Abstract
3D printing offers the advantage of being able to modify dosage form geometry, which can be exploited to modify release characteristics. In this study, we investigated the influence of the surface area to volume ratio (SA/V) to change and predict release profiles of 3D printed dosage forms. Geometries with varying SA/V and dosages were designed and printed, and drug dissolution was investigated. Three drug substances were used: pramipexole, levodopa (both BCS I) and praziquantel (BCS II). Two polymers were chosen as matrix formers: polyvinyl alcohol (water-soluble) and ethylene vinyl acetate (inert). Drug release was characterized using the mean dissolution time (MDT) and established equations that describe complete dissolution curves were applied. Predictions were validated with previously un-printed dosage forms. Based on an identified MDT-SA/V correlation, the MDT can be predicted with a deviation of ≤5 min for a given SA/V. Using correlations of fit parameters and SA/V, RMSEP values of 0.6–2.8% and 1.6–3.4% were obtained for the BCS I formulations and RMSEP values of 1.0–3.8% were obtained for the BCS II formulation, indicating accurate prediction over a wide range of dissolution profiles. With this approach, MDT and release profiles of dosage forms with a given SA/V can be precisely predicted without performing dissolution tests and vice versa, the required SA/V can be predicted for a desired release profile.
Highlights
Personalized pharmaceutical therapies are increasingly moving into focus to match the individual needs of patients [1,2,3]
Using correlations of fit parameters and surface area to volume ratio (SA/V), root mean square error of prediction (RMSEP) values of 0.6–2.8% and 1.6–3.4% were obtained for the biopharmaceutics classification system (BCS) I formulations and RMSEP values of 1.0–3.8% were obtained for the BCS II formulation, indicating accurate prediction over a wide range of dissolution profiles
We demonstrated that the relationships between constants of established equations and the SA/V ratio can be exploited to predict complete dissolution curves for specific
Summary
Personalized pharmaceutical therapies are increasingly moving into focus to match the individual needs of patients [1,2,3]. To adjust the dose of medicine for patients based on these dependencies, several approaches are available. Liquid or semi-solid preparations can be measured and dosed individually with the help of dosing aids, such as spoons, syringes, or cups. Some tablets can be split into halves or quarters by hand or with the help of a tablet cutter, but these methods lead to inaccurate dosing [7,8]. To provide patients with customized medicines, 3D printing to manufacture individualized medicine has been investigated [10,11,12,13,14].
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