Towards novel treatments for lysosomal storage disorder cystinosis

Cystinosis is a prototypical lysosomal storage disorder (LSD) caused by inactivating mutations in cystinosin (CTNS), a proton-driven cystine transporter located on the surface of the lysosome. Loss of CTNS impairs lysosome-autophagy degradation pathways across multiple organs, with early dysfunction in kidney proximal tubule (PT) cells, leading to progressive multi-organ complications. Current treatment with cysteamine has limited efficacy, poor tolerance, and does not restore PT function — highlighting the need for disease-modifying therapies in children with cystinosis.

Our proof-of-concept studies demonstrate that inhibiting the overactive mTORC1 pathway, downstream of CTNS loss and cystine storage, can rescue disease phenotypes in preclinical models of cystinosis. However, existing mTORC1 inhibitors lack specificity and cause toxicity, underscoring the need for safer, targeted approaches to restore physiological homeostasis in cystinosis.

To address this therapeutic gap, we integrate preclinical models of cystinosis (mouse, nematode, rat, and zebrafish), physiologically relevant cell systems, and organelle-based function assays with artificial intelligence(AI)-powered drug discovery and screening platforms. Our key aims are to:

1. Identify selective mTORC1 modulators through repurposable drug and natural product screens;
2. Discover novel therapeutics using AI-driven drug design and clinical trial success prediction;
3. Develop a first-in-human clinical trial protocol to test promising repurposable candidates in children with cystinosis.

By combining advanced AI-enabled technologies with a comprehensive cross-species screening and validation pipeline, our goal is to accelerate the development of safe, targeted, effective therapies for cystinosis — and potentially other lysosomal disorders — ultimately delivering meaningful clinical benefit to affected children.