Automation and High-Throughput Technologies
Screening & Profiling at higher throughput using physiologically relevant cell models
Development of new pharmaceutical drugs is an expensive and high-risk endeavor for pharmaceutical industry. Major advances in physiologically relevant in vitro cellular assays such as three-dimensional models, induced pluripotent stem cells, organ-on-chip are expected to provide a better ability to predict therapeutic response, hence, reducing clinical attrition. Unlike High Throughput Screening, High Content Screening combines automated fluorescence microscopy with quantitative image analysis allowing phenotypic multiparametric readouts such as cell viability, DNA damage or mitochondria structure among many others. This approach is particularly well suited for complex or partially characterized targets. Moreover, in the oncology field, it has been shown that compound efficacy could be dramatically modulated in 3D models.
In this context, we are aiming to perform a medium scale screening campaign using a chemically diverse compounds collection on a cell line derived from non-small cell lung cancer with a specific mutation both in 2D and 3D models. Using High Content Imaging approaches, a large set of parameters will be extracted, leading to a better characterization of various toxicity mechanisms of actions.
To provide robust comparable results between cellular models, a specific subset of compounds was selected and screened in dose responses during the assay development workflow. The analysis of this rich set of complex data provided an opportunity to improve the rest of the screening campaign.
Hits obtained from both screens will be classified, compared and validated in dose responses for a better understanding of the difference induced by the use of 3D model combined with High Content Imaging. Ultimately this could help assess the relevance of 3D model in drug discovery in oncology.