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A Systems Pharmacology Model of Ageing Identifies Optimal Combination Therapies With Secondary Benefits on Weight Loss and Metabolic Health

Goryanin, I.; Damms, B.; Goryanin, I.

2026-04-23 pharmacology and therapeutics
10.64898/2026.04.22.26351392 medRxiv
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BackgroundAgeing is a systems-level biological process underlying the onset and progression of multiple chronic disorders. Rather than arising from a single pathway, age-related decline reflects interacting disturbances in metabolic regulation, inflammation, nutrient sensing, cellular stress responses, and tissue repair. Although GLP-1 receptor agonists, sodium-glucose cotransporter-2 inhibitors, metformin, and rapamycin are usually evaluated against disease-specific endpoints. ObjectiveTo develop an SBML-compliant quantitative systems pharmacology model in which ageing is the primary pharmacological endpoint and to evaluate which combination therapy provides the greatest benefit for both metabolic and ageing-related outcomes. MethodsWe developed model comprising four layers: a metabolic/pharmacodynamic layer describing weight loss, HbA1c reduction, and nausea with tolerance; a drug layer capturing class-specific effects of GLP-1 agonists, sodium-glucose cotransporter-2 inhibitors, metformin, and rapamycin; an ageing layer representing damage accumulation, repair capacity, frailty, and biological age gap; and a biomarker layer generating trajectories and estimated glucose disposal rate. Calibration was staged across semaglutide clinical endpoints. Bayesian hierarchical meta-analysis, global sensitivity analysis, and practical identifiability analysis were used to assess robustness and interpretability. ResultsThe model reproduced semaglutide efficacy and tolerability dynamics and supported distinct drug-class profiles across metabolic and ageing axes. Rapamycin showed minimal glycaemic effect but emerged as a dominant driver of repair-related ageing outcomes. Combination simulations predicted two distinct optima: one favouring metabolic improvement and one favouring ageing-related benefit. ConclusionThe model supports the view that metabolic and ageing optimization are mechanistically distinct objectives and that weight loss and glycaemic improvement alone may be insufficient surrogates for health span benefit.

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