SLAS Discovery 2017, Vol. 22(2) 203–209 © 2016 Society for Laboratory Automation and Screening DOI: 10.1177/1087057116675316 journals.sagepub.com/home/jbx Application Note Introduction Surface plasmon resonance (SPR) is a powerful biophysical method for measuring molecular interactions. The versatil- ity of the technology means that it can be used both as a screening platform to identify binders and for detailed kinetic characterization of binding interactions. This has resulted in SPR being used widely in the drug discovery community. 1–4 With the increased interest in the binding kinetics of drugs 5,6 to better understand the mode of binding and possibly predict therapeutic effectiveness, the demand for SPR data is rising. In order to accommodate this increased demand, AstraZeneca explored how it could sim- plify and optimize its SPR workflow. For this streamlining exercise, instrumentation and analysis software were scrutinized to identify opportuni- ties for optimization. Currently, the small-molecule drug discovery performed by Discovery Sciences at AstraZeneca uses the General Electric Healthcare (GEHC) Biacore 4000, S200, T200, and 3000 SPR instruments. Two major areas for improvement in the Biacore software were read- ily identified. First, each SPR instrument comes with its own control and data evaluation software, which are aimed at the primary uses of the particular platform, such 675316JBX XX X 10.1177/1087057116675316Journal of Biomolecular ScreeningDahl et al. research-article 2016 1 Discovery Sciences, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Mölndal, Sweden 2 Genedata AG, Basel, Switzerland 3 R&D Information, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Mölndal, Sweden 4 Discovery Sciences, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Cambridge, UK 5 Discovery Sciences, Innovative Medicines and Early Development Biotech Unit, Waltham, MA, USA 6 Discovery Sciences, Innovative Medicines and Early Development Biotech Unit, Macclesfield, Cheshire, UK *These authors contributed equally to this work Received July 5, 2016, and in revised form Sep 30, 2016. Accepted for publication Sep 30, 2016. Supplementary material for this article is available on the Journal of Biomolecular Screening Web site at http://jbx.sagepub.com/supplemental. Corresponding Author: Stephan Steigele, Genedata AG, Margarethenstrasse 38, 4053 Basel, Switzerland. Email: stephan.steigele@genedata.com Unified Software Solution for Efficient SPR Data Analysis in Drug Research Göran Dahl 1* , Stephan Steigele 2* , Per Hillertz 3 , Anna Tigerström 1 , Anders Egnéus 3 , Alexander Mehrle 2 , Martin Ginkel 2 , Fredrik Edfeldt 1 , Geoff Holdgate 4 , Nichole O’Connell 5 , Bernd Kappler 2 , Annette Brodte 2 , Philip B. Rawlins 4 , Gareth Davies 6 , Eva-Lotta Westberg 3 , Rutger H. A. Folmer 1 , and Stephan Heyse 2 Abstract Surface plasmon resonance (SPR) is a powerful method for obtaining detailed molecular interaction parameters. Modern instrumentation with its increased throughput has enabled routine screening by SPR in hit-to-lead and lead optimization programs, and SPR has become a mainstream drug discovery technology. However, the processing and reporting of SPR data in drug discovery are typically performed manually, which is both time-consuming and tedious. Here, we present the workflow concept, design and experiences with a software module relying on a single, browser-based software platform for the processing, analysis, and reporting of SPR data. The efficiency of this concept lies in the immediate availability of end results: data are processed and analyzed upon loading the raw data file, allowing the user to immediately quality control the results. Once completed, the user can automatically report those results to data repositories for corporate access and quickly generate printed reports or documents. The software module has resulted in a very efficient and effective workflow through saved time and improved quality control. We discuss these benefits and show how this process defines a new benchmark in the drug discovery industry for the handling, interpretation, visualization, and sharing of SPR data. Keywords automation or robotics, database and data management, label-free technologies, pharmacology, ligand binding, receptor binding, general pharmaceutical process