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Forecasting Methods Time-series modelling S-curve and diffusion models (for emerging technologies) Driver-based forecasting (GDP, disposable income, adoption rates, regulatory changes) Price elasticity models Market maturity and lifecycle-based projections Scenario Analysis Given inherent uncertainties, three scenarios were constructed: Base-Case Scenario: Expected trajectory under current conditions Optimistic Scenario: High adoption, favourable regulation, strong economic tailwinds Conservative Scenario: Slow adoption, regulatory delays, economic constraints Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption

Acknowledgments This work was supported by the University of Zagreb, Zagreb, Croatia (Grant BM 099)

Reconstitution: 2.0 mL per 10 mg vial (5 mg/mL) for accurate measurements

It mimics the effects of a natural hormone in the body called glucagon-like peptide-1 (GLP-1) that regulates blood sugar levels

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