One of the revolutionary technologies that has transformed pharmacovigilance is artificial intelligence (AI). Traditional methods of data analysis, based on manual processing of adverse event reports, can no longer cope with the massive volume of information coming from various sources. Every day, pharmaceutical companies receive data from clinical trials, physician reports, patient complaints, and even social media posts. In such circumstances, automation becomes essential.

AI enables the analysis of millions of reports within minutes, uncovering patterns that might otherwise go unnoticed. For instance, machine learning-based programs can detect rare adverse effects occurring in specific patient groups, such as the elderly or those with chronic conditions.

A successful example of AI application is the system developed by IBM Watson Health. This system not only analyzes adverse event data but also predicts the likelihood of their occurrence, allowing pharmaceutical companies to adjust drug compositions during the production stage. In 2023, this system identified a rare adverse effect associated with one of the COVID-19 vaccines, enabling timely measures to mitigate risks.

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