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Four-Dimensional Printed Construct from Temperature-Responsive Self-Folding Feedstock for Pharmaceutical Applications

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Summary

This study introduces a novel 4D printed drug delivery system using thermo-responsive materials and machine learning. The system demonstrates precise, environment-responsive drug release, paving the way for advanced therapeutics.

Keywords:
4D constructdrug deliverymachine learningsmart materials

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Area of Science:

  • Biomaterials Engineering
  • Drug Delivery Systems
  • Additive Manufacturing

Background:

  • Four-dimensional (4D) printing offers autonomous control over drug release based on physiological conditions.
  • Thermo-responsive materials are key to developing smart drug delivery devices.

Purpose of the Study:

  • To develop and evaluate a 4D printed construct using a novel thermo-responsive self-folding feedstock for controlled drug delivery.
  • To utilize machine learning (ML) for optimizing the shape recovery behavior of the 4D printed construct.

Main Methods:

  • Synthesis of a novel thermo-responsive self-folding feedstock.
  • Fabrication of 4D printed constructs using SSE-mediated 3D printing.
  • Shape memory programming and recovery at specific temperatures (50°C, 4°C, 37°C).
  • Machine learning modeling for batch optimization of shape recovery.
  • Drug loading with paracetamol (PCM) and *in vitro* drug release studies.

Main Results:

  • The 4D printed construct achieved a shape recovery ratio of 97.41% after ML-based optimization.
  • High entrapment efficiency of 98.11 ± 1.5% for paracetamol.
  • *In vitro* studies showed near-complete drug release (100% ± 4.19%) within 4 hours at gastric pH, demonstrating temperature-responsive behavior.

Conclusions:

  • The developed 4D printing strategy enables independent control of drug release in response to physiological environments.
  • This technology holds significant potential for creating advanced, personalized drug delivery devices.