Structure Data for the IDMP Model
Transform extracted regulatory data into structured, IDMP-ready datasets aligned with the right model, fields, and granularity.
Overview
IDMP Structuring helps teams organize regulatory data into a consistent target model, normalize values, and prepare reusable datasets for downstream validation, comparison, and submission readiness.
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Model Alignment
Align source data with the target IDMP structure across products, packages, manufacturers, and related entities.
Value Normalization
Standardize codes, controlled terms, and field values to improve consistency across records and datasets.
Granularity Control
Apply the right level of detail for each data object to support regulatory business rules and future submission needs.
Example Code for
IDMP Structuring
See how Theranext turns complex regulatory data into structured, validated, and operational outputs through configurable workflows across extraction, integration, and readiness activities.
# Example structuring flow
source_data = "extracted regulatory dataset"
target_model = "IDMP target structure"
map_entities = ["medicinal product", "pack", "manufacturer"]
normalize_values = ["codes", "terms", "formats"]
check_granularity = True
output = "structured IDMP-ready dataset"Move from complexity to execution
Theranext helps pharma teams structure data, deliver transformations, and operationalize AI across R&D processes.
