USA 2024 Congress Sessions

AI in the Lab of the Future

You can now experience some of the AI sessions from Lab of the Future USA 2024, and discover the main themes and takeaways from this year’s event.

Session 1: AI in the Lab of the Future


AI at AbbVie: Moonshot, Woodstock, Watergate, Punk Rock

Brian Martin, Head of AI in R&D Information Research, Research Fellow, AbbVie


Choosing a path forward involves balancing a set of different challenges. This brief talk discusses those challenges and how AbbVie have been approaching them for the past 5+ years in the field of AI research and development.

  • Do you shoot for the moon by investing in novel molecule generators for drug discovery?
  • Do you try and bring everyone together in a “kum ba yah” way to find the path forward?
  • How do you navigate the murky gray waters between opportunity and obligation – reputation and regulation?
  • How do you latch on to the seemingly limitless energy that powers innovation?


Exploiting recent computational advances for drug discovery: A view from the Industry

Christos Nicolaou, Senior Scientific Director, Digital Small Molecule Lead, Novo Nordisk


Christos gives an introduction and background to AI/ML in drug discovery, before speaking on the fundamentals of the drug discovery process, the achievements and challenges for in silico drug discovery at Novo, and the drug discovery cycle progress. Christos also talks on persistent bottlenecks they have come across, and the future outlook.


Making life-science data AI-ready

Abhishek Jha, Co-Founder & CEO, Elucidata


Building an end-to-end data ecosystem to go from data to insights is not trivial. Breaking data silos through seamless data integration, interoperability and provenance is the precursor to driving any successful data initiatives in BioPharma. In this session Dr Abhishek Jha will talk about how Elucidata’s data harmonization engine, Polly is making life-sciences data AI-ready through large scale multi-modal and multi-source data harmonization, high quality data and our differentiated ML-ops services.

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