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Machine Learning NLP Engine for Pharmacovigilance


Centreum has developed a machine learning engine to improve safety monitoring and compliance by automating the identification and tagging of clinical entities such as adverse events, and patient events (such as discharge, hospitalization)


Medical Information Extraction


The ML Engine extracts the following attributes from unstructured reports:

  • Adverse Events (and classification of Serious Adverse Events)
  • Drug Names and dosing amounts
  • Medical Procedures/Tests conducted
  • Clinically significant events such as patient discharge, hospitalization


Patient Engagement Solution


Patient engagement solution and mobile app to improve patient experience and communication between patient and care provider

Key Features:

  • Audio/Text format –  Patients can share medically relevant information with the care provider in Audio/Text format which is analyzed in real time by the NLP Engine
  • Workflows -Based on the reported events, initiate customizable workflows (such as regulatory reporting, care provider updates)


Analysis visualization


Dashboard built using R Shiny/Python to analyze the results of the NLP engine and perform exploratory, and traceability analysis across patients, drugs, and adverse events