Collaborative research between academia and industry using a large clinical trial database: a case study in Alzheimer's disease

<p>Abstract</p> <p>Background</p> <p>Large 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, h...

Full description

Bibliographic Details
Main Authors: Jones Roy, Wilkinson David, Lopez Oscar L, Cummings Jeffrey, Waldemar Gunhild, Zhang Richard, Mackell Joan, Gauthier Serge
Format: Article
Language:English
Published: BMC 2011-10-01
Series:Trials
Online Access:http://www.trialsjournal.com/content/12/1/233
id doaj-197111bfa3aa41029ba3651253d7063f
record_format Article
spelling doaj-197111bfa3aa41029ba3651253d7063f2020-11-24T22:56:22ZengBMCTrials1745-62152011-10-0112123310.1186/1745-6215-12-233Collaborative research between academia and industry using a large clinical trial database: a case study in Alzheimer's diseaseJones RoyWilkinson DavidLopez Oscar LCummings JeffreyWaldemar GunhildZhang RichardMackell JoanGauthier Serge<p>Abstract</p> <p>Background</p> <p>Large 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.</p> <p>Methods</p> <p>The 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.</p> <p>Results</p> <p>Six 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.</p> <p>Conclusions</p> <p>The 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.</p> http://www.trialsjournal.com/content/12/1/233
collection DOAJ
language English
format Article
sources DOAJ
author Jones Roy
Wilkinson David
Lopez Oscar L
Cummings Jeffrey
Waldemar Gunhild
Zhang Richard
Mackell Joan
Gauthier Serge
spellingShingle Jones Roy
Wilkinson David
Lopez Oscar L
Cummings Jeffrey
Waldemar Gunhild
Zhang Richard
Mackell Joan
Gauthier Serge
Collaborative research between academia and industry using a large clinical trial database: a case study in Alzheimer's disease
Trials
author_facet Jones Roy
Wilkinson David
Lopez Oscar L
Cummings Jeffrey
Waldemar Gunhild
Zhang Richard
Mackell Joan
Gauthier Serge
author_sort Jones Roy
title Collaborative research between academia and industry using a large clinical trial database: a case study in Alzheimer's disease
title_short Collaborative research between academia and industry using a large clinical trial database: a case study in Alzheimer's disease
title_full Collaborative research between academia and industry using a large clinical trial database: a case study in Alzheimer's disease
title_fullStr Collaborative research between academia and industry using a large clinical trial database: a case study in Alzheimer's disease
title_full_unstemmed Collaborative research between academia and industry using a large clinical trial database: a case study in Alzheimer's disease
title_sort collaborative research between academia and industry using a large clinical trial database: a case study in alzheimer's disease
publisher BMC
series Trials
issn 1745-6215
publishDate 2011-10-01
description <p>Abstract</p> <p>Background</p> <p>Large 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.</p> <p>Methods</p> <p>The 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.</p> <p>Results</p> <p>Six 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.</p> <p>Conclusions</p> <p>The 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.</p>
url http://www.trialsjournal.com/content/12/1/233
work_keys_str_mv AT jonesroy collaborativeresearchbetweenacademiaandindustryusingalargeclinicaltrialdatabaseacasestudyinalzheimersdisease
AT wilkinsondavid collaborativeresearchbetweenacademiaandindustryusingalargeclinicaltrialdatabaseacasestudyinalzheimersdisease
AT lopezoscarl collaborativeresearchbetweenacademiaandindustryusingalargeclinicaltrialdatabaseacasestudyinalzheimersdisease
AT cummingsjeffrey collaborativeresearchbetweenacademiaandindustryusingalargeclinicaltrialdatabaseacasestudyinalzheimersdisease
AT waldemargunhild collaborativeresearchbetweenacademiaandindustryusingalargeclinicaltrialdatabaseacasestudyinalzheimersdisease
AT zhangrichard collaborativeresearchbetweenacademiaandindustryusingalargeclinicaltrialdatabaseacasestudyinalzheimersdisease
AT mackelljoan collaborativeresearchbetweenacademiaandindustryusingalargeclinicaltrialdatabaseacasestudyinalzheimersdisease
AT gauthierserge collaborativeresearchbetweenacademiaandindustryusingalargeclinicaltrialdatabaseacasestudyinalzheimersdisease
_version_ 1725653630688690176