Unleash the power of metadata driven by MetaVate

Why MetaVate?

End to end transparency in data flow from CDASH through SDTM, ADaM and associated TFLs.

Gain atleast 50% efficiency on data transformation & submission.

Plug & Play engine to achieve modular or end to end automation.


Statistical Computing Environment
Your challenges
  • Current environment poses limitations in business workflows for automation, information availability and access
  • Silo’ed solutions alleviate organizational challenges but are not sustainable or scalable
Our solution
  • Establishes a standard SAS execution environment
  • Scripting across platforms
  • Access to CDISC foundational standards metadata as library
  • Rich programmer utilities includes standard directory tree / storage locations and programmer utilities for troubleshooting, review and quality checks


Data Transformation Engine
Your challenges
  • Disparate approach for transforming different data states
  • ADaM transformation is challenging due to study level derivations
  • Define.xml is seen as the last step and hence prone to data structure errors
Our solution
  • Standard approach that generates data transfer specifications, data flow and data sets based on source and target data states and map metadata
  • Data states can be any relational data including CDASH, SDTM, and ADaM
  • Define.xml is defined right at the beginning to avoid future issues


Standards Management Module
Your challenges
  • Studies built over time have different metadata design and hence add complexities for cross study analysis, data aggregation and operational inefficiencies
Our solution
  • Concise & adequate metadata design to support operational efficiency for managing data standards across studies, therapeutic areas
  • Legacy data conversion
  • Comparisons between studies, study to standard, versions of standards, intitial to final study data spec., etc
  • Access to CDISC foundation standards metadata as library


Data Anonymization Module
Your challenges
  • Deidentification and anonymization of individual patient data to fulfill regulatory requirements relating to transparency at the same time safeguarding data privacy of participants
Our solution
  • Deidentifies data at multiple levels using the metadata design to meet regulatory requirements, making the data available while protecting the privacy of study subjects
  • Consistent anonymizations across data states such as SDTM and ADaM


Statistical Reporting Module
Your challenges
  • Time consuming double programming spaghetti code approach which leads to lot of manual verification and inconsistencies between SAP, shells and outputs
Our solution
  • Assists in creating tables and listings. Mainly focused on titles and footnotes at this time
  • Can be customized to build sponsor based TFL shells
  • Title / Footnote storage and automation to reports
E3 Structure and Content of Clinical Study Reports COMPLIANCE


Regulatory Submission Module
Your challenges
  • Process of arranging multiple metadata definitions (SDTM, ADAM, ARM) in Define-XML may be very time-consuming if it is handled manually
Our solution
  • Create programming-related deliverables for eCTD submissions, including define.xml schema version 2 and SAS transport files
  • Enhanced define in html format for submission as printable define

* - All product names, logos, and brands are property of their respective owners.