Abstract: FR-PO298
Scalable Micro-Kidneys for Unbiased Phenotypic Drug Discovery and Target Identification in Diabetic Nephropathy and Inherited Kidney Diseases
Session Information
- Diabetic Kidney Disease: Basic - 1
October 25, 2024 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Diabetic Kidney Disease
- 701 Diabetic Kidney Disease: Basic
Author
- Etoc, Fred, RUMI Scientific, New York, New York, United States
Background
A key bottleneck in the discovery of therapeutics in nephrology is the lack of physiological models that are compatible with drug discovery at a high-throughput scale for target identification. Currently, available in vitro models 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 very scalable but lack structural organization. RUMI has uniquely developed a platform that bridge this gap by allowing scalable screening and target ID in fully 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.
Methods
The key component of our platform is a micropatterning technology that allows for 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 at once. These large data sets of micro-kidneys images, in disease and control conditions, then enable the use of AI/deep learning to quantify subtle yet robust disease features within micro-kidney structures, 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.
Results
We will present our micro-kidney's characterization, and demonstrate how this system can be leveraged to model multifactorial aspects of the diabetic injury related to 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 will discuss our preliminary results for phenotypic discovery of inherited kidney diseases such as Alport Syndrome and Polycystic Kidney Disease.
Conclusion
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Funding
- Private Foundation Support