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The current "blockbuster" model for drug development is unsustainable and it is clear that an alternative model is needed. In particular, the R&D costs for developing one drug has been estimated to exceed billions of dollars, and takes over 10-15 years 1, which is much longer and more expensive than necessary. Under so-called "Eroom's law", such R&D costs are doubling every nine years 2, with the US median annual list price of new drugs being US300, 000 per annum in 2023, up 35% from the previous year 3. Orphan drugs are also reaching exorbitant levels, such as Ravicti (glycerol phenylbuterate), which is priced at approximately US800, 000 per annum for Urea Cycle Disorder 4. However, by leveraging a new model of self-funding clinical trials, it is possible to address both the financial toxicity of new drugs and the lack of private incentives to repurpose low-cost generic drugs for new uses 5. In particular, by comparing a low-cost intervention, such as a repurposed generic, with an expensive drug, the immediate cost-savings generated for payors can fund the trial itself, even if it fails. This methodology is referred to as "interventional pharmacoeconomics" 6 although it can apply to any interventions where the cost-difference exceeds the cost of funding the trial (e. g. over US20, 000 per patient per annum). To address ethical concerns with comparing an approved intervention to a yet-to-be approved one, it is possible to focus on low-cost interventions that are most likely to provide superior health outcomes, such as through improved efficacy, safety, compliance or convenience. Commercial, political and legal barriers to leveraging self-funding trials should be considered, and vary by jurisdiction. These include whether the co-operation of the trial sponsor with the holder of the marketing authorisation of the generic is needed, whether payors are disincentivised from co-operating due to volume discounts or rebates offered for expensive drugs, and whether payors are legally permitted to fund clinical trials 7.
Savva Kerdemelidis (Wed,) studied this question.