Evidence map›Paper›PMID 22980732›Full record

ReviewCurrent opinion in pharmacology2013

Solving the lost in translation problem: improving the effectiveness of translational research.

Ceren Ergorul, Leonard A Levin

Abstract readReview
In one paragraph

Review in Current opinion in pharmacology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.

  1. Pooled it
  2. Potential role ofNeural regeneration research · 2023
    Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Human reconstructed kidney models.In vitro cellular & developmental biology. Animal · 2021
    Review
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Pharmacotherapy of glaucoma.Journal of ocular pharmacology and therapeutics : the official journal of the Association for Ocular Pharmacology and Therapeutics · 2015
    Review
  16. Article
  17. Review
  18. Article
  19. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 2 countries.

Ceren ErgorulDepartment of Ocular Research, Toxikon Corporation, Bedford, MA 01730, USA.
Leonard A Levin
McGill University · CAToxikon (United States) · US

Funding

Novel Mitochondrial Targeted Neuroprotectants for GlaucomaR21EY017970 · NEI · UNIVERSITY OF WISCONSIN-MADISON · PI LEVIN, LEONARD A · 2007 to 2009
$607k
CIHR MOP 84211NEI NIH HHS R21 EY017970NEI NIH HHS R21EY017970
6 · The paper itself

Abstract

Translational research frequently fails to replicate in the clinic what has been demonstrated in the laboratory. This has been true for neuroprotection in the central nervous system, neuroprotection in glaucoma, as well as many other areas of medicine. Two fundamental reasons for this 'Lost in Translation' problem are the 'Butterfly Effect' (chaotic behavior of many animal models) and the 'Two Cultures' problem (differences between the methodologies for preclinical and clinical research). We propose several strategies to deal with these issues, including the use of ensembles of animal models, adding intraocular pressure lowering to preclinical neuroprotection studies, changing the way in which preclinical research is done, and increasing interactions between the preclinical and clinical teams.

Indexed as

Translational Research, BiomedicalAnimalsDisease Models, AnimalDrug Evaluation, PreclinicalGlaucomaHumans

Identifiers

PMID22980732
PMCPMC3529749
OpenAlexW2135138000

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.