Ensuring Integrity in AI-Driven Pharmacovigilance
Prasanthi Sadhu, Editor, Pharma Focus Asia
As the pharmaceutical industry accelerates AI adoption, it is becoming increasingly clear that trust is the currency of the future. From drug discovery to patient engagement, AI is reshaping how we understand diseases, predict risks, and deliver life-saving therapies. Yet nowhere is the need for trustworthy AI more crucial than in pharmacovigilance—where decisions made by algorithms can directly influence patient safety, regulatory confidence, and overall public health.
Today’s advanced AI models can analyze millions of data points drawn from clinical trials, real-world evidence, social media, and electronic health records. They are capable of detecting early safety signals, revealing patterns that could literally be impossible to spot manually, and dramatically improving the speed and precision of safety monitoring. Yet with this powerful potential comes an equally significant responsibility.
Challenges such as hallucinations, data bias, incomplete datasets, and opaque model behaviour cannot be overlooked. Left unaddressed, they threaten not only the reliability of safety insights but also the confidence of healthcare professionals, regulators, and most importantly, the patient health & safety.
This issue explores how pharma leaders, data scientists, regulators, and technology partners are working together to build AI systems that are transparent, reliable, and ethically grounded. We examine strategies to detect and mitigate model hallucinations, approaches to ensure data diversity and equity, frameworks for responsible AI governance, and the growing importance of human-in-the-loop validation. The goal is not simply to adopt AI, but to do that wisely, with accountability, clarity, and constant moderation.
Building trustworthy AI is not a one-time initiative; it is a long-term commitment. It demands cross-functional collaboration, rigorous validation, and a culture that embraces both innovation and ethical responsibility. As the industry advances toward more automated and intelligent safety ecosystems, our collective focus must remain on safeguarding patients and deriving true value out of the technologies we use.
An article titled ‘Toward Trustworthy AI in Pharma - Managing hallucination and bias in pharmacovigilance’ by John Praveen, Vice President, Pharmacovigilance & Medical Writing Account Delivery & PV Shared Services Offering (SSO) Lead, Accenture Solution Pvt Ltd. narrates the integration of generative AI (GenAI) in pharmacovigilance streamlines processes such as adverse event detection and data analysis. It also outlines the issues and challenges involved in the process.
I hope this edition provides valuable insights and practical perspectives to help your organisation navigate the path toward safe, transparent, and bias-aware AI in pharmacovigilance. Together, we can shape a future where AI enhances the trust in global healthcare.
Author Bio
Prasanthi Sadhu, Editor, Pharma Focus Asia
