Biomedical Engineering Reference
In-Depth Information
1
Building research data handling
systems with open source tools
Claus Stie Kallesøe
Abstract:
Pharmaceutical discovery and development requires
handling of complex and varied data across the process pipeline.
This covers chemical structures information, biological assay and
structure versus activity data, as well as logistics for compounds,
plates and animals. An enterprise research data handling system
must meet the needs of industrial scientists and the demands of a
regulatory environment, and be available to external partners.
Within Lundbeck, we have adopted a strategy focused on agile and
rapid internal development using existing open source software
toolkits. Our small development team developed and integrated
these tools to achieve these objectives, producing a data management
environment called the Life Science Project (LSP). In this chapter, I
describe the challenges, rationale and methods used to develop LSP.
A glimpse into the future is given as we prepare to release an updated
version of LSP, LSP4All, to the research community as an open
source project.
Key words:
research data management; open source software;
software development; pharmaceutical research; Lundbeck; LSP;
LSP4All.
1.1 Introduction
All pharmaceutical company R&D groups have some kind of 'corporate
database'. This may not originally be an in-house designed knowledge
