In the world of clinic treatments, 3D-printed tissue constructs have emerged as a less invasive treatment method for various ailments. Printing processes, scaffold and scaffold free materials, cells used, and imaging for analysis are all factors that must be observed in order to develop successful 3D tissue constructs for clinical applications. However, current research in 3D bioprinting model development lacks diverse methods of successful vascularization as a result of issues with scaling, size, and variations in printing method. This study analyzes the methods of printing, bioinks used, and analysis techniques in 3D bioprinting for vascularization. These methods are discussed and evaluated to determine the most optimal strategies of 3D bioprinting for successful vascularization. Integrating stem and endothelial cells in prints, selecting the type of bioink according to its physical properties, and choosing a printing method according to physical properties of the desired printed tissue are steps that will aid in the successful development of a bioprinted tissue and its vascularization.

Spheroids serve as the building blocks for three-dimensional (3D) bioprinted tissue patches. When larger than 500 μm, the desired size for 3D bioprinting, they tend to have a hypoxic core with necrotic cells. Therefore, it is critical to assess the viability of spheroids in order to ensure the successful fabrication of high-viability patches. However, current viability assays are time-consuming, labor-intensive, require specialized training, or are subject to human bias. In this study, we build a convolutional neural network (CNN) model to efficiently and accurately predict spheroid viability, using a phase-contrast image of a spheroid as its input. A comprehensive dataset of mouse mesenchymal stem cell (mMSC) spheroids of varying sizes with corresponding viability percentages, which was obtained through CCK-8 assays, was established and used to train and validate the model. The model was trained to automatically classify spheroids into one of four distinct categories based on their predicted viability: 0–20%, 20–40%, 40–70%, and 70–100%. The model achieved an average accuracy of 92%, with a consistent loss below 0.2. This deep-learning model offers a non-invasive, efficient, and accurate method to streamline the assessment of spheroid quality, thereby accelerating the development of bioengineered cardiac tissue patches for cardiovascular disease therapies.

Perfusion offers unique benefits to tissue-engineered systems, enhancing oxygen and nutrient transport, which improves tissue formation and growth. In this study, we present a novel and integrated portable perfusion system. Weighing < 10 lbs, the system can maintain continuous flow in a standard incubation environment (37 °C, 5% CO₂), effectively functioning as a portable perfusion and tissue culturing system. To characterize the perfusion system’s flow parameters, we measured the volumetric flow rate across a range of pressures and found that the system could achieve flow velocities between 1.69 to 4.6 $\mathsf{\mu }$m/s, which is similar to in vivo interstitial flow. Computational fluid dynamics revealed fully developed laminar flow within the sample-containing region of the perfusion system, helping ensure even fluid and nutrient distribution. To study the system’s compatibility with live tissues, bioengineered tissue patches were created and perfused. After 24 h of perfusion, no significant difference in cell viability was observed between the perfused samples and static controls, indicating no adverse effects on cell health. Perfusion also facilitated enhanced spatial organization within tissue patches, reducing the inter-spheroids distance. Furthermore, perfusion strengthened the tissue matrix and reduced the degradation rate of the hydrogel scaffold. Complemented by its ability to provide mobile perfusion and incubation, this novel integrated portable perfusion system holds promise for promoting tissue maturation and advancing tissue bioengineering studies.

Recent advancements in biotechnology forged the path for clinical trials in dish (CTiDs) to advance as a popular method of experimentation in biomedicine. CTiDs play a fundamental role in translational research through technologies such as induced pluripotent stem cells, whole genome sequencing, and organs-on-a-chip. In this review, we explore advancements that enable these CTiD biotechnologies and their applications in animal testing, disease modeling, and space radiation technologies. Furthermore, this review dissects the advantages and disadvantages of CTiDs, as well as their regulatory considerations. Lastly, we evaluate the challenges that CTiDs pose and the role of CTiDs in future experimentation.