Common characteristics of open source software development and applicability for drug discovery: a systematic review View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-12

AUTHORS

Christine Årdal, Annette Alstadsæter, John-Arne Røttingen

ABSTRACT

BACKGROUND: Innovation through an open source model has proven to be successful for software development. This success has led many to speculate if open source can be applied to other industries with similar success. We attempt to provide an understanding of open source software development characteristics for researchers, business leaders and government officials who may be interested in utilizing open source innovation in other contexts and with an emphasis on drug discovery. METHODS: A systematic review was performed by searching relevant, multidisciplinary databases to extract empirical research regarding the common characteristics and barriers of initiating and maintaining an open source software development project. RESULTS: Common characteristics to open source software development pertinent to open source drug discovery were extracted. The characteristics were then grouped into the areas of participant attraction, management of volunteers, control mechanisms, legal framework and physical constraints. Lastly, their applicability to drug discovery was examined. CONCLUSIONS: We believe that the open source model is viable for drug discovery, although it is unlikely that it will exactly follow the form used in software development. Hybrids will likely develop that suit the unique characteristics of drug discovery. We suggest potential motivations for organizations to join an open source drug discovery project. We also examine specific differences between software and medicines, specifically how the need for laboratories and physical goods will impact the model as well as the effect of patents. More... »

PAGES

36

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1478-4505-9-36

DOI

http://dx.doi.org/10.1186/1478-4505-9-36

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1037221172

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/21955914


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Turtle is a human-readable linked data format.

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