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Direct Reprogramming for Predictive Nephrotoxicity Testing (DRiPNeT).

Sector: Commercial • Location: Switzerland

Source: EU Funding & Tenders Portal

Project
Ongoing

Acute tubular necrosis (ATN) is a major cause of nephrotoxicity-related drug attrition in clinical trials, yet current preclinical models rely on animal studies or immortalized renal cell lines, which lack human physiological relevance. To address this gap, we have developed a directly reprogrammed renal epithelial cell (iREC) platform, enabling a human-specific, scalable, and high-throughput neph

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The project “Direct Reprogramming for Predictive Nephrotoxicity Testing (DRiPNeT).” is an infrastructure initiative in the Commercial sector, located in Switzerland. Taiyo aggregates data on it from EU Funding & Tenders Portal.

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ongoing

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Description

Description

Acute tubular necrosis (ATN) is a major cause of nephrotoxicity-related drug attrition in clinical trials, yet current preclinical models rely on animal studies or immortalized renal cell lines, which lack human physiological relevance. To address this gap, we have developed a directly reprogrammed renal epithelial cell (iREC) platform, enabling a human-specific, scalable, and high-throughput nephrotoxicity screening assay. Our iREC-based system overcomes the limitations of primary, or iPSC-derived models by offering a rapid, reproducible, and physiologically relevant alternative model. Building on the advances of the ERC-Starting Grant project DiRECT, this project will validate the iREC-based platform by screening a curated panel of nephrotoxic and non-nephrotoxic compounds, assessing performance metrics, such as specificity, sensitivity, and Predictive value to benchmark against other model systems. This project aims to establish the technical and commercial feasibility of iREC-based nephrotoxicity testing, seeking more predictive human-based preclinical models. The outcome will provide a cost-effective, scalable alternative to animal testing renal safety screen. Ultimately, this project will help reduce late-stage drug failures, improve patient safety, advance personalized risk prediction, and accelerate the development of safer therapeutics.

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High

Data quality score

100%

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