Optimizing Targeted Drug Delivery Using LSTM and TLR-Enhanced Molecular Communication in Cancer Therapy

International Journal of Electrical and Electronics Engineering

© 2024 by SSRG - IJEEE Journal

Volume 11 Issue 6

Year of Publication : 2024

Authors : Ashwini Katkar, Vinitkumar Dongre

10.14445/23488379/IJEEE-V11I6P125

How to Cite?

Ashwini Katkar, Vinitkumar Dongre, "Optimizing Targeted Drug Delivery Using LSTM and TLR-Enhanced Molecular Communication in Cancer Therapy," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 6, pp. 234-241, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I6P125

Abstract:

In cancer treatment, the continuous aim is to find innovative solutions that effectively target malignant cells while limiting harm to healthy tissues. Molecular Communication (MC) has developed as a promising approach for targeted drug delivery, but congestion issues often hamper it. This study introduces a novel framework that combines Long Short-Term Memory (LSTM) congestion control with Toll-Like Receptor (TLR) feedback mechanisms to enhance drug delivery efficiency in cancer therapy. Using COMSOL simulations to determine congestion angles, LSTM models are trained, giving an accuracy rate of 97.75%. Through extensive computational modeling, the proposed approach significantly reduces congestion and improves the targeting and elimination of cancer cells. This research represents a key advancement in cancer treatment, enabling the precise, safe, and efficient delivery of drugs directly to cancer cells.

Keywords:

Cancer cell, Drug delivery, LSTM, Molecular Communication, Targeted drug.

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