Selective laser sintering for 3D printing of medications

Suboptimal treatment caused by inaccurate dosing of prescribed medications is a challenging issue for the pharmaceutical industry. As a result, certain groups of patients, especially pediatric patients, may suffer from a lack of specific dosage forms, leading to potential side effects. To address this issue, various manipulation techniques are being applied, such as tablet crushing, splitting, and solution preparations. Unfortunately, these methods lack accuracy and economic efficiency. 3D printing technology has been considered one of the potential solutions for manufacturing limited batch dosage forms. Dosage forms produced through 3D printing can be fabricated on demand for specific patients. Furthermore, the unique properties of these dosage forms, such as API amorphization, can be adjusted due to the high tunability of the 3D printing process. The work conducted in this thesis is dedicated to investigating the potential applications of Selective Laser Sintering (SLS) and the associated aspects of this method for manufacturing solid dosage forms. The investigations into printing parameters and formulation content enabled the establishment of correlations between these factors and the properties of the final dosage forms. Higher print temperature, Laser Power Ratio, and colorant concentration led to increased mass and hardness of the dosage forms. The polymer constitutes the major portion of the formulation in terms of mass. Consequently, various grades of polymer were examined to ascertain their chemical influence on the properties of the dosage forms. The findings revealed that the type of polymer, degree of hydrolysis, and dynamic viscosity of the polymer significantly impact both the dissolution rate and API amorphization. Utilizing FDM for printing the shell component of the drug delivery device improved its durability, whereas the SLS-printed insert resulted in a faster and adjustable dissolution rate. This experiment showcased the potential of combining the advantages of each technique to produce dosage forms with additional features. A thermal image analysis device was developed and employed to monitor temperature conditions throughout the printing process. The outcomes demonstrated that the collected data could be utilized for in-process quality control objectives and serve as a dataset for machine learning algorithms. This capability allows for real-time process monitoring, defect detection, and automated process refinement. In conclusion, a comprehensive study was conducted on the application of SLS and its limitations. This study will hopefully pave the way for further discussions and the implementation of this technology