Join Dr. Tom Williams, Senior Manager, Product Innovation at Elsevier, to see how Elsevier’s scientific connectors bring curated scientific data into the AI tools and agents your teams already use.

Before any AI tool can help with a compound or target, someone has to answer a basic question: what is it, when every system calls it something different? What’s already known about it, and can you trust what the tool tells you? In drug R&D, the answer depends on getting the basics right, with evidence that is comparable and traceable to its source. Dr. Tom Williams shares what Elsevier learned from building an agentic research platform, why the path to the evidence mattered as much as the AI itself, and how Elsevier’s scientific connectors bring curated, source-linked data into the tools and agents your teams already use.

What you’ll see:

• Lessons learned from building an agentic research platform across scientific data sources


• Why orchestration worked, but the path to dependable evidence did not


• How scientific connectors resolve identity, normalize evidence, and preserve links to sources


• Practical examples across chemistry, pharmacokinetics, drug safety, and literature


• How this evidence layer can support AI tools and agents in your own environment

Who should join
Anyone in pharma R&D exploring AI for drug discovery and development, including scientists, informatics and data science teams, and R&D decision-makers

Availability note: Elsevier connectors are available through enterprise licensing.