RNAseq
In development · Target: v1.0
DEG verification, pathway enrichment sensitivity, batch correction documentation, and normalisation method consistency for bulk RNA-seq workflows. Pilot engagements in scoping.
Western blot densitometry, histology and image-based quantification, proteomics and metabolomics normalisation, and scRNA-seq cluster stability assessment.
Segmentation threshold, ROI definition, reader variability, quantification software version
Near-deterministic · Structural verification
Western blot
Loading control linear range, ROI definition, normalisation reference
Exact · Near-deterministic
Submit a biomedical study for review
Initial scoping consultation at no cost.
← All domains
Domain 02
Clinical Research & Trial Analytics
Independent verification of clinical endpoint analyses and survival studies — where integrity of outcome reporting has direct regulatory implications, verified by a neutral, non-sponsoring party.
Verification scope
What RIQA evaluates in clinical research
Modern clinical studies involve implementation-sensitive analytical choices that are rarely subjected to external reconstruction. RIQA evaluates whether the analytical logic is sound, the SAP was followed, and conclusions hold under alternate assumptions.
Verify correction method and scope; recompute adjusted p-values
Illustrative agreement
When exact reconstruction is not expected
RIQA evaluates directional stability and significance preservation — not numerical identity — for software-tolerant methods like MMRM.
Illustrative agreement assessment
Scenario
HR
p-value
Sponsor reported
0.74
0.041
RIQA reconstruction
0.79
0.067
Alternate censoring
0.83
0.110
Breslow tie-handling
0.81
0.089
Illustrative example from RIQA-CS-CLI-001 demonstration study.
RIQA assessment
Treatment direction preserved across all scenarios. Statistical significance was not maintained under four of six sensitivity scenarios evaluated, including the RIQA primary reconstruction. This class of finding — analytically subtle, methodologically significant — is RIQA's primary value proposition in the clinical domain.
F-102 · Moderate
Significance not maintained under alternate analytical assumptions. Recommendation: strengthen SAP censoring specification and pre-register sensitivity analyses.
Engagement models
When to engage RIQA in clinical research
Pre-NDA / pre-submission
Sponsor-engaged assurance
Independent reconstruction of primary and secondary endpoints before a regulatory or publication submission. RIQA assurance report included in the submission package.
Pre-publication
Author-engaged assurance
Research groups seeking methodological assurance before submission to high-impact journals. Structured assurance report referenced in methods section.
Grant applications
NIH grant proposal assurance
PIs seeking neutral third-party verification of preliminary data statistical conclusions before R01 or other funding submissions.
Submit a clinical study for review
Pre-NDA, pre-publication, or grant proposal assurance.
← All domains
Domain 03
Healthcare Analytics & Quality Assurance
Specification-to-implementation verification of claims-based models and quality reporting pipelines — verifying whether implemented analytics match declared specifications where errors carry direct financial and compliance consequences.
Audit scope
What RIQA evaluates in healthcare analytics
RIQA verifies whether the implemented analytics match the declared specifications — identifying inconsistencies between documented logic and production implementation.
HEDIS measure specification compliance, numerator and denominator derivation, measure version tracking
Specification-to-code gaps, measure version drift across reporting periods
ETL governance
Transformation logic documentation, data lineage tracing, schema version tracking, field-level mapping verification
Undocumented transformations, field mappings deviating from specification
HCC drift analysis
Longitudinal consistency of HCC assignments across model updates, software version changes, crosswalk revisions
Silent output changes accumulating over time
Concrete anomaly examples
What a typical implementation gap looks like
HCC flag miscalculation
Chronic condition look-back mismatch
Specification requires a 24-month look-back window for chronic HCC conditions. Production code implements 12 months. Result: 3,847 members missing qualifying diagnoses. RAF scores systematically understated by an average of 0.14 per affected member.
ETL transformation drift
Revenue code crosswalk version mismatch
Model documentation references FY2022 ICD-10-CM crosswalk. Production pipeline silently retained FY2021 mappings after a scheduled update. 214 procedure codes mapped to incorrect HCC categories across Q1–Q3.
Quality measure reconstruction
Denominator construction error
Reported measure denominator: 18,440 eligible members. RIQA reconstruction: 16,982. Discrepancy of 1,458 members traced to an enrollment gap period not excluded per HEDIS specification. Compliance rate overstated by 2.3 percentage points.
These examples are illustrative. All figures are synthetic and constructed for demonstration purposes.
Illustrative finding
The stakes of implementation gaps
RIQA-CS-CMS-001 · Demonstration study
HCC look-back window mismatch
A Medicare Advantage analytics team submitted a hierarchical logistic regression model for risk-adjusted readmission rate verification. RIQA's quality assurance review identified that the HCC chronic condition look-back window had been implemented as 12 months despite a 24-month specification in the model documentation.
No evidence of misconduct was identified. The error arose from a specification-to-implementation gap — a class of error invisible to any review mechanism that does not independently examine the code against the specification.
Resubmission completed with corrected covariate derivation and updated ICD-10 crosswalk.
Submit an analytics model for review
Risk adjustment, quality reporting, or claims analytics.
← All domains
Demonstration series
RIQA Analytical Demonstration Studies
These studies illustrate how the RIQA framework evaluates analytical integrity across three primary domains. They demonstrate the verification methodology, finding classification system, and integrity scoring framework — not client outcomes.
▲
Framework demonstration series. These studies utilize synthetic and reconstructed datasets derived from publicly available analytical patterns and are intended solely to illustrate the RIQA verification methodology and reporting framework. They are not client engagements, real studies, or validated deployments. Initial collaborative pilot engagements with research institution partners are currently in development.
A research group engaged RIQA for pre-publication methodological assurance of a multi-modal vascular biology study integrating bulk RNA-seq, single-cell transcriptomics, in vivo phenotyping, and image-based lesion quantification.
Biological direction preserved across all reconstruction workflows.
RIQA-CS-CLI-001Clinical Research & Trial Analytics
Pre-NDA Assurance · Phase III Oncology Survival Analysis
A pharmaceutical sponsor engaged RIQA for pre-NDA independent external analytical assurance of a Phase III randomized trial in advanced NSCLC. Primary endpoint: progression-free survival.
F-101 · Censoring rule implementation gapModerate
F-102 · p-value sensitivity to censoringModerate
F-103 · SAP tie-handling underspecifiedMinor
82/ 100Verified with notes
Treatment direction preserved. Significance not maintained across 4 of 6 sensitivity scenarios.
A healthcare analytics team submitted a hierarchical logistic regression model for risk-adjusted readmission rate verification prior to CMS quality reporting across 142,800 beneficiaries and 14 providers.
F-201 · HCC look-back window mismatch (12 vs 24 mo)Major
F-202 · ICD-10 crosswalk version discrepancyModerate
F-203 · ETL transformation undocumentedMinor
72/ 100Methodological concerns
8.3% of beneficiaries affected. 3 of 14 providers crossed compliance threshold. Resubmission required.
About this series
Methodology over narrative
These demonstration studies were developed to show how the RIQA framework reasons through complex analytical integrity problems — not to simulate a client portfolio. The value is in the methodology: the finding classification logic, the verification vocabulary, the integrity scoring framework, and the structured quality assurance report format.
RIQA's first real pilot engagements are currently in development with collaborating research institution partners. If you are interested in participating in a pilot engagement, contact us through the form below.
Interested in a pilot engagement?
Real data. Real findings. No commitment required at this stage.
Get in touch
Submit a study or start a conversation
Initial scoping consultations are conducted at no cost. Use the form below to describe your study or engagement interest and we will respond within two business days.
Inquiry received
Thank you for reaching out. RIQA will review your inquiry and respond within two business days.