OBJECTIVES: No specific market access process has been developed for orphan drugs (ODs) in France, but there is an unspoken will to support these medicines. Pricing process of ODs is unclear, and many of them became blockbusters despite the small size of the targeted population. The aim of the study is to identify the main drivers of ODs prices in France. METHODS: ODs prices were extracted from Ameli database. Drugs and diseases attributes were defined based on the reports of the European Medicines Agency and Haut Authorité de Santé (HAS). Attributes included the prevalence, ATC class, therapeutic area, disease severity, alternative treatments, level of clinical evidence, SMR and ASMR scores, year assessment, and treatment line. Association between the annual treatment cost per patient and the attributes was studied using Pearson correlation coefficient (for quantitative variables), ANOVA (for qualitative variables), and generalized linear model using gamma distribution. RESULTS: Annual treatment costs varied from 1,500€ to almost 1,000,000€. Bivariate analysis showed a significant association between the annual treatment cost and disease prevalence, age group, treatment line, alternative treatments, therapeutic area, and ATC class (p<0.05 for all). Significantly higher cost was observed in pediatric population, first treatment line, metabolic diseases, or in case of absence of alternative treatment. Multivariate analysis including these variables did not showed significant results. Given the complex correlation structure between the co-variates, the model including only the prevalence and alternative treatments was tested. Both co-variates were significant. CONCLUSIONS: Disease prevalence and unmet needs seems to be the main drivers of ODs prices while the level of clinical evidence and disease severity had no impact. However, this is difficult to justify statistically because of high variance and small number of observations. Interestingly, ASMR score presented by the HAS as main price driver was not shown having an impact on drug prices.