Scalable Microkidneys for Unbiased Phenotypic Drug Discovery and Target Identification (ID) in Diabetic Nephropathy and Inherited Kidney Diseases

Background: A bottleneck in the development of therapeutics in nephrology is the lack of physiological models that are compatible with drug discovery at a high-throughput scale. Currently, available in vitro models broadly consist of impressive reconstitution of kidney tissues that are impractical for screening: 3D mini-kidneys, or micro-physiological systems that are all too large, too variable or too complex to be employed at scale within drug screens. At the other end, 2D cell models are still employed are very scalable but lack the structural organization characteristic of human kidneys. Methods: RUMI has uniquely developed a platform that bridge this technological gap by allowing scalable screening and target ID in scalable and standardized complex micro-kidneys. We are leveraging this tool for in-house drug discovery, building a pipeline centered around high unmet needs areas such as DKD and inherited kidney diseases. Results: The key component of our platform is the introduction of micropatterning technology that allows the arrayed generation of nearly identical self-organizing human micro-kidney tissues, which are derived from human embryonic stem cells. One multi-well plate can easily generate more than 5’000 replicates, and >100 plates can be generated in parallel. Because of these large amounts of micro-kidneys imaged, we can build very large image data sets of in control and disease conditions, enabling the use of AI/deep learning to quantify subtle yet robust disease features within micro-kidney, as well as the potential for drugs to reverse the disease state to normal, paving the way towards discovery of new therapeutic candidates. Moreover, it has the potential to be coupled with CRISPR-KO genetic “suppressor screens”, which are the gold standard for target identification which today and cannot be performed with alternative technologies. Conclusion: We present the characterization of our micro-kidney, and demonstrate how this system can be leveraged to model multifactorial aspects of DKD. We will show that a key hallmark of kidney injury, KIM1, can be alleviated by knocking out of SLC5A2, demonstrating the validity of our platform in reproducing established clinical results. Moreover, we discuss our preliminary results for phenotypic discovery of inherited kidney diseases such as Alport Syndrome and Polycystic Kidney Disease.