The trial-and-error method currently used to create formulations with excellent printability demands considerable time and resources, primarily due to the increasing number of variables involved. Rheology serves as a relatively rapid and highly beneficial method for assessing materials and evaluating their effectiveness as 3D constructs. However, the data obtained can be overwhelming, especially for users lacking experience in this field. This study examined the rheological properties of formulations of agar, hydroxypropyl methylcellulose, and the model drug caffeine, alongside exploring their printability as gummy formulations. The gels' rheological properties were characterized using oscillatory and rotational experiments. The correlation between these gels' rheological properties and their printability was established, and three clusters were formed based on the rheological properties and printability of the samples using principal component analysis. Furthermore, the printability was predicted using the sample's rheological property that correlated most with printability, the phase angle δ, and the regression models resulted in an accuracy of over 80%. Although these relationships merit confirmation in later studies, this study suggests a quantitative definition of the relationship between printability and one rheological property and can be used for the development of formulations destined for extrusion 3D printing.
Keywords: drug delivery; extrusion 3D printing; gels; principal component analysis (PCA); printability; rheology.
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