Pharmacovigilance (PV) is defined as the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem. (Source – https://www.who.int/teams/regulation-prequalification/pharmacovigilance)
PV is critical for drug approval, continuance, and safe use of their pharmaceutical products. At a high level, PV process begins with a reported AE (case intake), culminating with regulatory reporting and corrective actions taken.
Some of the challenges in PV Case intake are:
- Incomplete AE information
- High volume of AEs
- AE information is generated from various modes, for example, clinical trials, post marketing programs, spontaneous reports, and literature or legal reports
- Following the various modes, there are various formats of AE reports – forms, literature, emails, phones, paper etc. and it contains both structured and unstructured data.
Case Intake is a manual intensive step in the PV workflow. Automation in Case intake can reduce manual processing and improve operational efficiency. Traditional rules based automation does not provide benefits as Case Intake deals with multiple formats and unstructured data.
The evolving tech and advances in NLP has made it possible for deploying customized ML/NLP based solutions to automate the Case Intake process and reduce the manual processing. Integration of OCR helps in reading scanned forms which has unlocked previously inaccessible scanned data for automation.
DataFoundry offers an AI enabled platform to transform Pharmacovigilance / safety processes. Click here to view the video of our product in action.