4.5 Review

3D bioprinting for organ and organoid models and disease modeling

Journal

EXPERT OPINION ON DRUG DISCOVERY
Volume 18, Issue 9, Pages 1043-1059

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/17460441.2023.2234280

Keywords

Organoids; bioprinting; bioinks; stem cells; cardiac; neural; >

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This article introduces the application of 3D printing technology in drug discovery, focusing on automating tissue production for high-throughput drug screening. The authors also discuss the considerations when using 3D bioprinting to generate cell laden constructs for drug screening, as well as the evaluation of potential drug candidates. The article highlights the use of bioprinting in generating cardiac, neural, and testis tissue models.
Introduction3D printing, a versatile additive manufacturing technique, has diverse applications ranging from transportation, rapid prototyping, clean energy, and medical devices.Areas coveredThe authors focus on how 3D printing technology can enhance the drug discovery process through automating tissue production that enables high-throughput screening of potential drug candidates. They also discuss how the 3D bioprinting process works and what considerations to address when using this technology to generate cell laden constructs for drug screening as well as the outputs from such assays necessary for determining the efficacy of potential drug candidates. They focus on how bioprinting how has been used to generate cardiac, neural, and testis tissue models, focusing on bio-printed 3D organoids.Expert opinionThe next generation of 3D bioprinted organ model holds great promises for the field of medicine. In terms of drug discovery, the incorporation of smart cell culture systems and biosensors into 3D bioprinted models could provide highly detailed and functional organ models for drug screening. By addressing current challenges of vascularization, electrophysiological control, and scalability, researchers can obtain more reliable and accurate data for drug development, reducing the risk of drug failures during clinical trials.

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