BACKGROUND: The ability to simulate in silico experiments is crucial for fast and cost-effective preliminary studies prior to clinical trials. We present an in silico approach to the design of optimal pramlintide-to-insulin (P/I) ratios, using our computer simulator of the human metabolic system, with a population of virtual adult type 1 diabetes mellitus patients and with individual parameters modified to account for the dynamic effects of pramlintide. MATERIALS AND METHODS: A model of pramlintide action on gastric emptying was built using data of 15 type 1 diabetes mellitus subjects studied twice with a standardized dual-tracer meal on placebo and pramlintide, which was incorporated in our type 1 diabetes simulator. Extensive in silico experiments on 100 virtual subjects were performed to optimize the co-administration of pramlintide and insulin prior to its submission to clinical trials; several P/I ratios were tested in terms of efficacy, in attenuating postprandial hyperglycemia, and in hypoglycemia safety. RESULTS: In silico experiments estimated the optimal P/I ratio to be 9 μg of pramlintide per unit (U) of insulin. Additional simulations narrowing the investigated range indicated that P/I ratios of 8 and 10 μg/U would achieve similar performance. Moreover, simulation results suggested that in clinical trials, insulin boluses should be reduced by approximately 21% at a P/I ratio of 9 μg/U to account for the effects of pramlintide and avoid postprandial hypoglycemia. CONCLUSIONS: We can assert that a valid simulation model of pramlintide action was developed, leading to in silico estimation of optimal pramlintide:insulin co-administration ratio. Clinical trials will confirm (or adjust) this initial estimation.
BACKGROUND: The ability to simulate in silico experiments is crucial for fast and cost-effective preliminary studies prior to clinical trials. We present an in silico approach to the design of optimal pramlintide-to-insulin (P/I) ratios, using our computer simulator of the human metabolic system, with a population of virtual adult type 1 diabetes mellituspatients and with individual parameters modified to account for the dynamic effects of pramlintide. MATERIALS AND METHODS: A model of pramlintide action on gastric emptying was built using data of 15 type 1 diabetes mellitus subjects studied twice with a standardized dual-tracer meal on placebo and pramlintide, which was incorporated in our type 1 diabetes simulator. Extensive in silico experiments on 100 virtual subjects were performed to optimize the co-administration of pramlintide and insulin prior to its submission to clinical trials; several P/I ratios were tested in terms of efficacy, in attenuating postprandial hyperglycemia, and in hypoglycemia safety. RESULTS: In silico experiments estimated the optimal P/I ratio to be 9 μg of pramlintide per unit (U) of insulin. Additional simulations narrowing the investigated range indicated that P/I ratios of 8 and 10 μg/U would achieve similar performance. Moreover, simulation results suggested that in clinical trials, insulin boluses should be reduced by approximately 21% at a P/I ratio of 9 μg/U to account for the effects of pramlintide and avoid postprandial hypoglycemia. CONCLUSIONS: We can assert that a valid simulation model of pramlintide action was developed, leading to in silico estimation of optimal pramlintide:insulin co-administration ratio. Clinical trials will confirm (or adjust) this initial estimation.
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