PANcreatic CAncer Initial Detection via liquid biopsy

Artificial intelligence (AI) is rapidly transforming cancer research and clinical care, offering powerful tools for early detection and precision oncology.

In our latest PANCAID Masterclass, Dr Núria Malats and Sergio Sabroso from CNIO explore how AI is advancing pancreatic cancer research, with a focus on pancreatic ductal adenocarcinoma (PDAC).

This lecture covers:

• Core definitions and applications of AI in cancer research
• Input tools and data modalities, from radiomics to pathomics
• Synthetic data and image generation
• AI-driven integration of liquid biopsy features
• Future perspectives for clinical implementation

The session provides an accessible introduction for cancer researchers, clinicians, and students interested in how data-driven approaches are shaping the future of oncology.

👉 Watch the full Masterclass here.

PANCAID researchers from the Department of Health Economics and Health Services Research at UKE, Hamburg have just published a systematic review in The European Journal of Health Economics, exploring the cost-effectiveness of early detection strategies for pancreatic cancer. A review directly liked to our Work Package 4.

Early detection is often cited as a game-changer in cancer care, but are the strategies, especially in pancreatic cancer, also economically viable? This new publication synthesizes data from 31 studies evaluating various screening and surveillance approaches in high-risk groups. The review found that while some early detection methods appear cost-effective, methodological inconsistencies and reporting gaps complicate definitive conclusions.

Key findings include:

• → Most studies focused on individuals with elevated pancreatic cancer risk (e.g., those with precancerous lesions)
• → Imaging modalities mostly consisted of endoscopic ultrasound, MRI, and CT
• → Results varied: six studies deemed early detection cost-effective, while others were inconclusive or mixed
• → Inconsistent evaluation frameworks highlight the need for more robust and standardized economic analyses

📄 Read the full article here: https://link.springer.com/article/10.1007/s10198-025-01793-4
📚 Citation: Wittram R, Kreis L, König HH, Brettschneider C. Economic evaluations of early detection strategies for pancreatic cancer: a systematic review. Eur J Health Econ. 2025.

Key information 

• Date: 15 October 2025, from 14:00 to 15:00 (CEST). 
• Duration: 60 minutes,  
• Format: Online via Microsoft Teams, registration is mandatory. 

Speakers 

• Federica Zanca (moderator). EIC Program Manager for Medical Imaging and AI in Healthcare for the European Innovation Council and SMEs Executive Agency (EISMEA) 
• John Hermans. Medical Imaging department, Radboud University Medical Center, Nijmegen, The Netherlands. PANCAIM Project Coordinator with Henkjan Huisman. 
• Massimo Alfano. Group Leader at San Raffaele Biomedical Science Park (Milan, Italy). PHIRE Project Coordinator.  
• Núria Malats. Head of the Genetic and Molecular Epidemiology Group at the Spanish National Cancer Research Centre (CNIO). PANCAID leader of WP3: Data Management and AI Analysis  

Abstract 

Early cancer detection is one of the most important challenges in oncology today. This 60-minute webinar will bring together healthcare professionals and researchers from three EU-funded research projects, PHIRE, PANCAIM, and PANCAID, to present different approaches to improving early diagnosis through biotechnology and artificial intelligence in pancreatic and bladder cancer. Through different strategies, the three projects share a common goal: making cancer detection faster, more accurate, and more personalised. 

The discussion will highlight how collaboration between researchers, clinicians, and AI specialists is leading to real-world improvements in healthcare. The speakers will also explore the broader impact of early diagnosis on patient wellbeing, healthcare costs, and innovation in the biotech sector. 

The event will include short project presentations, a panel discussion, and a Q&A session with the audience. Participants will learn about new technologies being developed, such as high-resolution imaging devices, diagnostic tests based on liquid biopsy, and the use of AI to analyse clinical and genomic data.  

The webinar is aimed at medical and biotechnology researchers, physicians, healthcare professionals, organisations supporting cancer patients, and AI experts working in the health sector.  

Register here