3D bioprinting for organ and organoid models and disease modeling.

IF 6 2区 医学 Q1 PHARMACOLOGY & PHARMACY
Expert Opinion on Drug Discovery Pub Date : 2023-07-01 Epub Date: 2023-07-11 DOI:10.1080/17460441.2023.2234280
Amanda C Juraski, Sonali Sharma, Sydney Sparanese, Victor A da Silva, Julie Wong, Zachary Laksman, Ryan Flannigan, Leili Rohani, Stephanie M Willerth
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引用次数: 1

Abstract

Introduction: 3D printing, a versatile additive manufacturing technique, has diverse applications ranging from transportation, rapid prototyping, clean energy, and medical devices.

Areas covered: The 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 opinion: The 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.

器官和类器官模型的3D生物打印以及疾病建模。
简介:3D打印是一种通用的增材制造技术,具有从运输、快速成型、清洁能源到医疗设备的多种应用。涵盖领域:作者专注于3D打印技术如何通过自动化组织生产来增强药物发现过程,从而实现对潜在候选药物的高通量筛选。他们还讨论了3D生物打印过程是如何工作的,在使用该技术生成用于药物筛选的载有细胞的构建体时需要考虑什么,以及确定潜在候选药物疗效所需的此类分析的输出。他们专注于生物打印如何用于生成心脏、神经和睾丸组织模型,重点关注生物打印的3D类器官。专家观点:下一代3D生物打印器官模型在医学领域前景广阔。在药物发现方面,将智能细胞培养系统和生物传感器纳入3D生物打印模型可以为药物筛选提供高度详细和功能性的器官模型。通过解决当前血管形成、电生理控制和可扩展性方面的挑战,研究人员可以获得更可靠、更准确的药物开发数据,降低临床试验中药物失败的风险。
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来源期刊
CiteScore
10.20
自引率
1.60%
发文量
78
审稿时长
6-12 weeks
期刊介绍: Expert Opinion on Drug Discovery (ISSN 1746-0441 [print], 1746-045X [electronic]) is a MEDLINE-indexed, peer-reviewed, international journal publishing review articles on novel technologies involved in the drug discovery process, leading to new leads and reduced attrition rates. Each article is structured to incorporate the author’s own expert opinion on the scope for future development. The Editors welcome: Reviews covering chemoinformatics; bioinformatics; assay development; novel screening technologies; in vitro/in vivo models; structure-based drug design; systems biology Drug Case Histories examining the steps involved in the preclinical and clinical development of a particular drug The audience consists of scientists and managers in the healthcare and pharmaceutical industry, academic pharmaceutical scientists and other closely related professionals looking to enhance the success of their drug candidates through optimisation at the preclinical level.
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