Additive manufacturing, otherwise known as three-dimensional (3D) printing, is driving major innovations in many areas, such as engineering, manufacturing, art, education and medicine. Recent advances have enabled 3D printing of biocompatible materials, cells and supporting components into complex 3D functional living tissues. 3D bioprinting is being applied to regenerative medicine to address the need for tissues and organs suitable for transplantation. Compared with non-biological printing, 3D bioprinting involves additional complexities, such as the choice of materials, cell types, growth and differentiation factors, and technical challenges related to the sensitivities of living cells and the construction of tissues. Addressing these complexities requires the integration of technologies from the fields of engineering, biomaterials science, cell biology, physics and medicine. 3D bioprinting has already been used for the generation and transplantation of several tissues, including multilayered skin, bone, vascular grafts, tracheal splints, heart tissue and cartilaginous structures. Other applications include developing high-throughput 3D-bioprinted tissue models for research, drug discovery and toxicology.

3D bioprinting of tissues and organs

Additive manufacturing (AM) alias 3D printing translates computer-aided design (CAD) virtual 3D models into physical objects. By digital slicing of CAD, 3D scan, or tomography data, AM builds objects layer by layer without the need for molds or machining. AM enables decentralized fabrication of customized objects on demand by exploiting digital information storage and retrieval via the Internet. The ongoing transition from rapid prototyping to rapid manufacturing prompts new challenges for mechanical engineers and materials scientists alike. Because polymers are by far the most utilized class of materials for AM, this Review focuses on polymer processing and the development of polymers and advanced polymer systems specifically for AM. AM techniques covered include vat photopolymerization (stereolithography), powder bed fusion (SLS), material and binder jetting (inkjet and aerosol 3D printing), sheet lamination (LOM), extrusion (FDM, 3D dispensing, 3D fiber deposition, and 3D plotting), and 3D bioprinting....

Polymers for 3D Printing and Customized Additive Manufacturing

A challenge for tissue engineering is producing three-dimensional (3D), vascularized cellular constructs of clinically relevant size, shape and structural integrity. We present an integrated tissue-organ printer (ITOP) that can fabricate stable, human-scale tissue constructs of any shape. Mechanical stability is achieved by printing cell-laden hydrogels together with biodegradable polymers in integrated patterns and anchored on sacrificial hydrogels. The correct shape of the tissue construct is achieved by representing clinical imaging data as a computer model of the anatomical defect and translating the model into a program that controls the motions of the printer nozzles, which dispense cells to discrete locations. The incorporation of microchannels into the tissue constructs facilitates diffusion of nutrients to printed cells, thereby overcoming the diffusion limit of 100-200 μm for cell survival in engineered tissues. We demonstrate capabilities of the ITOP by fabricating mandible and calvarial bone, cartilage and skeletal muscle. Future development of the ITOP is being directed to the production of tissues for human applications and to the building of more complex tissues and solid organs.

A 3D bioprinting system to produce human-scale tissue constructs with structural integrity

http://www.tissueeng.net/lab/papers/1-s2.0-S014296121500719X-main.pdf

Synthesis, properties, and biomedical applications of gelatin methacryloyl (GelMA) hydrogels

We demonstrate the additive manufacturing of complex three-dimensional (3D) biological structures using soft protein and polysaccharide hydrogels that are challenging or impossible to create using traditional fabrication approaches. These structures are built by embedding the printed hydrogel within a secondary hydrogel that serves as a temporary, thermoreversible, and biocompatible support. This process, termed freeform reversible embedding of suspended hydrogels, enables 3D printing of hydrated materials with an elastic modulus <500 kPa including alginate, collagen, and fibrin. Computer-aided design models of 3D optical, computed tomography, and magnetic resonance imaging data were 3D printed at a resolution of ~200 μm and at low cost by leveraging open-source hardware and software tools. Proof-of-concept structures based on femurs, branched coronary arteries, trabeculated embryonic hearts, and human brains were mechanically robust and recreated complex 3D internal and external anatomical architectures.

Three-dimensional printing of complex biological structures by freeform reversible embedding of suspended hydrogels.

The electrochemical method offers a sensitive, portable, and cost-effective method for detecting a range of analytes and has the capacity to be miniaturized. However, according to the World Health Organization, there is a need for point-of-care devices that meet the criteria for medical diagnostics in remote and resource-limited regions, as set forth by the World Health Organization. In this context, we developed a low-cost and high-throughput method for fabricating paper-based devices for electrochemical assays using a desktop pen plotter. In this study, we used a permanent marker to plot hydrophobic barriers and a liquid dispenser to pattern three electrodes (working, counter, and reference electrodes) with carbon paste on a paper substrate. To test the performance of the fabricated electrochemical devices, chronoamperometric and cyclic voltammetric analyses of potassium ferricyanide was conducted. Further, to demonstrate of the possible biomedical diagnostic applications, a quantitative glucose assay was performed. Here, we presented a low-cost electrochemical device fabrication method convenient for large-scale fabrication and widespread implementation of paper-based technologies in developing countries and resource-limited settings.

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A Hybrid Approach for Large-scale Fabrication of Paper-based Electrochemical Assays for Biomedical Diagnosis

Micromixers play an imperative role in chemical and biomedical systems. Designing compact micromixers for laminar flows owning a low Reynolds number is more challenging than flows with higher turbulence. Machine learning models can enable the optimization of the designs and capabilities of microfluidic systems by receiving input from a training library and producing algorithms that can predict the outcomes prior to the fabrication process to minimize development cost and time. Here, an educational interactive microfluidic module is developed to enable the design of compact and efficient micromixers at low Reynolds regimes for Newtonian and non-Newtonian fluids. The optimization of Newtonian fluids designs was based on a machine learning model, which was trained by simulating and calculating the mixing index of 1890 different micromixer designs. This approach utilized a combination of six design parameters and the results as an input data set to a two-layer deep neural network with 100 nodes in each hidden layer. A trained model was achieved with R2 = 0.9543 that can be used to predict the mixing index and find the optimal parameters needed to design micromixers. Non-Newtonian fluid cases were also optimized using 56700 simulated designs with eight varying input parameters, reduced to 1890 designs, and then trained using the same deep neural network used for Newtonian fluids to obtain R2 = 0.9063. The framework was subsequently used as an interactive educational module, demonstrating a well-structured integration of technology-based modules such as using artificial intelligence in the engineering curriculum, which can highly contribute to engineering education.

https://pubs.aip.org/aip/bmf/article-pdf/doi/10.1063/5.0146375/18028862/044101_1_5.0146375.pdf

Savas Tasoglu

Papers

A Hybrid Approach for Large-scale Fabrication of Paper-based Electrochemical Assays for Biomedical Diagnosis

Machine learning-augmented fluid dynamics simulations for micromixer educational module.