Abstract
Market access and pricing of pharmaceuticals are increasingly contingent on the ability to demonstrate comparative effectiveness and cost-effectiveness. As such, it is widely recognized that predictions of the economic potential of drug candidates in development could inform decisions across the product life cycle. This may be challenging when safety and efficacy profiles in terms of the relevant clinical outcomes are unknown or highly uncertain early in product development. Linking pharmacometrics and pharmacoeconomics, such that outputs from pharmacometric models serve as inputs to pharmacoeconomic models, may provide a framework for extrapolating from early-phase studies to predict economic outcomes and characterize decision uncertainty. This article reviews the published studies that have implemented this methodology and used simulation to inform drug development decisions and/or to optimize the use of drug treatments. Some of the key practical issues involved in linking pharmacometrics and pharmacoeconomics, including the choice of final outcome measures, methods of incorporating evidence on comparator treatments, approaches to handling multiple intermediate end points, approaches to quantifying uncertainty, and issues of model validation are also discussed. Finally, we have considered the potential barriers that may have limited the adoption of this methodology and suggest that closer alignment between the disciplines of clinical pharmacology, pharmacometrics, and pharmacoeconomics, may help to realize the potential benefits associated with linked pharmacometric-pharmacoeconomic modeling and simulation.
Highlights
Many jurisdictions across OECD countries require evidence of cost-effectiveness to secure the reimbursement and formulary inclusion of new medicinal products.[1]
We have considered the potential barriers that may have limited the adoption of this methodology and suggest that closer alignment between the disciplines of clinical pharmacology, pharmacometrics, and pharmacoeconomics, may help to realise the potential benefits associated with linked pharmacometric-pharmacoeconomic modelling and simulation
The results indicated that a hypothetical anti-inflammatory drug that increased FEV1 by 50ml, decreased exacerbations by 26%, and if priced at €35 per month, would be associated with an incremental cost-effectiveness ratio (ICER) ranging from €13,000 to €207,000 per quality-adjusted life year (QALY) gained across different patient subgroups, with the lowest ICER in patients with severe chronic obstructive pulmonary disease (COPD)
Summary
Many jurisdictions across OECD countries require evidence of cost-effectiveness to secure the reimbursement and formulary inclusion of new medicinal products.[1]. Economic evaluation during drug development aims to increase R&D efficiency through earlier termination of commercially non-viable drugs and, inform pricing strategies by predicting the price reimbursement authorities would be willing to pay.[10] Economic evaluation should ideally be applied iteratively, beginning in the pre-clinical phase and subsequently updated as clinical data emerges[11,12] and used beyond go/no-go and pricing decisions, to inform strategic, data collection and risk management decisions.[11] the methods and data sources required to parameterise early economic models have not been well described, including how to address the issue that outcomes in terms of the safety and efficacy of treatments will either be unknown or highly uncertain. A fourth category is presented for completeness, to include those published PMPE studies that are not focussed on drug development questions but may be used to inform resource allocation decisions from a payer perspective
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