Good Practice in Developing (Cell-based) Assays

16 Feb 2015, at 13.30-17.00 in Berlin, Germany

Short Overview of the Course

Cell-based assays, particularly phenotypic and high-content assays, are gaining importance for chemical biology and drug discovery. The course will provide state-of-the-art practice in how to develop robust and reproducible assays in microtiter plates not only for drug screening but also for smaller scale experiments in any lab. Basic considerations such as selecting the right cell model, cell culture conditions, or assay reagents and tools will be reviewed first. Then, an overview of cell-based assays applied to drug discovery will be given, with an excursion to more complex immunostaining assays, 3D assays and model organisms. Considerations and best-practice during assay development will be elaborated as well as how to fulfil certain standards and quality criteria. Advise on experimental design, selection of controls, systematically optimising conditions, applying (semi-)automated devices, quality assessment, assay validation and acceptance criteria will be provided. Aspects of assay transfer, adaption to automation and screening of chemical or genome-wide RNAi libraries will be discussed.

Learning Objectives

Learn how to develop robust and reproducible cell-based/high-content assays that fulfil essential quality standards, that not only improve your success, but also guarantee a certain standard to allow transfer of such assays from academia into industry, or from department to department, with a high chance of reproducibility.

Who would Benefit from this Training Course?

Both beginners as well as experienced individuals wishing to be refreshed on some aspects of cell-based assay development and (high-content) screening would greatly benefit. This course is directed towards attendees from both industry and academia. Particularly, young scientists from academia are highly encouraged to attend in order to learn the industry perspective and its expectations towards assays to be robust enough for large scale application, such as for high-throughput drug or genomic screens.