Abstract

Organ-Chips are micro-engineered systems designed to recapitulate the organ microenvironment. Implementation within the pharmaceutical industry aims to improve the probability of success of drugs by generating pre-clinical models that are human and disease relevant. Organ-Chips come in different shapes and sizes and their small scale often makes it challenging to sample analytes. Imaging via microscopy offers an orthogonal approach for capturing cell phenotype in response to drug exposure in situ. Image processing also allows for analysis at a single cell level and investigation of spatial effects.

We have developed an end to end, automated imaging workflow to robustly capture and analyse confocal images of multicellular Organ-Chips at scale. By automating the 3D acquisition and analysis of images, we have reduced user interaction time, process variability and user bias. We have also established a framework of statistical best practice for Organ-Chip imaging which aids study design and allows us to understand sources of variability in the data. We have applied this workflow to design and prosecute studies to evaluate known hepatoxic compounds and active AZ drug candidates in human Liver-Chips, illustrating its applicability in drug safety assessment. Finally, use of bespoke, 3D printed adaptors allow this process to be adaptable to different chip formats and we demonstrate this through application to a Kidney-Chip model.