The renal proximal tubule is a main target for drug-induced toxicity. The prediction of proximal tubular toxicity during drug development remains difficult. Any in vitro methods based on induced pluripotent stem cell-derived renal cells had not been developed, so far. Here, we developed a rapid 1-step protocol for the differentiation of human induced pluripotent stem cells (hiPSC) into proximal tubular-like cells. These proximal tubular-like cells had a purity of >90% after 8 days of differentiation and could be directly applied for compound screening. The nephrotoxicity prediction performance of the cells was determined by evaluating their responses to 30 compounds. The results were automatically determined using a machine learning algorithm called random forest. In this way, proximal tubular toxicity in humans could be predicted with 99.8% training accuracy and 87.0% test accuracy. Further, we studied the underlying mechanisms of injury and drug-induced cellular pathways in these hiPSC-derived renal cells, and the results were in agreement with human and animal data. Our methods will enable the development of personalized or disease-specific hiPSC-based renal in vitro models for compound screening and nephrotoxicity prediction.

The kidney is a major target for drug-induced toxicity, and the renal proximal tubule is frequently affected. Nephrotoxicity is typically detected only late during drug development, and the nephrotoxic potential of newly approved drugs is often underestimated. A central problem is the lack of preclinical models with high predictivity. Validated in vitro models for the prediction of nephrotoxicity are not available. Major problems are related to the identification of appropriate cell models and end points. As drug-induced kidney injury is associated with inflammatory reactions, we explored the expression of inflammatory markers as end point for renal in vitro models. In parallel, we developed a new cell model. Here, we combined these approaches and developed an in vitro model with embryonic stem-cell-derived human renal proximal tubular-like cells that uses the expression of interleukin (IL)-6 and IL-8 as end points. The predictivity of the model was evaluated with 41 well-characterized compounds. The results revealed that the model predicts proximal tubular toxicity in humans with high accuracy. In contrast, the predictivity was low when well-established standard in vitro assays were used. Together, the results show that high predictivity can be obtained with in vitro models employing pluripotent stem cell-derived human renal proximal tubular-like cells.

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