AI is transforming pharma and healthcare, from accelerating drug discovery to improving diagnostics. With this power comes a critical challenge: ensuring AI-driven decisions are fair, unbiased, and trustworthy. Studies show that biased AI models in healthcare have resulted in black patients receiving nearly 20% less care than white patients with the same health conditions. Without proactive measures, AI risks perpetuating disparities rather than closing the gaps in healthcare access and treatment.

Join our panel discussion on Responsible AI to explore practical solutions for building fair, accountable AI systems.

Key discussion points include:

• Transparency & Explainability: Best practices for making AI decisions interpretable and accountable to clinicians, regulators, and patients.
• Inclusive AI Development: Ensuring AI models are trained on diverse, representative datasets to improve healthcare equity.
• Building Public & Physician Trust: Strategies for increasing confidence in AI-driven decisions and demonstrating responsible AI leadership.

Join Sebastian Sbirna, Data Governance Lead in GlobalData & AI, to explores Novo Nordisk’s approach to data governance in its commercial pharmaceutical operations, focusing on how robust data management enables strategic data-driven decision-making. Key Discussion Points

• Data management complexities in the commercial functions of large-scale pharma
• Strategic objectives for advancing analytics capabilities and ensuring comprehensive data transparency
• Methodology for rolling out operational Data Governance - moving from proof-of-concept pilots to global deployment
• Key enablers and lessons learned