Science Forum: Improving preclinical studies through replications

  1. Natascha I Drude
  2. Lorena Martinez Gamboa
  3. Meggie Danziger
  4. Ulrich Dirnagl
  5. Ulf Toelch  Is a corresponding author
  1. Charité Universitätsmedizin, Germany
  2. Berlin Institute of Health, Germany

Abstract

The purpose of preclinical research is to inform the development of novel diagnostics or therapeutics, and the results of experiments on animal models of disease often inform the decision to conduct studies in humans. However, a substantial number of clinical trials fail, even when preclinical studies have apparently demonstrated the efficacy of a given intervention. A number of large-scale replication studies are currently trying to identify the factors that influence the robustness of preclinical research. Here, we discuss replications in the context of preclinical research trajectories, and argue that increasing validity should be a priority when selecting experiments to replicate and when performing the replication. We conclude that systematically improving three domains of validity – internal, external and translational – will result in a more efficient allocation of resources, will be more ethical, and will ultimately increase the chances of successful translation.

Data availability

No data was generated.

Article and author information

Author details

  1. Natascha I Drude

    Experimentelle Neurologie, Charité Universitätsmedizin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7153-2894
  2. Lorena Martinez Gamboa

    Experimentelle Neurologie, Charité Universitätsmedizin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  3. Meggie Danziger

    Experimentelle Neurologie, Charité Universitätsmedizin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Ulrich Dirnagl

    Department of Experimental Neurology, Charité Universitätsmedizin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0755-6119
  5. Ulf Toelch

    BIH QUEST Center for Transforming Biomedical Research, Berlin Institute of Health, Berlin, Germany
    For correspondence
    ulf.toelch@bihealth.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8731-3530

Funding

German Ministry for Education and Science

  • Natascha I Drude
  • Lorena Martinez Gamboa

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2021, Drude et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 3,223
    views
  • 311
    downloads
  • 36
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Natascha I Drude
  2. Lorena Martinez Gamboa
  3. Meggie Danziger
  4. Ulrich Dirnagl
  5. Ulf Toelch
(2021)
Science Forum: Improving preclinical studies through replications
eLife 10:e62101.
https://doi.org/10.7554/eLife.62101

Further reading

    1. Computational and Systems Biology
    2. Medicine
    Xin Zhou, Zhinuo Jenny Wang ... Blanca Rodriguez
    Research Article

    Sudden death after myocardial infarction (MI) is associated with electrophysiological heterogeneities and ionic current remodelling. Low ejection fraction (EF) is used in risk stratification, but its mechanistic links with pro-arrhythmic heterogeneities are unknown. We aim to provide mechanistic explanations of clinical phenotypes in acute and chronic MI, from ionic current remodelling to ECG and EF, using human electromechanical modelling and simulation to augment experimental and clinical investigations. A human ventricular electromechanical modelling and simulation framework is constructed and validated with rich experimental and clinical datasets, incorporating varying degrees of ionic current remodelling as reported in literature. In acute MI, T-wave inversion and Brugada phenocopy were explained by conduction abnormality and local action potential prolongation in the border zone. In chronic MI, upright tall T-waves highlight large repolarisation dispersion between the border and remote zones, which promoted ectopic propagation at fast pacing. Post-MI EF at resting heart rate was not sensitive to the extent of repolarisation heterogeneity and the risk of repolarisation abnormalities at fast pacing. T-wave and QT abnormalities are better indicators of repolarisation heterogeneities than EF in post-MI.

    1. Medicine
    2. Microbiology and Infectious Disease
    Berit Siedentop, Viacheslav N Kachalov ... Sebastian Bonhoeffer
    Research Article

    Background:

    Under which conditions antibiotic combination therapy decelerates rather than accelerates resistance evolution is not well understood. We examined the effect of combining antibiotics on within-patient resistance development across various bacterial pathogens and antibiotics.

    Methods:

    We searched CENTRAL, EMBASE, and PubMed for (quasi)-randomised controlled trials (RCTs) published from database inception to 24 November 2022. Trials comparing antibiotic treatments with different numbers of antibiotics were included. Patients were considered to have acquired resistance if, at the follow-up culture, a resistant bacterium (as defined by the study authors) was detected that had not been present in the baseline culture. We combined results using a random effects model and performed meta-regression and stratified analyses. The trials’ risk of bias was assessed with the Cochrane tool.

    Results:

    42 trials were eligible and 29, including 5054 patients, qualified for statistical analysis. In most trials, resistance development was not the primary outcome and studies lacked power. The combined odds ratio for the acquisition of resistance comparing the group with the higher number of antibiotics with the comparison group was 1.23 (95% CI 0.68–2.25), with substantial between-study heterogeneity (I2=77%). We identified tentative evidence for potential beneficial or detrimental effects of antibiotic combination therapy for specific pathogens or medical conditions.

    Conclusions:

    The evidence for combining a higher number of antibiotics compared to fewer from RCTs is scarce and overall compatible with both benefit or harm. Trials powered to detect differences in resistance development or well-designed observational studies are required to clarify the impact of combination therapy on resistance.

    Funding:

    Support from the Swiss National Science Foundation (grant 310030B_176401 (SB, BS, CW), grant 32FP30-174281 (ME), grant 324730_207957 (RDK)) and from the National Institute of Allergy and Infectious Diseases (NIAID, cooperative agreement AI069924 (ME)) is gratefully acknowledged.