ArticleTrials2011
Collaborative research between academia and industry using a large clinical trial database: a case study in Alzheimer's disease.
Article in Trials, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Benchmarks for ethically credible partnerships between industry and academic health centers: beyond disclosure of financial conflicts of interest.Clinical and translational medicine · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLarge clinical trials databases, developed over the course of a comprehensive clinical trial programme, represent an invaluable resource for clinical researchers. Data mining projects sponsored by industry that use these databases, however, are often not viewed favourably in the academic medical community because of concerns that commercial, rather than scientific, goals are the primary purpose of such endeavours. Thus, there are few examples of sustained collaboration between leading academic clinical researchers and industry professionals in a large-scale data mining project. We present here a successful example of this type of collaboration in the field of dementia.
methodsThe Donepezil Data Repository comprised 18 randomised, controlled trials conducted between 1991 and 2005. The project team at Pfizer determined that the data mining process should be guided by a diverse group of leading Alzheimer's disease clinical researchers called the "Expert Working Group." After development of a list of potential faculty members, invitations were extended and a group of seven members was assembled. The Working Group met regularly with Eisai/Pfizer clinicians and statisticians to discuss the data, identify issues that were currently of interest in the academic and clinical communities that might lend themselves to investigation using these data, and note gaps in understanding or knowledge of Alzheimer's disease that these data could address. Leadership was provided by the Pfizer Clinical Development team leader; Working Group members rotated responsibility for being lead and co-lead for each investigation and resultant publication.
resultsSix manuscripts, each published in a leading subspecialty journal, resulted from the group's work. Another project resulted in poster presentations at international congresses and two were cancelled due to resource constraints.
conclusionsThe experience represents a particular approach to optimising the value of data mining of large clinical trial databases for the combined purpose of furthering clinical research and improving patient care. Fruitful collaboration between industry and academia was fostered while the donepezil data repository was used to advance clinical and scientific knowledge. The Expert Working Group approach warrants consideration as a blueprint for conducting similar research ventures in the future.
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What OpenQuestion holds
Registered trials
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.