GENINVO Blogs

Building a Strong Foundation: Robust Metadata Repository (MDR) Framework for Automated Standard Compliant Data Mapping

Pharmaceutical and biotechnology companies operate within a constantly evolving regulatory landscape, where adherence to standards set by organizations like the Clinical Data Interchange Standards Consortium (CDISC) is crucial for submitting clinical trial data. In the area of clinical trial data management, information can originate from various sources and be stored across different platforms, systems, and networks. This includes data stored in spreadsheets with edit checks and specifications, as well as PDF documents containing Case Report Forms (CRFs) and protocols, this list goes on and on. With the constant updates and creation of new versions, it becomes challenging to ensure utilization and access to the most up-to-date files/standards and use it effectively to map raw clinical data in standards-compliant datasets (such as CDISC-SDTM). GenInvo has leveraged use of Machine Learning to develop tool (ApoGI™) which offer a robust metadata repository framework (MDR Module) to address these issues.  

ApoGI™ – Metadata Repository (MDR) Module 

The ApoGI™ – MDR module helps users to set up project-specific metadata through an intuitive graphic user interface (GUI). The data transformation (ApoGI-DT™) module of the ApoGI converts trial-related information to CDISC or sponsor-specific data standards. The solution stores all metadata in a central registry, and automatically maps new study metadata with the existing database. 

By utilizing ApoGI™ – MDR,  

  • One can easily track and manage the latest versions of files/standards, while also ensuring the integrity and quality of the data.  
  • This framework acts as a centralized hub responsible for capturing and managing the metadata associated with clinical studies.  
  • It efficiently manages various components such as source data, SDTM domain metadata, SDTM mapping specifications, and transformation rules etc…  
  • By consolidating these elements within a single platform, organizations can streamline their data management processes, enhance data integrity, and facilitate efficient data transformation and mapping activities.  

Furthermore, this MDR module enhances collaboration and consistency among team members by offering a centralized repository for data transformations, serving as a single source of truth. It also provides the advantage of inheritability and scalability for future study creation, enabling organizations to efficiently build upon existing frameworks. By maintaining data integrity and traceability, the MDR module simplifies the validation process and expedites regulatory submission. The implementation of MDR module promotes transparency and facilitates efficient management of changes, ultimately resulting in the generation of accurate and standards-compliant datasets (such as CDISC-SDTM). 

Key features of the ApoGI™ – MDR 

  • Workflow management: It automates workflows for creating new data standards or maintaining existing ones  
  • Automated study setup: Importing both Legacy/CDISC Metadata into ApoGI system with autorecognition of CDISC standards. Automatically maps new study metadata with the central library. 
  • Managing the Legacy/CDISC Metadata with any edits/updates to the domain/element. 
  • Governance model to support Governance process  
  • Impact Analysis: One of the key objectives of an MDR is to assess the potential impact of metadata changes before implementing them. This analysis involves evaluating all relevant standards and assets to let you know exactly what downstream and upstream metadata and processes that will be influenced by the proposed change.  
  • Change control: MDR allow users to initiate change requests for existing standard objects. This functionality enables users to log requests for modifications, such as updating a form. The change control process, which follows a pre-defined workflow, governs the approval process and the tracking and management of these change requests. All changes are tracked from inception to completion. 
  • Versioning 
  • Traceability 
  • Exporting functionality available for metadata. 
  • Reports and Dashboards: Intuitive dashboard to reflect on the KPIs used in standards. The flexibility to define customized reports based on user preference. Tracks any addition, deletion, or change in each object by maintaining an audit trail 
  • User management: Assigns roles and access privileges to users based on business needs 
  • 21CFR Part 11 Compliance 

ApoGI™ – MDR Flow: 

By Hitesh Raval, Principal Data Scientist & CDISC SME 

More Blogs

Importance and examples of usage of Data Anonymization in Healthcare & Other sectors

Data anonymization plays a critical role in healthcare to protect patient privacy while allowing for the analysis and sharing of…
Read More

Data Anonymization and HIPAA Compliance: Protecting Health Information Privacy

Data anonymization plays a crucial role in protecting the privacy of sensitive health information and ensuring compliance with regulations such…
Read More

Automation of Unstructured Clinical Data: A collaboration of automation and Medical Writers

In the field of healthcare, clinical data plays a crucial role in patient care, research, and decision-making. However, a significant…
Read More

Quality Control of the Methods and Procedures of Clinical Study

Methodology section of the Clinical Study Report (CSR) provides a detailed description of the methods and procedures used to conduct…
Read More

Automated Quality Control: Get the best out of your Clinical Study Report Review 

What are Clinical Study Reports?  Clinical study reports (CSRs) are critical documents that summarize the results and findings of clinical…
Read More

Clinical Study Results: Quality Control on study findings and outcomes

Clinical Study Reports, or the CSRs, are comprehensive documents providing detailed information about the design, methodology, results, and analysis of…
Read More

Big Save on Time > 60%, A case Study: DocQC™ Tested on 25 Studies.

Medical Writers have provenly spent a lot of time historically, in reviewing the Clinical Study Reports. Clinical Study Reports, or…
Read More

Data Anonymization in the Era of Artificial Intelligence: Balancing Privacy and Innovation

Data anonymization plays a crucial role in balancing privacy and innovation in the era of artificial intelligence (AI). As AI…
Read More

Automated Quality Control: Get the best out of your Clinical Study Report Review

What are Clinical Study Reports?  Clinical study reports (CSRs) are critical documents that summarize the results and findings of clinical…
Read More

Data Redaction: Safeguarding Sensitive Information in an Era of Data Sharing

Data redaction is a technique used to safeguard sensitive information in an era of data sharing. It involves selectively removing…
Read More

10 Best Data Anonymization Tools and Techniques to Protect Sensitive Information

Data anonymization plays a critical role in protecting privacy and complying with data protection regulations. Choosing the right data anonymization…
Read More

Building a Strong Foundation: Robust Metadata Repository (MDR) Framework for Automated Standard Compliant Data Mapping

Pharmaceutical and biotechnology companies operate within a constantly evolving regulatory landscape, where adherence to standards set by organizations like the…
Read More

Digitalization of Medical Writing: Balancing AI and Rule-based algorithms with Human Supervision in Medical Writing QC

What is Digitalization of Medical Writing?  The digitalization of medical writing refers to using digital technologies and tools to create,…
Read More

The Rise of Differential Privacy: Ensuring Privacy in the Age of Big Data

The rise of differential privacy is a significant development in the field of data privacy, especially in the age of…
Read More

Role of Intelligent Automation: How Intelligent Automation transforms the Clinical Study Document Review in Real Time

Clinical Study Reports play a critical role in assessing the safety and efficacy of new medical treatments. Review of these…
Read More

Automation on Clinical Study Report: Improve the Speed and Efficiency of document review. 

Clinical Study Report (CSRs) are critical documents that summarize the findings and results of clinical trials. These reports require a…
Read More

Digitalization of Quality Control in Medical Writing: Advantages Digitalization brings for the critical aspects of Quality Control

Quality control in medical writing is a critical aspect of ensuring the accuracy, clarity, and reliability of medical documents. It…
Read More

Importance of “Table, Listing and Figures” Automation in Clinical Trials

Tables, Listings, and Figures (TLFs) help to analyse and summarize datasets of a clinical study into an easily readable format….
Read More

The “What” and “Why” of Clinical Data Anonymization

Clinical data anonymization is the process of transforming or modifying sensitive clinical-related information in a way that protects the privacy…
Read More

Medical Writer’s True AI Enabled Assistant

At GenInvo, our motive is to support pharmaceutical companies to bring life changing therapies into the market sooner so that…
Read More

Contact Us​

Skip to content