A Nanoporous 3D-Printed Scaffold for Local Antibiotic Delivery.
Pouyan AhangarJialiang LiLeslie S NkindiZohreh MohammadrezaeeMegan E CookePaul A MartineauMichael H WeberElie SaadeNima NateghiDerek H RosenzweigPublished in: Micromachines (2023)
Limitations of bone defect reconstruction include poor bone healing and osteointegration with acrylic cements, lack of strength with bone putty/paste, and poor osteointegration. Tissue engineering aims to bridge these gaps through the use of bioactive implants. However, there is often a risk of infection and biofilm formation associated with orthopedic implants, which may develop anti-microbial resistance. To promote bone repair while also locally delivering therapeutics, 3D-printed implants serve as a suitable alternative. Soft, nanoporous 3D-printed filaments made from a thermoplastic polyurethane and polyvinyl alcohol blend, LAY-FOMM and LAY-FELT, have shown promise for drug delivery and orthopedic applications. Here, we compare 3D printability and sustained antibiotic release kinetics from two types of commercial 3D-printed porous filaments suitable for bone tissue engineering applications. We found that both LAY-FOMM and LAY-FELT could be consistently printed into scaffolds for drug delivery. Further, the materials could sustainably release Tetracycline over 3 days, independent of material type and infill geometry. The drug-loaded materials did not show any cytotoxicity when cultured with primary human fibroblasts. We conclude that both LAY-FOMM and LAY-FELT 3D-printed scaffolds are suitable devices for local antibiotic delivery applications, and they may have potential applications to prophylactically reduce infections in orthopedic reconstruction surgery.
Keyphrases
- tissue engineering
- drug delivery
- soft tissue
- bone mineral density
- biofilm formation
- bone loss
- endothelial cells
- bone regeneration
- cancer therapy
- pseudomonas aeruginosa
- escherichia coli
- minimally invasive
- emergency department
- staphylococcus aureus
- postmenopausal women
- coronary artery disease
- body composition
- percutaneous coronary intervention
- atrial fibrillation
- cystic fibrosis
- big data
- drug release
- climate change
- acute coronary syndrome
- machine learning
- deep learning
- mass spectrometry
- tandem mass spectrometry
- solid phase extraction