# Exploring the Role of Extracellular Vesicles in Pancreatic and Hepatobiliary Cancers: Advances Through Artificial Intelligence

## TL;DR

This paper reviews how artificial intelligence is advancing the use of extracellular vesicles as biomarkers and therapies for pancreatic and liver cancers.

## Contribution

The paper highlights novel AI applications in identifying EV-based biomarkers and accelerating drug development for GI cancers.

## Key findings

- AI enhances biomarker selection from omics data for EV-based diagnostics.
- AI-driven modeling improves drug delivery and target identification in EV research.
- EVs show therapeutic potential through bioengineering and AI support.

## Abstract

Gastrointestinal (GI) cancers constitute an umbrella term for a wide variety of malignancies that are located in the digestive tract (esophageal, gastric, small and large intestine, anus, liver, gallbladder, and pancreas), with 25% of total cancers and 35% of cancer-related deaths being attributed to them. An alarming trend of rising GI malignancy diagnoses, especially in younger age groups, underscores the need for discoveries in liquid-based biomarkers that facilitate both early detection and optimal disease management. Extracellular vesicles (EVs) not only constitute promising nano-sized biomarkers, but also, via bioengineering, have shown a great therapeutic potential, with artificial intelligence (AI) revolutionizing their research via the selection of the best biomarkers from omics, the recognition of pathophysiological patterns, and facilitating a faster drug-development via AI-driven EV engineering, drug delivery modeling, and target identification. In this review, we will provide a clear insight into the implementation of AI methodologies in EV-based biomarker discovery and therapeutics for pancreatic and hepatobiliary cancer.