title: A primer on screening data management.
abstract: A drug discovery startup company or academic lab entering the screening arena faces numerous challenges as it tries to manage the large quantity of data generated by a typical drug discovery screening campaign. Although there are sophisticated off-the-shelf software solutions available, their use requires substantial forethought and attention to detail if the data they capture are to be of sufficient quality to serve the various purposes to which it will be put. For newcomers to the field of screening data management in particular, the problem is compounded by a lack of literature covering the practical aspects of managing screening data. The authors provide some practical advice based on their experience of using a commercially available software suite. They discuss issues ranging from the organizational aspects to examples of how the form and content of metadata can have a big impact on whether results can be easily queried, pivoted, and reported. It is also hoped that their experiences might provide an opportunity for reflection to data management practitioners operating in established environments.
authors: Siena Biotech S.p.A., Siena, Italy. mpalmer@sienabiotech.it
authors: Mike
authors: M
authors: Palmer
authors: Andreas
authors: A
authors: Kremer
authors: Georg C
authors: GC
authors: Terstappen
mesh_terms: D000465:Algorithms; D003628:Database Management Systems / Q000458:organization & administration; D016208:Databases, Factual; D004353:Drug Evaluation, Preclinical / Q000379:methods / Q000706:statistics & numerical data*; D017598:Efficiency, Organizational; D001330:Electronic Data Processing / Q000458:organization & administration; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D012984:Software; D013663:Teaching / Q000458:organization & administration; D014584:User-Computer Interface