NeuroScios GmbH, St. Radegund/Graz, Austria.
Neurodegener Dis. 2014;13(2-3):147-50. doi: 10.1159/000357568. Epub 2014 Jan 7.
Animal models closely resembling the etiopathogenesis of Alzheimer's disease (AD) are needed for research on disease mechanisms and for drug development. No natural model of AD is available, so big hopes arose from transgenic and knockout technology, expecting that modulation and expression of pathogenetically important proteins resemble human brain pathology and functional deficits in the expected morphological and temporal pattern.
The real usefulness of these models should be discussed from an objective point of view.
Not a single one of the published transgenic rodent models fulfils this hope, and even complex multiple transgenic animals do not suffer from real AD. It is crucial to be aware that all of the commonly used mice and rats are just models, and therefore results from drug efficacy testing have to be interpreted with care. Repeated experience with failed trials of new treatments that previously had been published as successful in animals has led to the wrong conclusion that animal models are of low predictive value or even of no use. Often clinical trials replicate exactly what was shown in the animal proof-of-concept studies.
The value of animal models depends mainly on the careful experimentation and correct interpretation of results. Appropriate planning of experiments will help to increase the predictive value in drug development programs, though this may also increase negative findings. However, the early failure may enable a faster focus on more promising strategies.
为了研究疾病机制和开发药物,我们需要能够模拟阿尔茨海默病(AD)病因和发病机制的动物模型。目前尚无 AD 的天然模型,因此人们对转基因和基因敲除技术寄予厚望,希望这些技术能够调节和表达与疾病相关的重要蛋白,使这些蛋白在形态和时间上的变化与人类大脑病理和功能缺陷相类似。
从客观的角度讨论这些模型的真正用途。
目前已发表的转基因啮齿类动物模型没有一个能够满足这一期望,甚至复杂的多重转基因动物也不会出现真正的 AD。重要的是要认识到,所有常用的小鼠和大鼠都只是模型,因此药物疗效测试的结果必须谨慎解释。人们多次尝试新的治疗方法,但之前这些方法在动物身上的试验都被认为是成功的,这导致了错误的结论,即动物模型的预测价值较低,甚至没有价值。通常情况下,临床试验会复制在动物概念验证研究中显示的结果。
动物模型的价值主要取决于对实验的精心设计和对结果的正确解释。适当的实验设计将有助于提高药物开发计划的预测价值,尽管这也可能会增加阴性结果的数量。然而,早期的失败可能会使人们更快地关注更有前途的策略。