In recent years, the pharmaceutical industry has been increasingly focusing on the production of larger and more complex image-based data sets. The automated screening microscopy platforms that generate such data have become more advanced and effective, resulting in the ability to produce thousands of high-quality images in a single day. Consequently, pharmaceutical companies are faced with the challenge of leveraging appropriate analysis methods that help extract the optimal amount of biologically-relevant information and insights from these images.
Images of cultured cells consist of a plethora of information. Hence, these images need to be precisely converted into numeric data to gain maximum actionable insights. High content analysis (HCA) has emerged as a crucial means to specifically analyze image data and transform complex morphological parameters extracted from individual cells into a comparatively simplified numerical output. By empowering researchers to rapidly identify cellular phenotypes in addition to being driven by advances in robotics, genomics, and imaging, HCA can hugely benefit the drug discovery process. Besides mainstream drug screening, HCA can also be used for cytotoxicity and apoptosis studies in the pharmaceutical industry, but its success primarily relies on whether the image analysis software delivers the accurate representation of cellular morphological parameters.
Furthermore, image analysis powered by artificial intelligence (AI) is expediting the process of finding tumors and their diameter, volume, and vasculature along with helping determine the flow parameters of blood or other fluids and pinpointing microscopic changes. To help pharmaceutical companies select the best fitting image analysis software that is not only precise but also up-to-date with modern technologies, we have shortlisted some of the most promising image analysis solution providers in the pharma tech landscape.
We present to you Pharma Tech Outlook’s “Top 10 Image Analysis Solution Providers - 2019.”














