Our deep learning AI models make the digitization and data mining process cost and time effective, while assuring compliance to the IDMP data standards.
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Key challenges in IDMP Compliance
With IDMP Compliance becoming mandatory by 2023, Pharma companies have begun the arduous task of understanding the requirements of IDMP compliance, data analysis and digitizing the data from SmPCs and eCTD Module 3 documents into IDMP compliant data sets to feed into regulatory submission systems. Most of the data is in unstructured regulatory documents and requires to be extracted and tagged appropriately. This involves lot of manual effort and precious time from medical experts to ensure the extracted data is codified properly and validated.
Time-bound regulatory mandate
Unstructured Regulatory Documents
Manual Review Process
Expert intervention
Data Digitization for IDMP Compliance – DF IDMP AI
DF IDMP AI helps achieve efficiency and compliance during the IDMP data life cycle. Starting from data extraction using our OCR models, to text mining using our NER models tailored for IDMP data standards, the process of generating a structured data set is automated to a large extent. The medical experts can focus on validating the output through a user-friendly UI. The IDMP data set is then made available to any down stream application such as a regulatory submission system or for analytics and insights.
The below are the key features of DF IDMP AI:
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Use the DF IDMP AI platform on our secure and compliant cloud or implement it in their own environment. -
Integrate the digitization pipeline with their upstream data sources and downstream applications.
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User-friendly UI for validation, analytics and insights.
Advantages of DF IDMP AI
