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Lab Futures Forum

November 2024 recording:
Building Lab-in-the-Loop ecosystems: from concept to application

Rui S. Campos kicks things off by sharing Automata’s groundbreaking vision for cloud-first and lab-in-the-loop applications. Then, Tomasz Jetka, PhD, Director of AI at Ardigen, dives into the practical steps and real-world applications of building lab-in-the-loop data ecosystems. Tomasz draws on over a decade of experience, showcasing successful collaborations with pharma and biotech—from target identification to lab automation. The session wraps up with an insightful fireside chat between Rui and Tomasz, packed with valuable insights, followed by an engaging audience Q&A.

October 2024 recording:
Validating in-silico drug design with Quantum and AI

Watch to explore the intersection of AI and physics-based models with David Wright, CTO of Kuano. The discussion explores how these tools revolutionise drug design, whether AI is enough, or if quantum-inspired approaches are needed. We cover automation as data engines with Russ Green, and a Q&A led by Daniel Siden featuring experts from Kuano and Automata.

September 2024 recording:
​Using AI to predict structures or generate molecules in drug R&D

Join us as we welcome David Ruau, NVIDIA’s Alliance Lead for Pharma in EMEA. NVIDIA’s groundbreaking work in GPU-accelerated computing is revolutionising drug R&D, with platforms like Clara for Drug Discovery and BioNeMo leading the charge.

In this session, David will explore how AI is being used to predict molecular structures, generate novel molecules, and accelerate early drug discovery through advanced computational tools.

August 2024 recording:
Data processing pipeline for AI-driven discovery

In this session, we had the pleasure of speaking to Jesse Johnson, the founder and CEO of Merelogic, a biotech company focused on transforming research data into actionable insights through innovative AI-powered tools.

Watch to find out how data cleaning, normalisation, and feature engineering are essential steps to prepare datasets for AI applications. Through their presentations, Joao and Jesse discuss how the integration of various tools and techniques is used to streamline the process and enable more accurate and efficient AI model training.