Ten Points to Improve Reproducibility and Translation of Animal Research

Abstract

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 a priori 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.

Keywords: 3R; 6R; DSM-based animal model; HARCKing; confirmatory animal study; exploratory animal study; open science; p-hacking.

FIGURE 1

The workflow of an exploratory animal study type I and II. In the case of an exploratory study Type I, in which methodological new ground is broken the choice of model organism is of critical importance as well as the choice of behavioral test (which could be also a DSM-5-based behavioral model). The study design should be in accordance with the 3R principles, however, registration of the study design makes no sense, since experimental parameters are likely to be modified again and again in the course of the study until the new approach ultimately measures what is intended and can then be published. For a type II study the method is already established in a laboratory and is used to carry out new measurements. The study design can involve a power calculation (based on a systematic review), and is in accordance with the ARRIVE 2.0 guidelines and the 3R/6R principles. Pre-registration should be done and the publication irrespective if it reports negative or positive results should be open access and all digital data should be handled in accordance to the FAIR principles.

FIGURE 2

The workflow of a confirmatory animal study. If possible the null hypothesis should be based on a systematic review and even better for a quantitative statement on a meta-analysis. However, for most hypotheses it is not possible to perform a meta-analysis. The study design should include a power calculation, should adhere to the ARRIVE 2.0 guidelines and the 3R/6R principles, and should involve both sexes for generalization. For drug testing a multi-center study provides best translation and should consider tolerance development and a correction for the placebo effect. The study has to be pre-registered also in the form of a registered report. The publication should be open access and all digital data should be handled in accordance to the FAIR principles.