Presentation (CTI)

OBJECTIVES: The Most-Favoured Nation (MFN) policy is reshaping global drug pricing by anchoring US prices to those in economically comparable OECD countries. This study used a scenario-based modelling framework to assess two strategic decisions under the GLOBE and GUARD Medicare models: (1) whether manufacturers should disclose confidential net prices (Method II) to enable volume-weighted average net price benchmarking versus defaulting to the lowest country-level average list price (Method I); (2) whether to delay or forego launch in MFN basket countries to protect US pricing, or accept a lower US benchmark for ex-US revenue. Historical counterfactual case studies were developed for two high-volume medicines, osimertinib and ocrelizumab, and two orphan drugs, eculizumab and nusinersen, to assess differences across archetypes.
METHODS: A structured modelling framework simulated various launch and pricing scenarios under GLOBE and GUARD. Public list prices were used, with proxy net prices estimated using statutory deductions and confidential discount assumptions. Scenarios modelled included non-disclosure versus disclosure of net prices and full basket launch versus selective delay or non-launch. Outcomes included US price impact, ex-US revenue captured or foregone, and global revenue impact.
RESULTS: Exposure varied by archetype. For high-volume products, higher ex-US proportional share of volumes offsetting US revenue loss and a tighter pricing corridor limiting the negative impact on benchmarks may limit the attractiveness of delayed launch despite US price pressure. For rare diseases, lower ex-US volumes and high differentials between US and ex-US pricing increase the rationale for selective launch or delay. The value of disclosure depends on whether net-price concessions are concentrated in low-volume countries or distributed across high-weight markets.
CONCLUSIONS: The GLOBE and GUARD models create divergent incentives across product archetypes. Net price disclosure can mitigate exposure to low list prices when averages remain favourable. Robust scenario modelling is essential to optimise pricing and launch strategies.