Proof of concept of a predictive model of drug release from long-acting implants obtained by fused-deposition modeling

Manini, Giuseppe; Benali, Samira; Raquez, Jean‐Marie; Goole, Jonathan

doi:10.1016/j.ijpharm.2022.121663

Cited by 8 publications

(4 citation statements)

References 27 publications

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“…Given the multifactorial nature of HME and FDM 3DP, conventional systemic methods of evaluating each input variable on printing success (i.e., based on design of experiments) can be time-consuming. The large amount of data derived from almost a decade of pharmaceutical 3D printing research contains critical yet convoluted information that could accelerate formulation development if structured and unraveled ( Crișan et al, 2022 ; Elbadawi et al, 2021c ; Manini et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Accelerating 3D printing of pharmaceutical products using machine learning

Ong

Castro

Gaisford

et al. 2022

International Journal of Pharmaceutics: X

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Section: Introductionmentioning

confidence: 99%

Accelerating 3D printing of pharmaceutical products using machine learning

Ong

Castro

Gaisford

et al. 2022

International Journal of Pharmaceutics: X

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“…In a study by Manini et al, higher porosity and surface/volume ratios were observed for scaffolds with lower infill densities, thus providing a higher burst release. As the infill density decreased, the number of printed meshes decreased, and the area of pores created by the printed material became larger [ 47 ]. The findings from the current study were also in line with the initial hypothesis of this research that the infill density has a major impact on the drug release behavior and, thereby, the overall performance of the 3D-printed scaffolds.…”

Section: Resultsmentioning

confidence: 99%

“…As shown in Figure 10 B, scaffolds with smaller wall thickness (1 mm) had a higher percentage of drug release compared to thicker scaffolds (3 mm). The layer thickness has been reported to impact the mechanical strength of 3D-printed structures [ 51 ] and influence drug release [ 47 , 49 , 52 ]. In a study by Yang et al, the impact of shell thickness on the release of ibuprofen was studied.…”

Section: Resultsmentioning

confidence: 99%

Three-Dimensional Printing of Drug-Eluting Implantable PLGA Scaffolds for Bone Regeneration

Annaji,

Mita,

Poudel

et al. 2024

Bioengineering

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Despite rapid progress in tissue engineering, the repair and regeneration of bone defects remains challenging, especially for non-homogenous and complicated defects. We have developed and characterized biodegradable drug-eluting scaffolds for bone regeneration utilizing direct powder extrusion-based three-dimensional (3D) printing techniques. The PLGA scaffolds were fabricated using poly (lactic-co-glycolic acid) (PLGA) with inherent viscosities of 0.2 dl/g and 0.4 dl/g and ketoprofen. The effect of parameters such as the infill, geometry, and wall thickness of the drug carrier on the release kinetics of ketoprofen was studied. The release studies revealed that infill density significantly impacts the release performance, where 10% infill showed faster and almost complete release of the drug, whereas 50% infill demonstrated a sustained release. The Korsmeyer–Peppas model showed the best fit for release data irrespective of the PLGA molecular weight and infill density. It was demonstrated that printing parameters such as infill density, scaffold wall thickness, and geometry played an important role in controlling the release and, therefore, in designing customized drug-eluting scaffolds for bone regeneration.

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“…Without the aid of in vitro testing, however, predicting the performance of implants with new drug formulations, polymer compositions, or dimensions can prove challenging. A predictive model can inform how the properties of the drug and polymer affect performance and further guide the design of the implant to achieve a target release profile [ 35 , 36 , 37 ]. Such a predictive model will allow the rapid selection of implant parameters without the need to perform extensive in vitro testing, therefore significantly reducing the time and cost associated with in vitro product development efforts.…”

Section: Introductionmentioning

confidence: 99%

Reservoir-Style Polymeric Drug Delivery Systems: Empirical and Predictive Models for Implant Design

Lee

Cruz

et al. 2022

Pharmaceuticals

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Controlled drug delivery systems can provide sustained release profiles, favorable pharmacokinetics, and improved patient adherence. Here, a reservoir-style implant comprising a biodegradable polymer, poly(ε-caprolactone) (PCL), was developed to deliver drugs subcutaneously. This work addresses a key challenge when designing these implantable drug delivery systems, namely the accurate prediction of drug release profiles when using different formulations or form factors of the implant. The ability to model and predict the release behavior of drugs from an implant based on their physicochemical properties enables rational design and optimization without extensive and laborious in vitro testing. By leveraging experimental observations, we propose a mathematical model that predicts the empirical parameters describing the drug diffusion and partitioning processes based on the physicochemical properties of the drug. We demonstrate that the model enables an adequate fit predicting empirical parameters close to experimental values for various drugs. The model was further used to predict the release performance of new drug formulations from the implant, which aligned with experimental results for implants exhibiting zero-order release kinetics. Thus, the proposed empirical models provide useful tools to inform the implant design to achieve a target release profile.

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Proof of concept of a predictive model of drug release from long-acting implants obtained by fused-deposition modeling

Cited by 8 publications

References 27 publications

Accelerating 3D printing of pharmaceutical products using machine learning

Accelerating 3D printing of pharmaceutical products using machine learning

Three-Dimensional Printing of Drug-Eluting Implantable PLGA Scaffolds for Bone Regeneration

Reservoir-Style Polymeric Drug Delivery Systems: Empirical and Predictive Models for Implant Design

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