Nano-Bioadhesives for Gastrointestinal Hemostasis and Healing: Integrating Artificial Intelligence for Precision Design and Application.
TL;DR
Predictive, multiobjective materials design is identified as the AI domain most critical for GI nanobioadhesives because adhesion, hemostasis, degradation, biosafety, and healing must be optimized simultaneously.
Abstract
Gastrointestinal (GI) bleeding and mucosal injury remain clinically challenging because most bioadhesives lose performance under acidic, enzymatic, and peristaltic conditions. Nanotechnology has advanced adhesive design by enhancing mechanical integrity, degradation control, and antimicrobial activity; however, translating these gains into consistently favorable clinical outcomes is still difficult. Artificial intelligence (AI) offers a route to accelerate and derisk development. Here, we identify predictive, multiobjective materials design as the AI domain most critical for GI nanobioadhesives because adhesion, hemostasis, degradation, biosafety, and healing must be optimized simultaneously. Predictive modeling, molecular simulations, and high-throughput experimentation enable rational control of adhesion strength, degradation kinetics, and biocompatibility, while machine-learning models expedite the discovery of optimal polymeric nanoparticle formulations. Emerging strategies such as digital twins and closed-loop optimization further support patient-specific and adaptive adhesive systems. By integrating AI-guided design with nanotechnology platforms, next-generation GI bioadhesives could unify rapid hemostasis, antimicrobial protection, and regenerative functions, thereby improving reliability and clinical translation. This review outlines the synergy between AI and nanotechnology and highlights priorities for advancing GI adhesive therapies from bench to bedside.