One Drug, Two Indications—How Simulation Helped Clarify the Filing Strategy

Some time ago, we helped a development team evaluating a compound with two indications. They needed to decide how to structure the NDA filings: either submit both together or file for the first indication as soon as Phase 3 is complete and let the second follow.

In the first scenario, the earlier project must wait for the second, which delays launch. In the second, the first indication moves ahead, but the second is held back due to regulatory timing constraints. The decision involves trade-offs in speed, overlap, and total value.

Development timelines added further complexity. Phase 3 durations were uncertain, which made it hard to assess how much faster the first indication would be. Depending on the difference, either approach could turn out better.

Market entry timing also played a role. Early launch of the first indication could provide a competitive edge and drive higher peak market share. But if the second indication has greater long-term value, it may be worth aligning timelines even if it delays launch.

Simulation modeling helped clarify the decision. We mapped out expected timelines, revenue potential, and scenario outcomes. A key benefit was the ability to test how much more valuable the first indication needed to be for a staggered filing to make financial sense.

The team also used output grids to determine the maximum wait time they could tolerate before filing individually became the better option. This gave them concrete decision support — not just a preferred path, but a set of thresholds and parameters for future reference.

These kinds of analyses demonstrate the value of simulation-based models that incorporate uncertainty. Rather than simply reacting to outcomes as they unfold, we can proactively explore and prepare for multiple scenarios. This shift—from reacting to planning—adds real strategic value. By understanding the dynamics between timelines, regulatory paths, and market factors, teams are better equipped to make informed decisions and maximize the impact of their R&D investments.

We continue to see more biopharma teams adopt this kind of approach for cross-functional alignment and investment decisions.