Four-dimensional (4D) printing, as a newly evolving technology to formulate drug delivery devices, displays distinctive advantages that can autonomously monitor drug release according to the actual physiological circumstances. In this work, we reported our earlier synthesized novel thermo-responsive self-folding feedstock for possible SSE-mediated 3D printing to form a 4D printed construct deploying machine learning (ML) modeling to determine its shape recovery behavior followed by its potential drug delivery applications. Therefore, in the present study, we converted our earlier synthesized temperature-responsive self-folding (both placebo and drug-loaded) feedstock into 4D printed constructs using SSE-mediated 3D printing technology. Further, the shape memory programming of the printed 4D construct was achieved at 50 °C followed by shape fixation at 4 °C. The shape recovery was achieved at 37 °C, and the obtained data were used to train and ML algorithms for batch optimization. The optimized batch showed a shape recovery ratio of 97.41. Further, the optimized batch was used for the drug delivery application using paracetamol (PCM) as a model drug. The % entrapment efficiency of the PCM-loaded 4D construct was found to be 98.11 ± 1.5%. In addition, the in vitro release of PCM from this programmed 4D printed construct confirms temperature-responsive shrinkage/swelling properties via releasing almost 100% ± 4.19 of PCM within 4.0 h. at gastric pH medium. In summary, the proposed 4D printing strategy pioneers the paradigm that can independently control drug release with respect to the actual physiological environment.

Recently, various innovative technologies have been developed for the enhanced delivery of biologics as attractive formulation targets including polymeric micro and nanoparticles. Combined with personalized medicine, this area can offer a great opportunity for the improvement of therapeutics efficiency and the treatment outcome. Herein, a novel manufacturing method has been introduced to produce protein-loaded chitosan particles with controlled size. This method is based on an additive manufacturing technology that allows for the designing and production of personalized particulate based therapeutic formulations with a precise control over the shape, size, and potentially the geometry. Sprayed multi adsorbed-droplet reposing technology (SMART) consists of the high-pressure extrusion of an ink with a well determined composition using a pneumatic 3D bioprinting approach and flash freezing the extrudate at the printing bed, optionally followed by freeze drying. In the present study, we attempted to manufacture trypsin-loaded chitosan particles using SMART. The ink and products were thoroughly characterized by dynamic light scattering, rheometer, Scanning Electron Microscopy (SEM), and Fourier Transform Infra-Red (FTIR) and Circular Dichroism (CD) spectroscopy. These characterizations confirmed the shape morphology as well as the protein integrity over the process. Further, the effect of various factors on the production were investigated. Our results showed that the concentration of the carrier, chitosan, and the lyoprotectant concentration as well as the extrusion pressure have a significant effect on the particle size. According to CD spectra, SMART ensured Trypsin’s secondary structure remained intact regardless of the ink composition and pressure. However, our study revealed that the presence of 5% (w/v) lyoprotectant is essential to maintain the trypsin’s proteolytic activity. This study demonstrates, for the first time, the viability of SMART as a single-step efficient process to produce biologics-based stable formulations with a precise control over the particulate morphology which can further be expanded across numerous therapeutic modalities including vaccines and cell/gene therapies.