TY - JOUR
T1 - Horizon scanning and drug expenditure for rare diseases: three-year predictive model in Italy 2025–2027
AU - Marcellusi, Andrea
AU - Cazzato, Daniela
AU - Guarnotta, Giulio
AU - Aiello, Andrea
AU - Bonfanti, Marzia
AU - Bitonti, Rossella
AU - Guardigni, Melissa
AU - Lucchetti, Chiara
AU - Luccini, Fulvio
AU - Canonico, Pier Luigi
AU - JOMMI, CLAUDIO
PY - 2025
Y1 - 2025
N2 - Background and objective: In recent years, spending on orphan drugs in Italy has seen a significant rise. The analysis aims to estimate future spending for medicines for rare diseases (RDs) in Italy. Methods: A forecasting model was developed over a three-year time frame. New drugs were selected according to specific criteria, using Biomedtracker and clinical trial databases. For each therapeutic indication, comparators were identified to estimate the average cost per patient. Overall expenditure was projected by applying prevalence data to the eligible population, and considering expected drug uptake trends over the study period. Additionally, a deterministic sensitivity analysis was performed to assess the influence of price fluctuations on total pharmaceutical spending. Results: Overall, a total of 137 pipeline drugs for RDs were identified, covering 74 indications. The model estimated a total spending on RD treatments equal to €2.08 billion in 2024, corresponding to an average cost of €24,777 per patient. The projection indicates an increase by 1.9% in 2025, 4.0% in 2026, and 7.1% in 2027 compared to 2024. Focusing on orphan designation drugs (n = 115), the 2024 expenditure was estimated at €1.93 billion, with an average patient cost of €22,984. The introduction of new orphan drugs is expected to drive further increases in spending by 1.1% in 2025, 2.2% in 2026, and 3.7% in 2027. Conclusions: The results underscore the growing financial impact of orphan drugs on Italy's healthcare budget. This analysis offers a quantitative projection of the resources required to ensure continued access to innovative therapies for RDs.
AB - Background and objective: In recent years, spending on orphan drugs in Italy has seen a significant rise. The analysis aims to estimate future spending for medicines for rare diseases (RDs) in Italy. Methods: A forecasting model was developed over a three-year time frame. New drugs were selected according to specific criteria, using Biomedtracker and clinical trial databases. For each therapeutic indication, comparators were identified to estimate the average cost per patient. Overall expenditure was projected by applying prevalence data to the eligible population, and considering expected drug uptake trends over the study period. Additionally, a deterministic sensitivity analysis was performed to assess the influence of price fluctuations on total pharmaceutical spending. Results: Overall, a total of 137 pipeline drugs for RDs were identified, covering 74 indications. The model estimated a total spending on RD treatments equal to €2.08 billion in 2024, corresponding to an average cost of €24,777 per patient. The projection indicates an increase by 1.9% in 2025, 4.0% in 2026, and 7.1% in 2027 compared to 2024. Focusing on orphan designation drugs (n = 115), the 2024 expenditure was estimated at €1.93 billion, with an average patient cost of €22,984. The introduction of new orphan drugs is expected to drive further increases in spending by 1.1% in 2025, 2.2% in 2026, and 3.7% in 2027. Conclusions: The results underscore the growing financial impact of orphan drugs on Italy's healthcare budget. This analysis offers a quantitative projection of the resources required to ensure continued access to innovative therapies for RDs.
KW - Forecast model
KW - Horizon scanning
KW - Orphan drugs
KW - Pharmaceutical expenditure
KW - Rare diseases
KW - Forecast model
KW - Horizon scanning
KW - Orphan drugs
KW - Pharmaceutical expenditure
KW - Rare diseases
UR - https://iris.uniupo.it/handle/11579/223651
U2 - 10.1186/s13561-025-00699-4
DO - 10.1186/s13561-025-00699-4
M3 - Article
SN - 2191-1991
VL - 15
JO - Health Economics Review
JF - Health Economics Review
IS - 1
ER -