Project Name
FDA Data Compliance: Converting XML/JSON to a Regulated Schema at Scale
Our client is a US-based life sciences and pharmaceutical services organisation responsible for preparing and submitting Structured Product Labelling and adverse event data to the US Food and Drug Administration on behalf of multiple sponsor companies.
Their submission workflow was entirely manual – analysts received source data in varying XML and JSON formats from sponsors, manually mapped fields to FDA schema requirements, and used a combination of spreadsheets and desktop validation tools to check compliance before submission.
With submission volumes growing and FDA schema versions evolving, the manual process was becoming untenable from both a cost and risk perspective – every schema update required manual review across the team, and every ESG rejection consumed days of rework time the organisation could not absorb at scale.
Heterogeneous source formats from multiple sponsors, deeply nested FDA schema specifications with hundreds of conditional validation rules, a 30% first-submission rejection rate, and an audit trail that existed only in analyst inboxes.
- Heterogeneous Source Data Formats: Sponsor data arrived in different XML and JSON formats with inconsistent structures, field names, and code sets, requiring extensive manual mapping before submission.
- FDA Schema Complexity: Complex FDA schemas with deeply nested structures and conditional validation rules made manual implementation and maintenance difficult.
- Schema Version Management: Frequent FDA updates to schemas and medical code sets required time-consuming manual changes to transformation logic.
- Validation Before Submission: Every submission needed comprehensive pre-validation to prevent FDA rejections caused by schema or code set errors.
- Regulatory Audit Trail: Each transformation, validation, and submission required a complete, traceable audit log to meet regulatory compliance requirements.
- High-Volume Processing: Growing submission volumes demanded automated, large-scale processing beyond the limits of the existing manual workflow.
Ksolves, an AI-first DevOps consulting services company, developed a multi-stage regulatory data pipeline that transforms diverse source formats into FDA-compliant submission documents using a canonical data model and rule-based mapping engine. Built with a validate-first approach, the solution detects and resolves issues before submission, improving accuracy and compliance.
- Source Ingestion & Normalization: XML and JSON files are converted into a validated canonical data model, identifying missing fields, invalid formats, and inconsistent values early in the process.
- Rule-Based Mapping Engine: Version-controlled mapping rules transform the canonical model into FDA-compliant formats, making schema updates configuration-driven rather than code-driven.
- FDA Code Set Validation: Automated validation against current FDA code sets ensures all coded values comply with approved medical terminologies before document generation.
- XSD & Schematron Validation: Every submission is validated against official FDA schemas and business rules, with detailed error reporting for faster issue resolution.
- ESG Submission Integration: Validated documents are automatically submitted to the FDA Electronic Submissions Gateway, eliminating manual upload processes.
- Audit Logging & Traceability: Every transformation, validation, and submission is recorded with complete audit metadata, ensuring end-to-end regulatory traceability and compliance.
Technology Stack
| Category | Technology |
|---|---|
| Data Pipeline | Node.js / Express |
| Schema Standards | HL7 v3 CDA / SPL / MedWatch XML |
| Validation | XSD / Schematron / AJV |
| Code Set Management | NDF-RT / SNOMED CT / MedDRA / RxNorm |
| Submission Channel | FDA Electronic Submissions Gateway (ESG) |
| Audit and Storage | AWS S3 + DynamoDB |
The solution delivered significant improvements in regulatory compliance, processing efficiency, and submission accuracy.
- Submission Preparation Reduced from 12 Hours to Under 20 Minutes: Automated processing and validation significantly accelerate FDA submission preparation.
- Over 95% First-Pass ESG Acceptance: Pre-submission validation minimizes schema and code set errors, reducing submission rejections.
- Schema Updates Deployed in Under 4 Hours: Configuration-driven mapping enables faster adoption of FDA schema changes with automated testing.
- End-to-End Regulatory Audit Trail: Immutable audit logs provide complete traceability from source data to FDA acknowledgement, ensuring regulatory readiness.
By automating the end-to-end regulatory submission process, Ksolves replaced manual, error-prone workflows with a scalable and compliance-driven pipeline. The solution accelerated submission preparation, improved validation accuracy, strengthened audit readiness, and reduced regulatory risks through automated mapping, validation, and traceability. Built on a flexible architecture, the platform is well-positioned to support future FDA submission types and evolving global regulatory requirements.
Does Your Regulatory Submission Process Still Rely on Analysts Mapping Fields by Hand?
