Comparative Evaluation of Electronic Syringe and Pan Coating Techniques for Loading of FDM 3D Printed Tablets

<b>Background/Objectives</b>: 3D printing, particularly fused deposition modeling (FDM), is an emerging technology in pharmaceutical manufacturing, enabling the customization of dose or release rate to individual patient needs. However, finding the appropriate loading method to ensure the stability of the drug and achieve the targeted dose may be challenging. Furthermore, the drug utilization of most loading methods is poor, which results in considerable waste production and increased environmental burden. This study aimed to compare two post-printing drug-loading techniques: electronic syringe deposition and pan coating on FDM-printed polylactic acid (PLA) tablets. PLA is a biodegradable and biocompatible polymer that is widely used in this field due to its mechanical strength and regulatory approval. <b>Methods</b>: Tablets with honeycomb-shaped infill (30% and 60% infill densities) were fabricated using PLA filaments, followed by loading with a 15% paracetamol solution via either electronic syringe deposition or pan coating. The resulting tablets were assessed for drug content, weight variation, friability%, surface morphology (SEM), drug distribution (Raman mapping), solid-state characteristics (DSC and FTIR), and dissolution performance. <b>Results</b>: The results indicated that pan coating and electronic syringe deposition offered drug utilization up to 88% and 91.7%, respectively, which is superior to conventional soaking methods. Nevertheless, there is a significant difference in drug loading and release rate: pan coating yielded up to 10.14% drug loads and fast release (over 80% in 30 min), while electronic syringe deposition showed lower drug loading up to 4.8% and slower release (less than 80% within 60 min), which could be associated with better mechanical film integrity and higher precision. Both methods met USP standards with a weight loss of less than 1% and maintained the drug's crystalline state and compatibility with PLA. <b>Conclusions</b>: FDM combined with controlled post-printing drug loading presents a rapid, cost-effective, and flexible novel approach for manufacturing personalized immediate-release tablets, with pan coating potentially being more suitable for commercial scalability and electronic syringe offering precise dosing for personalized therapies.

Authors

Institutions

Publication Details

Journal
Pharmaceuticals
Published
2026-03-02
DOI
https://doi.org/10.3390/ph19030411
Primary Topic
3D Printing in Biomedical Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparative Evaluation of Electronic Syringe and Pan Coating Techniques for Loading of FDM 3D Printed Tablets

Yusra Ahmed, Krisztina Ludasi, Krisztián S. Kovács, Tamás Sovány et al.
Pharmaceuticals
3D Printing in Biomedical Research
article

Comparative Evaluation of Electronic Syringe and Pan Coating Techniques for Loading of FDM 3D Printed Tablets

Yusra Ahmed, Krisztina Ludasi, Krisztián S. Kovács, Tamás Sovány, Orsolya Jójárt-Laczkovich
article en

Abstract

<b>Background/Objectives</b>: 3D printing, particularly fused deposition modeling (FDM), is an emerging technology in pharmaceutical manufacturing, enabling the customization of dose or release rate to individual patient needs. However, finding the appropriate loading method to ensure the stability of the drug and achieve the targeted dose may be challenging. Furthermore, the drug utilization of most loading methods is poor, which results in considerable waste production and increased environmental burden. This study aimed to compare two post-printing drug-loading techniques: electronic syringe deposition and pan coating on FDM-printed polylactic acid (PLA) tablets. PLA is a biodegradable and biocompatible polymer that is widely used in this field due to its mechanical strength and regulatory approval. <b>Methods</b>: Tablets with honeycomb-shaped infill (30% and 60% infill densities) were fabricated using PLA filaments, followed by loading with a 15% paracetamol solution via either electronic syringe deposition or pan coating. The resulting tablets were assessed for drug content, weight variation, friability%, surface morphology (SEM), drug distribution (Raman mapping), solid-state characteristics (DSC and FTIR), and dissolution performance. <b>Results</b>: The results indicated that pan coating and electronic syringe deposition offered drug utilization up to 88% and 91.7%, respectively, which is superior to conventional soaking methods. Nevertheless, there is a significant difference in drug loading and release rate: pan coating yielded up to 10.14% drug loads and fast release (over 80% in 30 min), while electronic syringe deposition showed lower drug loading up to 4.8% and slower release (less than 80% within 60 min), which could be associated with better mechanical film integrity and higher precision. Both methods met USP standards with a weight loss of less than 1% and maintained the drug's crystalline state and compatibility with PLA. <b>Conclusions</b>: FDM combined with controlled post-printing drug loading presents a rapid, cost-effective, and flexible novel approach for manufacturing personalized immediate-release tablets, with pan coating potentially being more suitable for commercial scalability and electronic syringe offering precise dosing for personalized therapies.

PharmaceuticalsVol. 19(3)
University of Szeged (HU), Sudan University of Science and Technology (SD)
Openalex Percentile: Top 39%
3D Printing in Biomedical Research
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.