We develop the mathematics and the models behind cell-replacement therapy for type 1 diabetes: how to manufacture insulin-producing cells at the scale, cost, and consistency that millions of patients require, how to protect them from the immune system, and how to tell whether they will keep working.
Across two public human beta-cell CRISPR screens, we show how repeated guide identity and shared controls can create apparent reproducibility without a reliable gene-level phenotype.
A preregistered cross-screen analysis finds no broad shared gene program between SC-islet recovery after transplantation and intact-gene necessity under beta-cell cytokine stress.
We audit the public evidence needed for an AI-guided SC-islet product model and define the campaign-to-outcome data contract required for prospective validation.
We prove the conjectured higher-alphabet spectral bound for Hamming graphs, strengthen it to arbitrary supports in the minimal dimension, and extend the result to unequal coordinate weights.
We establish a spectral compression principle, construct new obstructions to Hamming-ball optimality, and classify the first two compressed defect layers exactly.
We are building the quantitative foundation that cell replacement needs to become a routine therapy, alongside the groups manufacturing the cells and running the trials. We bring the mathematics and the models, and we set the experimental agenda together.
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