3D Bioplotter Research Papers

3D printing enables precise control over tablet design and drug release, but challenges remain in optimising ink formulation, ensuring printability, and predicting final tablet properties. This study addresses the need for data-driven strategies in fabricating chewable tablets and tests the hypothesis that integrating rheology with machine learning (ML) enables predictive control over print quality and dosage form performance. We developed drug nanosuspension inks with varying water content (85–20 wt.%) and identified 40% as optimal, balancing shear-thinning behaviour, yield stress, and shear recovery for consistent extrusion. Analytical models predicted strut diameter (D) based on printing parameters—pressure (P), speed (v), and nozzle…