Insilico Medicine Enters Collaboration with University of Zurich to Apply Generative AI to Discover Treatments for Cystinosis

Rare Dailys Staff

The MIKADO group, a translational team at the University of Zurich and the AI drug discovery company Insilico Medicine said they have entered into a research and development collaboration designed to accelerate the discovery of transformative novel therapeutics for the rare lysosomal storage disorder cystinosis.

The duration of the initial research collaboration will be one year.

Cystinosis is one of a family of approximately 70 rare inborn diseases of metabolism known as lysosomal storage diseases that collectively affect 1 in 5,000 live births. It is caused by inactivating mutations in the CTNS gene encoding the proton-driven transporter cystinosin, which exports cystine from the lysosome. Its functional loss leads cystine to accumulate within the lysosome of tissues across the body, culminating in severe multiorgan dysfunction that affect primarily the brain, eyes, liver, muscles, pancreas, and kidneys.

Fanconi syndrome is the first manifestation of cystinosis, usually presenting within the first year of life and characterized by the early and severe dysfunction of the kidney proximal tubule, most often complicated by chronic kidney disease and life-threatening manifestations. In their second to third decade of life, patients with cystinosis can also develop hypothyroidism, hypogonadism, diabetes, myopathy, deterioration of fine vision, and decline of the central nervous system. Beyond supportive care, the only available FDA-approved strategy to counteract cystine storage is the oral administration of cysteamine, which allows cystine to exit from the lysosomes. However, cysteamine treatment is hampered by side effects and poor tolerance, and it does not prevent kidney disease.

Under the collaboration, MIKADO group will leverage its multi-omics databank obtained from preclinical models and cystinosis-based cell models by using Insilico’s comprehensive novel target discovery AI platform PandaOmics to identify cellular and molecular pathways that drive life-threatening complications in cystinosis patients.

The MIKADO group will analyze disease-relevant targetable pathways and utilize Insilico’s proprietary algorithms to generate libraries of small molecule compounds that are expected to be validated in preclinical models and cystinosis cell systems using disease-relevant screening technologies developed by the MIKADO group at the University of Zurich.

“With the power of artificial intelligence-driven, systems biology-based drug discovery, we intend to accelerate the analysis and discovery of drug targets, with the goal of bringing novel breakthrough medicines to cystinosis patients while decreasing costs and increasing probabilities of success,” said Olivier Devuyst, head of MIKADO group at the University of Zurich.

“Using innovative preclinical models and disease-relevant phenotype screening, we aim to validate novel drug targets for diseases [for] which no cure has been found,” said Alessandro Luciani, senior scientist and team leader at MIKADO. “Ultimately, we want to improve the quality of life for those affected by the disease and bring tangible hope to thousands of cystinosis patients around the world.”