Work

AI-Driven Molecular Communication for Targeted Drug Delivery with Adaptive Release Optimization

Year: 2025

Type: article

Abstract: Molecular Communication has emerged as a prominent area of research, particularly for drug-based medical therapies. Nanomachines are utilized to inject drugs (such as anti-inflammatory molecules) into the human body, targeting infected cells through communication technologies. Nevertheless, creating an effective Targeted Drug Delivery (TDD) system that minimizes drug wastage remains a significant challenge. Previous research has tackled various issues, including improper drug delivery and low success rates. These challenges have inspired us to set the goal of accurately delivering drugs to the intended location using molecular Communication in TDD. Furthermore, we propose an AI-enhanced TDD system aimed at achieving improved therapeutic outcomes for a range of conditions, including cancer and heart disease. This research also addresses the problems of high side effects, improper path selection, and inefficient drug delivery. The main objective of this research is to design an advanced targeted drug delivery using molecular Communication. So, we employ Artificial Intelligence (AI) technology for Targeted Drug Delivery with an adaptive Drug Release Rate optimization method (AI-TDD) to overcome the existing issues. We execute a Double Deep Q Network (DDQN)- based adaptive Drug Release method to minimize drug wastage. This method uses biomarker concentrations and timely signal provisioning from external devices and entities. This work’s simulation is performed using Python-based simulations with fine-tuned system and simulation configurations. Our work’s performance assessment is carried out using four major metrics: Delivery Error Analysis, RMSE Analysis, Drug Release Rate Analysis, and Drug Reception Rate Analysis, which shows that our proposed AI-TDD model outperforms the existing model.

Source: International Journal of Electronics and Communication Engineering

DOI: 10.14445/23488549/ijece-v12i8p125

Authors: Harsha Sanap, Vinitkumar Jayaprakash Dongre

Institutions: University of Mumbai, Thakur College of Engineering and Technology

Language: English

Topic: Molecular Communication and Nanonetworks

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: diamond

Funder: University of Mumbai