Can predictive modeling improve pharmacovigilance?

Pharmacovigilance has historically relied on post-marketing surveillance and adverse event reporting systems.

With access to longitudinal healthcare data, we now have opportunities to:

• Identify early safety signals
• Model polypharmacy interaction networks
• Detect high-risk patient clusters
• Monitor prescribing pattern drift
• Integrate lab trends into toxicity prediction

What methodologies have you used (or seen) for proactive drug safety analytics?

• Survival analysis?
• Time-series anomaly detection?
• Causal inference models?
• Network analysis?

Let’s explore how AI can enhance medication safety without overburdening clinicians.

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