Microencapsulation drug delivery has the potential to improve drug efficacy, reduce toxicity, contribute to patient compliance and convenience, and even enable new therapies that may have been infeasible to implement otherwise. Multiple designs and manufacturing techniques have been used to fabricate microparticles with a range of sizes and functionality. However, the administration of microparticles and biomaterials via injection holds several challenges. Injectable microparticle formulations have several controlled release drug applications.
The US Food and Drugs Association(FDA) has approved 11 microparticle based drug formulations. There have also been 92 clinical trials globally and 45 in the US on injectable microparticle formulations. High-efficiency transfer of microparticles through the injection can play a key factor in delivering the correct dose to the patient and enable successful clinical translation of particulate drug delivery systems. There is a serious need for the development of models and techniques providing insights into injection efficacy of any arbitrary microparticle system. This study is conducted to contribute to that existing need.
Hypodermic needles are the most assessable option for injection but they present the challenge of clogging in the microparticle drug delivery system. Despite various advancements in drug encapsulation, investigative reports on injection efficacy are few. Therefore, the different parameters causing microparticle clog formation which in turn affects injectability is analysed, when administering particulate biopharmaceutical formulations using a typical syringe attached to a hypodermic needle. In this study, computational simulations were performed on a model 3ml sized syringe containing 2ml of the injection solution. 2 needles of varying sizes were used in the study. A multiphysics model was constructed to numerically study particle transport in a syringe-needle system.
The model coupled CFD with the particle transport system. Injectability was studied further experimentally with a Design of Experiment(DOE) approach. An ANOVA based on the general linear model was used to identify the relative importance of each design factor of injectability from the DOE. An Artificial Neural Network(ANN) was also trained for predicting microparticle injectability. Inspired by a pattern of streamlines and the design of nozzles, a new syringe was designed and manufactured to achieve a high microparticle injectability.
The study provides a comprehensive framework for microparticle injectability through hypodermic syringe needles and techniques that contribute to efficient microparticle delivery. Solution viscosity was found to be the statistically dominant factor followed by particle size and needle size. Increasing viscosity within the proposed range increased injectability. Increasing size of the particles and decreasing size of the needle in general decreased injectability. It was also found that concentrating particles in the centerline of the syringe can improve injectability.
A mathematical formula was proposed to predict the chance of successful injection based on two nondimensional parameters, capturing properties of syringe, needle, and particles. The formula was further supplemented with an ANN, both indicating that a predicted injectability of 60% can be associated with actual injectability of more than 50%. A design framework based on numerical and experimental understanding helped manufacture a cost-effective syringe tailor-made for high injectability. Results of this study can potentially be used in a wide range of applications for parenteral injection of advanced drug delivery carriers and injectable biomaterials, especially subcutaneously, through conventional hypodermic needles, or design of novel drug delivery devices.
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