INTEGRATING INTELLIGENCE INTO LIFE SCIENCE

Agenda for Advanced AI Training Program for Oncology Clinicians & Researchers

Directed by Dr. Gil Mor and Dr. Ramon Salazar

24 March 2026
Hotel Gallery
Barcelona

About the Workshop

This intensive one-day workshop has been specifically designed for Medical Oncologist Clinicians and Researchers to unlock their full potential for research excellence using AI technology.


The program focuses on advanced applications of generative AI in oncology research.

Participants will learn advanced prompt engineering techniques, develop custom AI agents for specific research oncology workflows like literature search, summarizing complex scientific biological networks, preparing clinical protocols, draft reports and creating powerful knowledge AI libraries that transform how they conduct research.

The participants will also practice on real scientific & operational use cases.

Program

09:00 - 09:30
Session 1: Sign-up to leading AI models

Sign up to leading AI models to ensure every participant can practice hands-on throughout the workshop.

  • Assistance to setting up leading AI models like ChatGPT, Claude, Gemini, NotebookLM, and Perplexity to your laptops and mobile devices.
  • Quick orientation to interfaces, file uploads, context windows, multimodal features.
  • Preparing each participant’s workspace for the practice during the day.
09:30 - 10:00
Session 2: Introduction to AI in Medicine & Essential Tools

An introduction to AI capabilities in the research work.

  • How AI Can Impact Oncology? Exploring real-world use cases in oncology and identifying strategic opportunities to implement AI technology to oncology workflow.
  • How AI Works? Understanding large language models capabilities and limitations.
10:00 - 11:00
Session 3: Prompt Engineering & Interactive Problem-Solving

Real Clinical Case Practice

  • Learn how to craft precise and detailed prompts to improve the relevance and accuracy of AI-generated outputs.
  • We will cover methods to reduce system hallucination to maximize output quality.
  • Learn how to train AI systems with your own documents and your personal knowledge.
11:00 - 11:15
Coffee break
11:15 - 12:15
Session 4: Developing Task-Specific AI Agents

Learn to design and train AI agents to perform expert-level tasks across oncology domains.

  • Learn how agents can gather and analyze data based on your internal documents, knowledge sources, and real-world tasks.
  • Understand how to build AI agents (GPTs).
12:15 - 13:45
Session 5: Creating Intelligent Library Environments

Turn documents, articles, laboratory notebooks, protocols and reports into an organized, intelligent knowledge system powered by AI.

  • Learn how to develop AI-driven knowledge libraries.
  • Learn to generate audio and video representations of scientific documents, enabling researchers to consume complex material through interactive formats.
  • Extract insights, discover more relevant sources, and identify key connections across documents.
  • Generate visual representations of complex biological topics.
13:45 - 14:30
Lunch break
14:30 - 16:45
Session 6: Practicing on Real Scientific & Operational Use Cases

This session introduces a set of practical exercises. Pure hands-on problem solving by the participants on real examples

Potential use cases:

  • Replying to Email.
  • Article Summarization.
  • Create presentation (PPTX) and one-pager poster for a conference.
  • Search for evidence-based investigation into innovative Phase I trial designs
  • Protocol drafting to support the clinical professionals
  • Literature search guidance
  • Manuscript preparation using AI


All exercises are delivered through hands-on practice. Participants can bring specific use-case to practice real problems.

16:45 - 17:00
Coffee break
17:00 - 18:00
Session 7: Peer Learning and Closing Discussion
  • Participants demonstrate their use cases solutions to the group. See how peers approached the same challenges differently and learn from each other’s.
  • Final 15 minutes for questions and wrap-up.