Clinical modeling of motor function to predict treatment efficacy and enable in silico treatment comparisons in infantile-onset Pompe disease
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Updated: Jun 5, 2025

A Battery of Motor Tests in a Neonatal Mouse Model of Cerebral Palsy
Published on: November 3, 2016
Fatiha Rachedi1, Rana Jreich2, Susan Sparks3
1Sanofi, R&D, on behalf of IviData Life Sciences, Paris, France.
Abstract:
Infantile-onset Pompe disease (IOPD) is a rare, deadly, quickly-progressing degenerative disease. Even with life-sustaining treatment (e.g., alglucosidase alfa [ALGLU]), many patients experience continued motor impairment. The Mini-COMET trial evaluated avalglucosidase alfa (AVAL) versus ALGLU on motor and other outcomes in IOPD. However, treatment groups were imbalanced at baseline and the trial was not powered to directly compare treatments. To supplement this limited data, we developed a modeling and simulation approach to compare AVAL versus ALGLU head-to-head in in silico (i.e., computer-simulated) trials. We first developed a longitudinal clinical model to establish the relationship between changes in motor function and changes in urinary hexose tetrasaccharide (uHex4), an established biomarker in IOPD. This model was based on pooled data from Mini-COMET (n = 21) and COMET trials (n = 100 patients with late-onset Pompe disease, LOPD). We then conducted in silico trials mimicking Mini-COMET. Simulated trials were informed by motor data generated from the clinical model and uHex4 profiles simulated in a quantitative systems pharmacology model. The virtual IOPD population was based on observed Mini-COMET baseline characteristics but engineered to have well-balanced baseline characteristics across treatment cohorts. In silico trials showed that patients with IOPD would have the greatest improvements in motor function with AVAL 40 mg/kg every other week (Q2W), suboptimal improvement with ALGLU 40 mg/kg Q2W, and no improvement with ALGLU 20 mg/kg Q2W. This study provides information on the relative efficacy of IOPD treatments and mitigates the confounding effects of imbalanced treatment cohorts. Our approach could also be applied in other rare diseases.
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