Market access and pricing of pharmaceuticals are increasingly contingent on the ability to demonstrate comparative effectiveness and cost-effectiveness. As such, it is widely recognised that predictions of the economic potential of drug candidates in development could inform decisions across the product lifecycle. 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 characterise decision uncertainty. This article reviews the published studies that have implemented this methodology and used simulation to either inform drug development decisions and/or optimise 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 endpoints, 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 realise the potential benefits associated with linked pharmacometric-pharmacoeconomic modelling and simulation.