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LNP-VACCO: Autoencoder-Driven Optimization of Cystic Fibrosis Drug Delivery

AJAS · 2025

Nidhi Yadalam · Oregon Academy of Science

Overview

Cystic Fibrosis (CF), characterized by its profound impact on respiratory and digestive functions, arises due to genetic mutations in the CFTR gene on chromosome 7. Despite progress in medical science, treatments like ivacaftor and lumicaftor offer incomplete restoration of chloride function and are burdened by significant complications and side effects, highlighting an unmet medical need. The emergence of gene editing technologies, particularly those utilizing chemically-modified-mRNA, has shown promise in addressing the underlying genetic mutations associated with CF. Concurrently, Lipid Nanoparticles (LNPs) have revolutionized the pharmaceutical industry, with mRNA-based therapies at the forefront of innovation. However, the formulation of LNPs presents challenges concerning stability and biocompatibility, underscoring the necessity for innovative solutions. In response to these challenges, this research introduces LNP-VACCO, a novel approach that seamlessly integrates cutting-edge technologies such as Variational Autoencoders (VAEs) and Combinatorial Chemistry. By leveraging principles of lipophilicity encoded in Simplified Molecular-Input Line-Entry System (SMILES) strings, LNP-VACCO autonomously navigates the vast landscape of LNP compositions, offering an efficient and systematic exploration of potential formulations. The methodology involves a sophisticated three-step unsupervised deep learning process, wherein the model iteratively refines lipid constituent compositions to optimize LNP performance. Validation experiments conducted in-vitro, involving the synthesis of lipids and subsequent transfection into HeLa mammalian cells to simulate CF conditions, demonstrated promising results in terms of encapsulation efficiency and cell viability. This research represents a significant leap forward in enhancing the efficacy of nanoparticle-based drug delivery systems, offering hope for effective treatments for CF and other genetic disorders.

Competition history

  • AJAS 2025 Category not listed

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Source: AAAS Annual Meeting (Confex) / American Junior Academy of Science

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