OBJECTIVES: It is becoming increasingly common that early stage drug candidates have potential applications in several therapy areas. This is especially prevalent where several diseases share a similar aetiology. Areas such as immunology, oncology and metabolic disorders can have ailments that are characterised by different physiological involvement but share a similar underlying cause. The objective of this study was to model the impact of a multiple indication launch on drug revenue over time, as well as develop a tool to enable launch strategy scenario testing. METHODS: The attractiveness and potential NPV of each therapy area is assessed using a combination of qualitative and quantitative methods. Therapy areas are scored and ranked by defined metrics allowing the optimum therapy area to be selected as the first launch indication. The assessment is repeated for the remaining therapy areas to account for changes in pricing dynamics from the initial launch indication, to generate the next most attractive therapy area and so on. NPV for the drug is then calculated based on a trade-off between patient population size and pricing dynamics across indications.  RESULTS: In general, the larger patient populations translate into lower drug costs to meet with budget impact thresholds. It is therefore vital for manufacturers to understand the optimal trade-off between price and population size across indications in order to maximise the overall commercial potential of a drug. When different indications have significantly differently sized patient populations, drug pricing becomes an issue. The research concluded that if the correct strategy is employed, a drug launch strategy can be optimised to generate the maximum possible revenue over the greatest number of indications. CONCLUSIONS: Modeling changes in price and population size during multiple-indication launches can be a vital tool in understanding total revenue potential of a new product, and optimal launch sequencing.