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Zebrafish disease models in drug discovery: from preclinical modelling to clinical trials

斑马鱼 药物发现 计算生物学 临床试验 药品 药物开发 疾病 生物 医学 药理学 生物信息学 基因 内科学 生物化学
作者
E. Elizabeth Patton,Leonard I. Zon,David M. Langenau
出处
期刊:Nature Reviews Drug Discovery [Nature Portfolio]
卷期号:20 (8): 611-628 被引量:541
标识
DOI:10.1038/s41573-021-00210-8
摘要

Numerous drug treatments that have recently entered the clinic or clinical trials have their genesis in zebrafish. Zebrafish are well established for their contribution to developmental biology and have now emerged as a powerful preclinical model for human disease, as their disease characteristics, aetiology and progression, and molecular mechanisms are clinically relevant and highly conserved. Zebrafish respond to small molecules and drug treatments at physiologically relevant dose ranges and, when combined with cell-specific or tissue-specific reporters and gene editing technologies, drug activity can be studied at single-cell resolution within the complexity of a whole animal, across tissues and over an extended timescale. These features enable high-throughput and high-content phenotypic drug screening, repurposing of available drugs for personalized and compassionate use, and even the development of new drug classes. Often, drugs and drug leads explored in zebrafish have an inter-organ mechanism of action and would otherwise not be identified through targeted screening approaches. Here, we discuss how zebrafish is an important model for drug discovery, the process of how these discoveries emerge and future opportunities for maximizing zebrafish potential in medical discoveries. Zebrafish are useful model organisms for drug discovery, particularly in screening, disease modelling and toxicity assays. Here, Patton, Zon and Langenau discuss key recent successes in which zebrafish models have had key roles. Advances in gene modification technologies have enabled individual mutations to be recapitulated in zebrafish, leading to individualized treatments. Zebrafish xenografts as cancer models could also lead to rapid, personalized platforms for drug discovery.
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