10 Small Submissions
No more than 10 Documents per submission
ICSR case processing process within Pharmacovigilance operations is becoming complex owing to multiple unstructured data sources. There are more data sources than ever including social media, real-world data, electronic patient health records, insurance claims, etc.
Converting this unstructured information to structured format to feed into the global safety database using manual processes is error-prone and more resource-intensive.
High operational cost to manage the unstructured data due to lack of technology that integrates with existing safety systems.
High volume of data from disruptive technology like smart sensors and wearables are increasing the main source of patient data for virtual or decentralized trails and patient-centric trails.
Automating the intake of the adverse events for ICSR reporting from various unstructured data sources to structured data formats like E2B can be technologically viable.
All the unstructured data elements can be mapped/extracted to a structured format using advanced technologies like AI and machine learning translation, ontology searches, extraction of text embedded in the image and scanned PDF documents, medical transcriptions, speech to text conversion, relationship extraction for medication, etc. All these data processing services allow users to easily classify incoming adverse events into high-level categories and drastically reduce the time spent by human teams.
Technologies like Robotic Process Automation (RPA), NLP, NLG and cloud computing, along with the above-mentioned data processing services, using vendors like AWS, Microsoft, Google, etc. will be crucial for Regulatory and safety operations.
Importing the final structured E2B output of the adverse events in the safety system, along with an expert, to finalize and validate the adverse events will reduce the overall cost and increase efficiency.