Declaration of common standards for the preregistration of animal research-speeding up the scientific progress.
Céline HeinlAnna M D Scholman-VéghDavid T MellorGilbert SchönfelderDaniel StrechSteven A J ChamuleauBettina BertPublished in: PNAS nexus (2022)
Preregistration of studies is a recognized tool in clinical research to improve the quality and reporting of all gained results. In preclinical research, preregistration could boost the translation of published results into clinical breakthroughs. When studies rely on animal testing or form the basis of clinical trials, maximizing the validity and reliability of research outcomes becomes in addition an ethical obligation. Nevertheless, the implementation of preregistration in animal research is still slow. However, research institutions, funders, and publishers start valuing preregistration, and thereby level the way for its broader acceptance in the future. A total of 3 public registries, the OSF registry , preclinicaltrials.eu , and animalstudyregistry.org already encourage the preregistration of research involving animals. Here, they jointly declare common standards to make preregistration a valuable tool for better science. Registries should meet the following criteria: public accessibility, transparency in their financial sources, tracking of changes, and warranty and sustainability of data. Furthermore, registration templates should cover a minimum set of mandatory information and studies have to be uniquely identifiable. Finally, preregistered studies should be linked to any published outcome. To ensure that preregistration becomes a powerful instrument, publishers, funders, and institutions should refer to registries that fulfill these minimum standards.
Keyphrases
- healthcare
- clinical trial
- case control
- mental health
- public health
- primary care
- emergency department
- randomized controlled trial
- machine learning
- adverse drug
- systematic review
- adipose tissue
- electronic health record
- current status
- drinking water
- social media
- bone marrow
- decision making
- artificial intelligence
- drug induced
- meta analyses