Targeted Nanoparticle Delivery via Bio-Responsive Peptide-Conjugated Liquid Crystalline Elastomers: A Mechanistic and Predictive Framework

**Abstract:** This paper proposes a novel drug delivery system employing peptide-functionalized liquid crystalline elastomers (LCEs) encapsulated within biocompatible nanoparticles for targeted drug release in response to microenvironmental stimuli. The system leverages the intrinsic shape memory properties of LCEs coupled with the bio-recognition capabilities of peptides to achieve precise drug delivery at the target site. A comprehensive mechanistic framework, incorporating both continuum mechanics and molecular dynamics, alongside machine learning-driven predictive models, is presented to optimize nanoparticle design and peptide conjugation, maximizing drug efficacy while minimizing off-target effects. This system holds significant potential for improving cancer therapy, regenerative medicine, and other targeted drug applications.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-21
DOI
https://doi.org/10.5281/zenodo.17171097
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Targeted Nanoparticle Delivery via Bio-Responsive Peptide-Conjugated Liquid Crystalline Elastomers: A Mechanistic and Predictive Framework

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Targeted Nanoparticle Delivery via Bio-Responsive Peptide-Conjugated Liquid Crystalline Elastomers: A Mechanistic and Predictive Framework

article en

Abstract

**Abstract:** This paper proposes a novel drug delivery system employing peptide-functionalized liquid crystalline elastomers (LCEs) encapsulated within biocompatible nanoparticles for targeted drug release in response to microenvironmental stimuli. The system leverages the intrinsic shape memory properties of LCEs coupled with the bio-recognition capabilities of peptides to achieve precise drug delivery at the target site. A comprehensive mechanistic framework, incorporating both continuum mechanics and molecular dynamics, alongside machine learning-driven predictive models, is presented to optimize nanoparticle design and peptide conjugation, maximizing drug efficacy while minimizing off-target effects. This system holds significant potential for improving cancer therapy, regenerative medicine, and other targeted drug applications.

Zenodo (CERN European Organization for Nuclear Research)
Freed–Hardeman University (US)
Good health and well-being
Openalex Percentile: Top 32%
Geochemistry and Geologic Mapping
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.