The cost of conducting pharmacovigilance is increasing year-on-year with the growing volume of cases received by the pharmaceutical companies. Among the major functions of a pharmacovigilance department, case management is considered to be the most resource-intensive process.
Cognitive computing algorithms could automate several activities in pharmacovigilance, decreasing the overall costs of conducting pharmacovigilance.
This white paper explores the use of cognitive computing in pharmacovigilance, including:
- Case intake, triage, and receipt: Intelligent systems can scan the text/voice from various to identify important drug safety information required for case report generation.
- Case processing: Cognitive computing could automate most of the steps in case processing and decrease the manual workload
- Data analysis and signal detection: Cognitive computing systems can conduct a continuous analysis of the aggregate safety data as new cases are being added.
- Benefit-risk assessment: When a risk is identified, the predictive algorithms can estimate the burden it can cause on public health or on a specific population by taking various parameters into account.