Challenge:
A top-20 pharmaceutical company was preparing launch scenarios for a first-in-class specialty therapy with a high gross-to-net (G2N) spread. Traditional forecasting approaches couldn’t account for the dynamic variables across payer mix, competitive access moves, rebate structures, and patient support utilization. Finance teams were locked in static models. Market access was flying blind.
The Opportunity:
By applying agentic AI models—intelligent systems designed to simulate multi-party decision-making—we identified a smarter path to optimize net revenue scenarios across payer archetypes, distribution channels, and patient segments. Our goal: generate high-confidence G2N ranges with proactive levers, not just historical guesswork.
What We Did:
- Built a multi-agent simulation framework using real-world claims data, formulary coverage trends, and branded product analogs to model stakeholder behavior across payers, PBMs, and providers.
- Applied game theory constructs to simulate rebate counter-moves, step therapy strategies, and patient abandonment risks at varying copay levels.
- Integrated dynamic AI agents to pressure-test assumptions about access erosion, hub enrollment, and pull-through interventions—at a regional and segment-specific level.
- Collaborated with finance and market access leads to align the outputs with existing revenue recognition and contracting frameworks.
Key Enablers:
- Real-world data ingestion pipeline powered by FHIR-based infrastructure and payer intelligence sources
- Custom-built agentic AI engine trained on 3 years of specialty drug launch data
- Partnership with brand analytics and V&A teams to tie modeled assumptions to operational levers
Bottom Line:
Agentic A.I. solutions didn’t just forecast the future—they shaped it. By embedding intelligent, self-correcting models into the G2N planning process, we helped our client build a smarter launch strategy with fewer blind spots and better ROI discipline.
Want to build AI models that understand more than just math?
Let’s talk about how agentic systems can bridge finance, access, and real-world execution.
