Advanced Tissue Technologies of Blood-Brain Barrier Organoids as High Throughput Toxicity Readouts in Drug Development

Summary Recent advancements in engineering Complex in vitro models (CIVMs) such as Blood-brain barrier (BBB) organoids offer promising platforms for preclinical drug testing. However, their application in drug development, and especially for the regulatory purposes of toxicity assessment, requires robust and reproducible techniques. Here, we developed an adapted set of orthogonal image-based tissue methods including hematoxylin and eosin staining (HE), immunohistochemistry (IHC), multiplex immunofluorescence (mIF), and Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) to validate CIVMs for drug toxicity assessments. We developed an artificial intelligence (AI) algorithm to increase the throughput and the reliability of histomorphologic evaluations of apoptosis for in vitro toxicity studies. Our data highlight the potential to integrate advanced morphology-based readouts such as histological techniques and digital pathology algorithms for use on CIVMs, as part of a standard preclinical drug development assessment. Graphical abstract The graphical abstract was partially created with biorender.com. Highlights Advanced Complex in vitro models (CIVMs) like Blood-brain barrier (BBB) organoids show promise for preclinical drug testing. However, robust and reproducible techniques are crucial for the acceptance of CIVMs in drug development processes, especially for toxicity assessments which are highly regulated by health authorities. We developed orthogonal image-based readouts on histological sections to enable the use of BBB organoids for future compound toxicity assessment. A newly established artificial intelligence (AI) algorithm provides automated and label-free detection of apoptotic cells in drug screening using BBB organoids and provides an alternative killing assay on single cell resolution (40×) to current standards.