TDM - Pharmacovigilance software; Drug Safety Database

Need for this

In the domain of pharmacovigilance, handling and consuming vast amounts of literature is essential in pharmacovigilance. PvEdge's Literature Access Module (LAM) has proven invaluable in retrieving relevant articles from a variety of databases, including MEDLINE, Embase, Excerpta Medica, PubMed etc. However, sorting through these articles, selecting the relevant ones, and processing them appropriately still took a lot of human labor. This manual process required a lot of time, and work, and was prone to human mistakes. To overcome these obstacles, a more automated and effective way to improve productivity and optimize this workflow was desperately needed

How it Benefits

Text Data Mining (TDM) is designed to overcome the limitations of the existing LAM feature by introducing a higher level of automation and intelligence. The benefits of TDM include:

Reduced Manual Effort

By automating the extraction and processing of relevant articles, TDM minimizes the need for manual intervention, saving time and reducing labor costs.

Enhanced Efficiency

TDM processes large volumes of data quickly, enabling faster access to critical information and speeding up the decision-making process.

Scalability

Capable of handling increasing volumes of data, TDM ensures that the system can scale with the growing demands of pharmacovigilance activities.

User-Friendly Interface

Features such as field and case audit trails, source and output data logs, and ML-based algorithm optimization provide a seamless and efficient user experience.

Improved Accuracy

Advanced algorithms and natural language processing (NLP) ensure that only relevant pharmacovigilance articles are identified and processed, reducing the risk of human error.

How We Are Using TDM in Existing Products

TDM has been integrated into the PvEdge platform as an enhancement to the existing LAM feature. The workflow with TDM includes:

Automated Data Fetching: TDM fetches articles from PubMed, Embase, MEDLINE, and other platforms, just like LAM, but it goes further by automating the entire data extraction process.
Content Analysis: Using NLP and data mining techniques, TDM reads the content of fetched articles, identifying those relevant to pharmacovigilance.
Document Processing: TDM automates various document processing tasks, such as FTA details fetch, multi-patient identification, duplicate search mechanisms, ICSR & AOI segregation, and R2 XML generation.
Verification and Reporting: The system provides extracted data highlights for verification and generates reconciliation reports, ensuring data accuracy and integrity.

Result of Implementation of TDM

The implementation of TDM in PvEdge has yielded significant improvements:

Time Savings

The automated processes have drastically reduced the time required to identify and process relevant pharmacovigilance articles.

Increased Productivity

With less manual effort needed, staff can focus on more critical tasks, enhancing overall productivity.

Higher Accuracy

The use of advanced algorithms has improved the accuracy of data extraction and processing, leading to better decision-making.

Scalability

PvEdge can now handle larger volumes of literature more efficiently, supporting the growing needs of pharmacovigilance operations.