Automated Micro-Scale Manufacturing of PLGA-Based Drug-Eluting Stents via Dielectrophoresis and Real-Time AI-Driven Parameter Optimization

**Abstract:** This paper presents a novel system for the automated, high-throughput manufacturing of PLGA-based drug-eluting stents with precisely controlled drug release profiles. Utilizing dielectrophoresis (DEP) for particle assembly onto stent scaffolding and integrated with a real-time AI-driven parameter optimization loop, the system allows for rapid prototyping and production of stents tailored to specific drug formulations and release requirements. The approach significantly reduces manufacturing time, improves consistency, and enables the incorporation of complex, multi-drug delivery systems. This technology presents a substantial advancement in interventional cardiology, offering the potential to personalize stent therapies and improve patient outcomes. The framework is designed for immediate commercialization by combining established DEP principles with advanced iterative optimization algorithms.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-17
DOI
https://doi.org/10.5281/zenodo.16889817
Primary Topic
Theoretical and Computational Physics
Type
article
Field-Weighted Citation Impact
0.00
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article

Automated Micro-Scale Manufacturing of PLGA-Based Drug-Eluting Stents via Dielectrophoresis and Real-Time AI-Driven Parameter Optimization

Zenodo (CERN European Organization for Nuclear Research)
Theoretical and Computational Physics
article

Automated Micro-Scale Manufacturing of PLGA-Based Drug-Eluting Stents via Dielectrophoresis and Real-Time AI-Driven Parameter Optimization

article en

Abstract

**Abstract:** This paper presents a novel system for the automated, high-throughput manufacturing of PLGA-based drug-eluting stents with precisely controlled drug release profiles. Utilizing dielectrophoresis (DEP) for particle assembly onto stent scaffolding and integrated with a real-time AI-driven parameter optimization loop, the system allows for rapid prototyping and production of stents tailored to specific drug formulations and release requirements. The approach significantly reduces manufacturing time, improves consistency, and enables the incorporation of complex, multi-drug delivery systems. This technology presents a substantial advancement in interventional cardiology, offering the potential to personalize stent therapies and improve patient outcomes. The framework is designed for immediate commercialization by combining established DEP principles with advanced iterative optimization algorithms.

Zenodo (CERN European Organization for Nuclear Research)
Freed–Hardeman University (US)
Openalex Percentile: Top 58%
Theoretical and Computational Physics
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