From Target Identification to Clinical Trials — Use Case Deep Dive & Topics for 2027

This end-of-summer seminar takes a longitudinal view of AI across the full drug development pipeline — from the earliest stages of target identification and validation through to clinical trial design and execution. Through in-depth case studies and expert presentations, participants will examine where AI is delivering genuine, measurable value and where significant challenges remain.
 
The second half of the session turns to the future: an open, structured discussion to identify the topics, themes, and use cases that should shape the LSAIE programme in 2027. This is your opportunity to help set the agenda — ensuring the programme remains grounded in the real priorities of the life science community.
 
All members are encouraged to come prepared with use cases, questions, and perspectives from their own organisations.
 

Speakers

• Raul Rodriguez-Esteban, Senior Principal Scientist, Computational Sciences Center of Excellence, Roche (Basel). Patient digital twins built with large language models.
• Aishwarya Pathak, PhD, Clinical Data Scientist, Rancho BioSciences. Data curation across the drug development lifecycle in the age of AI.
• Thomas Wolf, Bayer Crop Science (leads a research program on model uncertainty and active learning), introduced by Suzanne Bach, datavisyn. Prioritizing molecules with learning to rank.
• Yidan Xue, University of Manchester, for the UK Centre of Excellence in In Silico Regulatory Science and Innovation. From mechanistic modeling to credible in silico trials.

  Find out more about the Life Science AI Exchange here.