Assay Development and Screening
Microtissues in 4D to Improve Drug Toxicity Risk Assessment
Wednesday, February 7
10:30 AM - 11:00 AM
Drug discovery and development is often halted or delayed due to toxicological risks associated with the candidate drug and in particular those associated with cardiac toxicity. Cellular models that enable early and accurate assessment of compound liability are required. We have developed a suite of 384-well based 3D spheroid based multicellular model systems and applied novel kinetic imaging and analytical approaches to better assess compound toicity risk early in drug discovery. Cardiac microtissues utilised tri-cultures of human primary, IPS cell derived and primary cells to better represent cardiac tissue structure and functional activity. Characterisation of these model systems show physiologically relevant responses. Cardiac microtissues had a spontaneous beat rate of 62 ± 24 beats/minute (mean ± SD) and the microtissues maintained synchronized contraction transients following stimulation at 1, 2 and 3 Hz. To study and quantify changes in cardiac contractility we developed a bespoke fast frame-rate widefield image acquisition methodology coupled with optical flow image analysis and Wavelet decomposition. Structural cardiotoxicity was assessed using cytotoxicity and live cell high-throughput confocal microscopy, combined with analysis of endoplasmic reticulum integrity and mitochondrial membrane potential from all-in-focus images. Validation against a panel of in vivo clinical and pre-clinical compounds that represented diverse mechanisms of toxic effect showed improved sensitivity and specificity over 2D model systems. 73% of internal compounds stopped due to changes in cardiac pathology between first GLP dose and FTiH (2001-2014) were detected using this live cell imaging and cytotoxicity approach for structural cardiotoxicity with functional cardiotoxicants identified at 91% sensitivity and 80% specificity. These developed models and imaging-based screening systems are in use at a scale enabling full dose-response testing of compounds to enable effective decisions to be made early in a drug project lifecycle. Our results demonstrate the potential to use sophisticated imaging and machine learning analysis techniques to interrogate increasingly complex cellular systems such as microtissues to assess and mitigate for toxicity risk in preclinical drug discovery.