Analysis: Cell Characterization and Quality Control in Drug Discovery
Answering scientific questions based on manual image analysis can be time-consuming and inefficient. Numerous tools are intended to help you analyze images quickly and efficiently, but extracting actionable data is not trivial. Images must be processed to remove systematic or sample-induced artifacts, and the biology of interest must be identified via appropriate image segmentation. These transformations need to apply uniformly to every image in the set in order to perform meaningful comparisons.
To provide you with more and better data and to enable you to be confident when picking “winners” to advance in your drug discovery programs, we offer software that removes artifacts, segments images, and analyzes relevant biology to ensure reliable recapitulation of the true biological signal.
Read more about these topics below:
Reliably analyzing large data sets
Raw data must be processed through multiple steps to reach a point where statistics may be meaningfully applied to the set. In a live-cell experiment performed in a 96-well plate, a thousand images is a perfectly reasonable data set size (and can be larger if you are capturing multiple channels, e.g. red fluorescence/green fluorescence/transmitted light). In analyzing a large image set, one must be assured that the set of operations is suitable across the set (e.g., on dead or living cells). Traditional image analysis software does not offer the ability to assess on a variety of images in an efficient manner, and thus analyzing typical live-cell microplate assays can be unwieldy. Our software has built-in solutions to address your needs when performing all the steps required to convert raw images to actionable data at scale.
Identifying relevant biology with your software
After an image has been sufficiently processed, the next step is identifying your biology of interest, which is done through appropriate image segmentation. In the simplest method for image masking, called “thresholding,” pixels are analyzed if above, or disregarded if below, a specific threshold. More complex interactions may also be analyzed using multiple masks controlled by Boolean logic (e.g., AND, OR, NOT) to hone in on the exact pixels of interest. Again, though, these analyses can be time-consuming and subjective. Purpose-built software that focuses on data analysis relevant to a specific scientific question can make image analysis both faster and more objective.
Technology for analyzing large sets of images and efficiently answering your scientific questions:
Cell Culture Quality Control Assay
Read our application note: Cell Culture Quality Control Assay to learn how you can use the IncuCyte to document and monitor routine cell culture and improve your cell-based assay quality and consistency.