Ben-Yakar Adela
Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas.
Adela Ben-Yakar from the Department of Mechanical Engineering, The University of Texas at Austin was awarded The President's Innovation award at the annual Society of Biomolecular Imaging and Informatics (SBI2) meeting held in Boston, September 2018.
Assay Drug Dev Technol. 2019 Jan;17(1):8-13. doi: 10.1089/adt.2018.908.
The drug-discovery process is expensive and lengthy, and has been causing a rapid increase in the global health care cost. Despite extensive efforts, many human diseases still lack a cure. To improve the outcomes, there is a growing need to implement novel approaches into the early stages of the drug-discovery pipeline. A specific such effort has focused on the development of novel disease models such as cellular models (genetically modified cell lines, spheroids, and organoids) and whole-animal models (small animal models and genetically modified large animal models). The whole-animal screens are advantageous as they can provide system-level information, off-target effects, complete absorption, distribution, metabolism, excretion, and toxicity architectures, and early in vivo toxicity, which help to prioritize compounds before using them for human trials. Such multivariate analysis helps to improve the translational potential of drug compounds. Drug testing in large animals is expensive and time consuming. A solution is small animal models that have simplified biological system with intact physiology and sufficient homology with human genes. In recent times, many such models have constantly been developed and tested to identify new disease mechanisms. Caenorhabditis elegans is one such small animal model that has been considered for large-scale drug testing. In this review, we will discuss the current state-of-the-art technologies, including two platforms developed in my group that have enabled high-throughput and high-content screening using C. elegans disease models.
药物发现过程既昂贵又漫长，且一直在导致全球医疗保健成本迅速增加。尽管付出了巨大努力，但许多人类疾病仍然无法治愈。为了改善治疗效果，越来越需要在药物发现流程的早期阶段采用新方法。一项具体的此类努力聚焦于开发新型疾病模型，如细胞模型（基因改造细胞系、球体和类器官）和全动物模型（小动物模型和基因改造大动物模型）。全动物筛选具有优势，因为它们可以提供系统层面的信息、脱靶效应、完整的吸收、分布、代谢、排泄和毒性结构，以及早期体内毒性，这有助于在将化合物用于人体试验之前对其进行优先级排序。这种多变量分析有助于提高药物化合物的转化潜力。在大动物身上进行药物测试既昂贵又耗时。一种解决方案是使用具有简化生物系统、完整生理学且与人类基因有足够同源性的小动物模型。近年来，人们不断开发和测试许多此类模型以识别新的疾病机制。秀丽隐杆线虫就是这样一种被考虑用于大规模药物测试的小动物模型。在这篇综述中，我们将讨论当前的先进技术，包括我团队开发的两个平台，它们能够利用秀丽隐杆线虫疾病模型进行高通量和高内涵筛选。
