Spanagel Rainer
Institute of Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Front Behav Neurosci. 2022 Apr 21;16:869511. doi: 10.3389/fnbeh.2022.869511. eCollection 2022.
Findings from animal experiments are often difficult to transfer to humans. In this perspective article I discuss two questions. First, why are the results of animal experiments often so difficult to transfer to humans? And second, what can be done to improve translation from animal experiments to humans? Translation failures are often the result of poor methodology. It is not merely the fact that low statistical power of basic and preclinical studies undermine a "real effect," but the accuracy with which data from animal studies are collected and described, and the resulting robustness of the data is generally very low and often does not allow translation to a much more heterogeneous human condition. Equally important is the fact that the vast majority of publications in the biomedical field in the last few decades have reported positive findings and have thus generated a knowledge bias. Further contributions to reproducibility and translation failures are discussed in this paper, and 10 points of recommendation to improve reproducibility and translation are outlined. These recommendations are: (i) prior to planning an actual study, a systematic review or potential preclinical meta-analysis should be considered. (ii) An power calculation should be carried out. (iii) The experimental study protocol should be pre-registered. (iv) The execution of the study should be in accordance with the most recent ARRIVE guidelines. (v) When planning the study, the generalizability of the data to be collected should also be considered (e.g., sex or age differences). (vi) "Method-hopping" should be avoided, meaning that it is not necessary to use the most advanced technology but rather to have the applied methodology under control. (vii) National or international networks should be considered to carry out multicenter preclinical studies or to obtain convergent evidence. (viii) Animal models that capture DSM-5 or ICD-11 criteria should be considered in the context of research on psychiatric disorders. (ix) Raw data of publication should be made publicly available and should be in accordance with the FAIR Guiding Principles for scientific data management. (x) Finally, negative findings should be published to counteract publication bias. The application of these 10 points of recommendation, especially for preclinical confirmatory studies but also to some degree for exploratory studies, will ultimately improve the reproducibility and translation of animal research.
动物实验的结果往往很难应用于人类。在这篇观点文章中，我讨论两个问题。第一，为什么动物实验的结果常常如此难以应用于人类？第二，如何才能提高从动物实验到人类应用的转化效率？转化失败往往是方法不当所致。不仅基础研究和临床前研究的统计效能低会削弱“实际效应”，而且动物研究数据收集和描述的准确性以及由此产生的数据稳健性通常很低，往往无法转化到更为异质性的人类情况。同样重要的是，在过去几十年里，生物医学领域的绝大多数出版物都报道了阳性结果，从而产生了知识偏差。本文讨论了对可重复性和转化失败的其他影响因素，并概述了提高可重复性和转化效率的十点建议。这些建议包括：(i) 在规划实际研究之前，应考虑进行系统评价或潜在的临床前荟萃分析。(ii) 应进行效能计算。(iii) 实验研究方案应预先注册。(iv) 研究的实施应符合最新的ARRIVE指南。(v) 在规划研究时，还应考虑所收集数据的可推广性（例如，性别或年龄差异）。(vi) 应避免“方法跳跃”，即不必使用最先进的技术，而是要掌握所应用的方法。(vii) 应考虑通过国家或国际网络开展多中心临床前研究或获取趋同证据。(viii) 在精神疾病研究中，应考虑采用符合《精神疾病诊断与统计手册》第5版（DSM-5）或《国际疾病分类》第11版（ICD-11）标准的动物模型。(ix) 出版物的原始数据应公开提供，并应符合科学数据管理的FAIR指导原则。(x) 最后，应发表阴性结果以抵消发表偏倚。应用这十点建议，特别是对于临床前确证性研究，在一定程度上对于探索性研究，最终将提高动物研究的可重复性和转化效率。
