3D-Printed Gastroretentive Sustained Release Drug Delivery System by Applying Design of Experiment Approach

• Published in: Molecules (Basel, Switzerland) Switzerland), 2020-05, Vol.25 (10), p.2330
• Main Authors: Jeong, Hyeon Myeong, Weon, Kwon-Yeon, Shin, Beom Soo, Shin, Soyoung
• Format: Article
• Language: English
• Subjects: 3-D printers; 3D printing; Baclofen; Baclofen - chemistry; Controlled release; Delayed-Action Preparations - chemistry; Design of experiments; Design optimization; Dissolution; Drug Carriers - chemistry; Drug delivery; drug delivery system; Drug delivery systems; Drug development; Drug dosages; Drug Liberation; Factor Analysis, Statistical; Factorial design; floating system; Fused deposition modeling; Humans; Kinetics; Muscle Relaxants, Central - chemistry; Oral administration; Patient compliance; Polymers; Printing, Three-Dimensional - instrumentation; Regulatory approval; Solutions; Stomach; Sustained release; Tablets
• ISSN: 1420-3049; 1420-3049
• DOI: 10.3390/molecules25102330

This study aimed to develop a novel oral drug delivery system for gastroretentive sustained drug release by using a capsular device. A capsular device that can control drug release rates from the inner immediate release (IR) tablet while floating in the gastric fluid was fabricated and printed by a fused deposition modeling 3D printer. A commercial IR tablet of baclofen was inserted into the capsular device. The structure of the capsular device was optimized by applying a design of experiment approach to achieve sustained release of a drug while maintaining sufficient buoyancy. The 2-level factorial design was used to identify the optimal sustained release with three control factors: size, number, and height of drug-releasing holes of the capsular device. The drug delivery system was buoyant for more than 24 h and the average time to reach 80% dissolution (T ) was 1.7-6.7 h by varying the control factors. The effects of the different control factors on the response factor, T , were predicted by using the equation of best fit. Finally, drug delivery systems with predetermined release rates were prepared with a mean prediction error ≤ 15.3%. This approach holds great promise to develop various controlled release drug delivery systems.