Panel Discussion Recording
From data access to data readiness:
The next bottleneck in AI-Driven small molecule discovery

AI is advancing rapidly in drug discovery — but is your data ready?

Artificial Intelligence is transforming small molecule drug discovery, but many organizations are discovering that access to data alone is not enough. The quality, structure, context, and readiness of scientific data have become critical factors in determining the success of AI-driven research initiatives.
Watch this expert panel discussion featuring leaders from AI-first biotech, computational chemistry, and pharmaceutical R&D as they explore why data readiness has emerged as one of the most significant challenges in modern drug discovery and how organizations are addressing it.

About the discussion

As AI models become increasingly sophisticated, the focus is shifting from computational power to the quality of the underlying data. Fragmented datasets, inconsistent standards, and disconnected scientific information continue to limit the ability of AI systems to generate reliable and actionable insights.

In this discussion, industry experts share practical perspectives on transforming complex scientific data into AI-ready intelligence that can accelerate discovery workflows and improve research outcomes.

What you’ll learn

• Why data readiness is becoming a critical success factor for AI-driven drug discovery
• The challenges associated with fragmented and siloed scientific data
• Strategies for building integrated, context-rich datasets for AI applications
• How leading biotech and pharmaceutical organizations are improving data quality and accessibility
• Best practices for creating scalable, AI-ready discovery workflows
• The future of data-centric approaches in small molecule discovery