CDISC Clinical Data Validation Software
Semantic Intelligence Driven
Stop Checking Data.
Start Understanding It.
Kwalify™ operationalizes Care2Data's knowledge-driven validation framework — embedding semantic intelligence across linked clinical datasets to strengthen accuracy, traceability, and regulatory readiness before submission.
Kwalify™ Platform · Problem → Solution → Outcomes
Built for the Reality of Clinical Validation
Modern clinical validation demands more than rule execution — it requires systems that understand complexity, reduce inefficiencies, and scale with evolving study needs.
Kwalify™ is designed to address these realities through:
Purpose-built capabilities for complex clinical validation workflows
Seamless integration with existing clinical systems
Elimination of systemic SDTM data quality patterns — including missing reference ranges (93%), unit mismatches (79%), duplicate AE events (67%), and missing RFSTDTC (63%)
Purpose-Built Validation
Capabilities engineered specifically for complex clinical validation workflows — not repurposed from general analytics tools.
Seamless Integration
Embeds within existing clinical systems and workflows without requiring replacement or operational disruption.
Eliminate Hidden Inefficiencies
93% of surveyed datasets contain missing reference ranges in the LB domain alone — systemic patterns that Kwalify™ surfaces and resolves automatically.
Clinical Data Validation Has Outgrown Static Rules
Clinical trials generate deeply interconnected datasets across subjects, treatments, outcomes, and safety signals. Regulatory scrutiny continues to increase. Validation tools that rely on static rule execution are no longer sufficient.
Most validation systems available today:
- Execute static rule libraries
- Return pass/fail flags only
- Escalate investigation to humans
- Provide limited cross-dataset reasoning
They detect symptoms.
They do not diagnose causes.
Kwalify™:
- Applies semantic, context-aware validation across linked datasets
- Generates explainable insights — not just pass/fail outcomes
- Automates root cause analysis with AI-assisted reasoning
- Enables cross-domain intelligence and impact-aware validation
It connects signals.
It diagnoses causes.
The Intelligence Difference
Kwalify™ introduces a Semantic intelligence layer for clinical data validation.
By combining semantic reasoning, anomaly verification, and contextual validation across linked datasets, Kwalify™ transforms validation from checklist execution into knowledge-driven assurance.
Instead of identifying violations, Kwalify™ enables teams to understand the cause, impact, and resolution of data inconsistencies before submission.
Built for Clinical Validation — Not Repurposed Analytics
Many market solutions evolved from general-purpose data quality tools. Kwalify™ was engineered specifically for clinical validation, regulatory compliance, and submission workflows.
Context-Aware Validation
Kwalify™ evaluates relationships across domains, variables, and study logic—moving beyond isolated rule checks.
Validation logic understands study structure, regulatory expectations, and cross-dataset dependencies.
Explainable AI
For every validation finding, Kwalify™ generates:
- Issue summary
- Root cause explanation
- Impact analysis
- Recommended remediation
Customizable Compliance Rules
Beyond regulatory rule libraries, teams can configure study-specific validation rules to enforce additional compliance requirements—ensuring quality, integrity, and conformance alongside regulatory checks.
This enables organizations to apply internal governance standards alongside regulatory checks.
Traceable by Design
Validation lineage, rule logic, and investigation trails are embedded into the architecture.
Every validation outcome is traceable—supporting regulatory inspections and internal QA review.
Works Within Your Ecosystem
Kwalify™ integrates seamlessly with existing clinical systems including:
- Clinical Data Management Systems (CDMS)
- Statistical Computing Environment (SCE)
- Meta Data Repository Systems (MDR)
Regulatory Confidence — Driven by Accuracy, Consistency, and Scalability
Kwalify™ operates as a semantic intelligence layer across submission datasets — from ingestion to verified, audit-ready output.
Submission Dataset Ingestion
Clinical datasets from EDC systems are uploaded into Kwalify™ in standard formats (SAS, CSV) representing submission-ready data structures.
Regulatory Rule Validation
Datasets validated against FDA and CDISC rule libraries, ensuring conformance with regulatory data submission expectations.
Cross-Domain Contextual Validation
- Adverse events
- Subject lifecycle data
- Treatment exposure
- Safety signals & endpoints
Validation examines data meaning and relationships — not just syntax.
AI-Assisted Root Cause Analysis
- Issue summary
- Root cause analysis
- Regulatory impact
- Remediation steps
Guided resolution — reducing investigation time significantly.
Verification Through Anomaly Detection
- Temporal inconsistencies
- Subject lifecycle contradictions
- Sequence conflicts
- Unexpected data relationships
True data integrity — beyond rule compliance.
Operational Visibility Across Studies
Kwalify™ provides a centralized validation dashboard for monitoring study progress and compliance readiness — giving every team member instant, actionable insight.
Teams can instantly view:
Active Studies Under Validation
Monitor all ongoing clinical studies in a single, unified view.
Rule Compliance Status
Real-time conformance tracking against FDA and CDISC rule libraries.
Validation Progress Milestones
Track submission readiness against study timelines and deadlines.
Domain-Level Violation Summaries
Instantly identify which domains carry the highest error density.
Validation Trend Analysis
Intelligent grouping and prioritization of errors across multiple runs — eliminating manual cluster identification.
Error rate ↓ 61% across 6 runs
Enables proactive issue resolution and faster submission readiness — turning validation reporting into an operational advantage.
The Outcome
Submission-ready, defensible clinical data — without late-stage rework, without validation bottlenecks, without replacing existing systems.
Strengthened Data Integrity
Identify discrepancies at their origin — ensuring data accuracy before QA or regulatory review.
Faster Validation Cycles
AI-assisted investigation using LLM models reduces manual debugging and accelerates issue resolution.
Reduced Regulatory Queries
Explainable AI validation outputs improve clarity and traceability in submissions.
Enterprise Scalability
Kwalify™ scales across therapeutic areas, studies, and global trial programs without increasing validation complexity.
Why Enterprise Teams Are Moving Beyond Traditional Validation Tools
Many clinical validation tools in the market rely on static rule execution engines. While these systems can detect rule violations, they often require extensive manual investigation to understand the root cause and downstream impact of errors.
Common limitations of traditional validation tools include:
Limited cross-dataset reasoning
Lack of contextual validation logic
Minimal guidance for issue resolution
Fragmented visibility across studies
These gaps are consistently reflected in user feedback:
Vague error messages
No prioritization
Difficulty identifying affected records
Missing Reference Ranges
The most frequent lab-domain issue — often impacting downstream interpretation of safety data and missed by standard rule checks.
Unit Mismatches
Inconsistent measurement units across records create hidden inconsistencies that static rule checks cannot fully contextualize or resolve.
Duplicate AE Events
Present in 67% of datasets — leading to inflated or misleading adverse event reporting if not correctly identified before submission.
Missing RFSTDTC
Affects subject timeline anchoring in DM domain records — breaking downstream ADaM derivations and regulatory traceability.
Kwalify™ addresses these gaps through an intelligence-driven validation architecture. By combining semantic reasoning, anomaly verification, and explainable AI validation outputs, Kwalify™ enables teams to move beyond simple rule checking toward comprehensive data integrity assurance. The result is a validation process that is not only faster — but also more accurate, consistent and scalable under regulatory scrutiny.
Not Just a Tool.
An Intelligence Infrastructure.
Kwalify™ is engineered as a long-term clinical validation infrastructure — combining semantic reasoning, linked data models, and audit-ready architecture to deliver enterprise-grade data quality at every stage of the trial lifecycle.
Learn About Compliance Architecture →Knowledge-Driven Validation Framework
Semantic reasoning with RCA, Downstream Impact Analysis & impact chain visibility.
Linked Clinical Data Model
Enables structured reasoning across datasets rather than isolated rule checks.
Embedded Semantic Intelligence
Encodes study logic and regulatory expectations directly into validation workflows.
Audit-Ready Architecture
Traceability, lineage, and validation transparency built in — ensuring quality, integrity, and conformance.
Governance-Aligned Deployment
Supports regulatory expectations including data integrity requirements and 21 CFR Part 11 alignment.
Issue Tracking & Management
Centralised issue lifecycle management — from detection through remediation and sign-off.
Designed for Teams Responsible for Submission Integrity
CRO Leadership
Scale validation across sponsors while reducing operational variability.
Pharmaceutical & Biotech Sponsors
Strengthen submission confidence across global clinical programs.
Clinical Data Managers & SAS Programmers
Quickly identify validation violations and investigate affected records.
QA and Regulatory Teams
Gain traceable, defensible validation outputs aligned with regulatory expectations.
A Platform for the Full Clinical Data Lifecycle
Kwalify™ is designed as a validation platform, not just a submission checker.
The current platform focuses on submission dataset validation, with a roadmap extending across the entire clinical trial lifecycle.
Future capabilities will support validation of:
Derived Analysis Outputs
ADaM datasets and analysis-ready derived variables supporting statistical endpoints.
Statistical Analysis Datasets
Validation of datasets used in statistical computing environments and TFL generation.
Clinical Reporting Data
End-to-end traceability from data collection through tables, figures, and listings.
Cross-Stage Clinical Data Integrity
Unified validation intelligence spanning every lifecycle stage — from collection to submission.
This positions Kwalify™ as a long-term validation infrastructure
for modern clinical trials.
See the Semantic Intelligence Layer in Action
Discover how Kwalify™ identifies validation issues, diagnoses root causes, and verifies data integrity before submission.
Experience how semantic intelligence transforms validation into a strategic advantage for clinical teams.
Compliance is routine.
Confidence is driven by accuracy, consistency, and scalability.
Kwalify™ transforms clinical data validation from binary rule checking into enterprise-grade, knowledge-driven quality assurance.
And eliminates the systemic inefficiencies that continue to slow down clinical validation teams today.
Frequently Asked Questions
Kwalify™ is an intelligent clinical data validation and verification platform developed by Care2Data to identify discrepancies, inconsistencies, and data integrity issues in clinical trial datasets prior to regulatory submission.
Designed as a long-term validation infrastructure, Kwalify™ extends beyond submission checks to support the entire clinical trial data lifecycle — ensuring continuous data integrity across every stage of a study.
Kwalify™ applies semantic relationships, inference techniques, contextual validation, and intelligent rule application to detect both explicit and implicit data inconsistencies that traditional validation methods may miss.
By combining semantic intelligence with explainable AI, the platform evaluates cross-domain relationships, study logic, and regulatory expectations — enabling validation that is not only rule-compliant, but context-aware and insight-driven.
Traditional double programming relies on duplicate code and manual comparison to identify discrepancies — often making it time-consuming, resource-intensive, and prone to human variability.
Kwalify™ introduces both validation and verification within a unified intelligence layer. It not only detects inconsistencies but also verifies data integrity through anomaly detection and cross-dataset reasoning — making traditional approaches increasingly redundant.
The result is broader coverage, faster validation cycles, and more consistent, defensible outputs.
Validation ensures that clinical data conforms to predefined rules, standards, and regulatory expectations.
Verification goes a step further — identifying hidden inconsistencies, unexpected patterns, and cross-domain conflicts that may not be captured by rules alone.
By combining both, Kwalify™ ensures true data integrity, not just rule compliance.
Kwalify™ is designed for teams responsible for ensuring clinical data quality and submission readiness, including:
- •Contract Research Organizations (CROs)
- •Pharmaceutical & Biotech Sponsors
- •Clinical Data Management & Biostatistics Teams
- •Quality Assurance & Regulatory Affairs Professionals
Yes. Kwalify™ is built to support submission-ready and audit-ready datasets, with embedded traceability, lineage, and explainable validation outputs.
The platform aligns with regulatory expectations, including data integrity requirements and 21 CFR Part 11 compliance, enabling teams to submit with greater confidence and defensibility.
Kwalify™ supports a wide range of structured clinical datasets used across the trial lifecycle, including:
- •Clinical trial analysis datasets (e.g., SDTM, ADaM)
- •Derived variables and statistical outputs
- •Data used for clinical reporting and regulatory submission
Kwalify™ is designed to integrate seamlessly with existing clinical systems, including EDC platforms, CDMS, and statistical programming environments.
It works alongside current workflows — enhancing validation capabilities without requiring system replacement or disruption.
This ensures teams can adopt intelligence-driven validation while maintaining operational continuity.
Kwalify™ delivers measurable improvements across the clinical validation lifecycle:
Additionally, individual validation errors that typically require 30 minutes to 2 hours of manual debugging are resolved with AI-assisted root cause analysis — reducing investigation time and accelerating submission readiness.
Based on Care2Data's survey of clinical data professionals, the most frequently cited limitations of traditional validation tools are:
These gaps reflect a systemic reliance on static rule execution — tools that detect symptoms without diagnosing causes. Kwalify™ addresses each of these directly through explainable AI outputs, intelligent error prioritisation, and cross-domain impact tracing.