Background: Orphan medicines used to treat patients with rare diseases often come at high costs with lower levels of clinical evidence. We compared the likelihood and timeliness of reimbursement for orphan medicines with non-orphan medicines in Australia between 2005 and 2012.
Methods: We developed two key assessment metrics to compare submissions and outcomes for new orphan medicines with those for new non-orphan medicines, viz., the likelihood of submissions being recommended by the Pharmaceutical Benefits Advisory Committee (PBAC) (success rate) and the time from Therapeutic Goods Administration registration to reimbursement (overall timeliness).
Results: Thirty eight out of 95 outcomes for orphan medicines (40%) received a PBAC recommendation compared to 257/481 (53%) for non-orphan medicines (p = 0.17). The PBAC recommendations that resulted in listings were comparable between the orphan and non-orphan categories (33/38 [87%] vs 218/257 [85%], respectively, p = 0.74).
Conclusion: The results suggested orphan medicines were not accorded any special status for reimbursement.
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http://dx.doi.org/10.1586/14737167.2015.1042368 | DOI Listing |
Acta Pharm Sin B
December 2024
State Key Laboratory of Cellular Stress Biology and Fujian Provincial Key Laboratory of Innovative Drug Target Research, School of Pharmaceutical Science, Xiamen University, Xiamen 361102, China.
The orphan nuclear receptor Nur77 is emerging as an attractive target for cancer therapy, and activating Nur77's non-genotypic anticancer function has demonstrated strong therapeutic potential. However, few Nur77 site B ligands have been identified as excellent anticancer compounds. There are no co-crystal structures of effective anticancer agents at Nur77 site B, which greatly limits the development of novel Nur77 site B ligands.
View Article and Find Full Text PDFActa Pharm Sin B
December 2024
Department of Endocrinology, the First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.
BMJ Open
December 2024
European Medicines Agency, Amsterdam, The Netherlands
Objectives: In the European Union, a new orphan medicinal product must demonstrate 'significant benefit' over approved medicinal products targeting the same indication. To demonstrate a significant benefit, comparisons between the new product and the already approved medicinal products-either directly by a head-to-head comparison within a clinical trial or indirectly as a cross-trial comparison-are necessary. In this study, we investigate the types of trial designs and statistical approaches used for demonstrating a significant benefit of a new orphan medicinal product against approved comparators used between 2012 and 2022.
View Article and Find Full Text PDFParkinsonism Relat Disord
December 2024
Roche Pharma Research and Early Development (pRED), Roche Innovation Center, F. Hoffmann-La Roche Ltd, Basel, Switzerland.
Introduction: Prasinezumab was shown to potentially delay motor progression in individuals with early-stage Parkinson's disease (PD) who were either treatment-naïve or on monoamine oxidase type B inhibitor (MAO-Bi) therapy in the PASADENA study. We report the rationale, design, and baseline patient characteristics of the PADOVA study, designed to evaluate prasinezumab in an early-stage PD population receiving standard-of-care (SOC) symptomatic medications.
Methods: PADOVA (NCT04777331) is a Phase 2b, multicenter, randomized, double-blind, placebo-controlled, parallel-group study, in which individuals with early-stage PD on SOC stable symptomatic monotherapy (levodopa or MAO-Bi) receive intravenous prasinezumab 1500 mg every 4 weeks.
Pharmacoeconomics
January 2025
Belgian Health Care Knowledge Centre, Brussels, Belgium.
Background: Forecasting future public pharmaceutical expenditure is a challenge for healthcare payers, particularly owing to the unpredictability of new market introductions and their economic impact. No best-practice forecasting methods have been established so far. The literature distinguishes between the top-down approach, based on historical trends, and the bottom-up approach, using a combination of historical and horizon scanning data.
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