AI Summit

This session brings together leaders from pharma, AI technology, life sciences platforms, CROs, and specialized biotech AI to cut through the noise and examine how artificial intelligence is delivering tangible value in biopharma today. Panelists will explore the evolution from AI pilots to scaled implementation, sharing concrete examples of where AI is meaningfully accelerating drug discovery, im ...

Within the Asia Pacific Region, Google Health and Health2Sync have partnered with Taiwan's National Health Insurance Administration and AI to stratify diabetes patients at risk of complications and then provide personalized digital interventions to improve outcomes. In Singapore, both Google Health and Health2Sync are developing software that will help citizens better manage hypertension and pre-d ...

Generative genomics, using generative AI models to create entirely new, high-fidelity genomic data, represents a major shift in how we understand and apply biology. Large-scale AI models trained on genomic and transcriptomic data enable researchers to predict biological behavior before running an experiment - accelerating discovery, improving clinical decision-making, and enabling more efficient d ...

As technology evolves and AI requires more data to improve R&D productivity, the question largely becomes how much do we need versus how much do we want and subsequently, what are the unintended risks? For example, hospital data has already been held for ransom hundreds of times and AI companies are issuing warnings about their own tools empowering hackers. Creating biomedical data, whether it be ...

This session will explore how quantum computing is poised to redefine the frontiers of drug discovery by solving complex molecular and optimization problems that exceed the limits of classical computing. Leading experts in AI-driven drug design, quantum algorithms, and computational chemistry will discuss how emerging quantum methods can accelerate target identification and compound optimization. ...

Clinical trials for large-population diseases face persistent challenges and remain the most complex and resource-intensive steps in drug development. Patient recruitment often lags, administrative bottlenecks delay study timelines, and operational inefficiencies that span into patient services and safety can hinder data quality and regulatory compliance. Agentic AI – intelligent systems capable o ...