Meta Research

The QUEST Center carries out several projects on the topic of "Research on Research", so-called Meta Research. With the help of Meta Research we can identify necessary measures and follow-up projects, and also evaluate implemented measures and projects.

COVID-evidence: a living database of trials on interventions for COVID-19

The COVID-19 pandemic is characterized by an unprecedented urgency to obtain reliable information on therapeutic options and their evaluation in clinical trials. This project aims at providing a freely available and daily updated online database of worldwide trial evidence on benefits and harms of interventions for COVID-19, including interventions for prevention, diagnosis, treatment and clinical management.

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Facility for the systematic review and meta-analysis of animal studies

In biomedical science, animal experiments are conducted to improve human health. However, efforts to translate results to clinical benefit in humans are often unsuccessful. Systematic review and meta-analysis are transparent, reproducible methods to objectively summarise published studies. In animal research, systematic reviews can help to identify reasons for translational failure, promising experimental treatments, and optimal 3Rs-related experimental designs.

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IntoValue

BIH supports the AllTrials Initiative. In this context we are dealing with the publication of clinical studies. With the IntoValue study we - together with the Hannover Medical School - are investigating the exact proportion of studies conducted at all 36 German university hospitals, for which no results have been published.

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Meta-Research Innovation Center Berlin (METRIC-Berlin)

Under the leadership of Professor John P. A. Ioannidis (Einstein BIH Visiting Fellow, funded by the Stiftung Charité) the so-called Meta-Research Innovation Center Berlin (METRIC-Berlin), the European "sister" of the Meta-Research Innovation Center at Stanford (METRICS), is being build up at the QUEST Center. The aim of the Center is to investigate the origin and the reliability, validity, accessibility and reproducibility of biomedical research. The Center is funded by the Stiftung Charité and the Einstein Foundation Berlin.

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Preclinical systematic review and meta-analysis

Preclinical systematic review and meta-analysis are meta-research tools that we use to investigate some of the challenges of translational biomedical research. They provide a summary of research findings in a field and allow judgement of both the range and quality of available evidence, including the likelihood that findings are at risk of bias. The results can help us identify areas for improvement in preclinical research and inform the development of strategies to address these challenges.

We focus primarily on the review of data from studies involving animal models of stroke and other neurological diseases and have a range of ongoing projects.

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Research on Translation

The project series Research on Translation aims at analysing the definition of translational research, at contributing to a clearer picture of the organization of translational research and at investigating the implementation of translational research within BIH.

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The Meta Research reading list for peer reviewers

Looking for ways to improve your manuscripts and peer reviews? This “science of science” reading list can help! 

When reviewing papers or writing your own papers, it’s important to remember that the fact that something is standard practice for your field doesn’t mean that it’s the best way of doing things. Scientists, journals and funding agencies are increasingly recognizing the limitations of many existing practices and are implementing new policies to improve transparency, rigor and reproducibility. Here we present a list of meta-research articles for authors and peer reviewers. These “science of science” papers will help peer reviewers learn to identify and understand the problems with some very common practices.
This collection of articles also offer constructive solutions that make it easier for authors to improve transparency, rigor and reproducibility.

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