Platform

Platform preview highlights

  • Purpose-built for pharma and biotech forecasting workflows, including patient-flow and patient-based modeling.
  • Assumption-level source traceability so teams can see where key inputs came from and review them before they enter the model.
  • Human-in-the-loop review, allowing experts to approve, edit, and refine assumptions before outputs are generated.
  • Scenario-ready forecasts that help teams pressure-test key commercial and clinical assumptions.
  • PPT, CSV, PDF, and presentation-friendly outputs designed to fit into existing Excel, PowerPoint, and internal reporting workflows.
Gallery

What you will see in the screenshot gallery

The gallery below walks through the core PharmaCast-AI workflow. Each screen is designed to make the forecasting process more visible, reviewable, and repeatable - without requiring teams to rebuild fragile spreadsheets from scratch.

Add Product window in PharmaCast-AI app with product name Keytruda and options to generate indications by AI.
Start with the Asset, Indication, and Strategic Question

Create a forecast by defining the asset, indication, geography, time horizon, and modeling objective. The guided setup helps orient the workflow around the specific commercial question your team needs to answer.

PharmaCast-AI dashboard showing a forecast form for Keytruda and lung cancer in the US with 2020 launch year.
Develop a Source-Cited Assumption Grid

PharmaCast-AI helps organize core assumptions - including epidemiology, diagnosis and treatment flows, pricing, market share, persistence, and adoption inputs - into a structured grid with source visibility at the assumption level.

Software screen showing selection of forecasting models: Incidence, Prevalence, and Patient Flow models.
Review AI-Assisted Inputs Before They Enter the Model

AI can accelerate the starting point, but experts remain in control. Users can review, edit, approve, reject, or replace proposed assumptions before they are used in the forecast.

PharmaCast-AI app screen showing epidemiology and treatment data input for breast cancer forecasting.
Visualize Patient Flow and Market Dynamics

Built-in pharma-specific modeling structures help represent real-world patient journeys, including eligible populations, diagnosed and treated patients, line-of-therapy dynamics, discontinuation, and other key commercial levers.

PharmaCast-AI dashboard displaying business inputs for adherence and market dynamics in incidence forecast setup.
Compare Scenarios and Sensitivities

Quickly compare base, upside, and downside cases. Pressure-test launch timing, market share, pricing, access, persistence, competitive events, and other drivers that can materially change the forecast.

PharmaCast-AI dashboard showing AML R/R Oral Small Molecule sales forecast and sensitivity analysis chart.
Generate Forecast Outputs for Stakeholder Review

Turn assumptions into clear forecast outputs that can be reviewed by BD, portfolio, commercial, finance, and investment stakeholders. The goal is not just faster modeling - it is clearer decision-making.

Export Into Existing Workflows

Use structured exports to bring PharmaCast-AI outputs into the Excel models, presentation decks, and internal templates your team already uses. PharmaCast-AI is designed to improve the workflow without forcing a full rip-and-replace.

Icon

Start with the asset, indication, and strategic question

Add Product window in PharmaCast-AI app with product name Keytruda and options to generate indications by AI.

Create a forecast by defining the asset, indication, geography, time horizon, and modeling objective. The guided setup helps orient the workflow around the specific commercial question your team needs to answer.

Icon

Develop a source-cited assumption grid

PharmaCast-AI dashboard showing a forecast form for Keytruda and lung cancer in the US with 2020 launch year.

PharmaCast-AI helps organize core assumptions - including epidemiology, diagnosis and treatment flows, pricing, market share, persistence, and adoption inputs - into a structured grid with source visibility at the assumption level.

Icon

Review ai-assisted inputs before they enter the model

Software screen showing selection of forecasting models: Incidence, Prevalence, and Patient Flow models.

AI can accelerate the starting point, but experts remain in control. Users can review, edit, approve, reject, or replace proposed assumptions before they are used in the forecast.

Icon

Visualize patient flow and market dynamics

PharmaCast-AI app screen showing epidemiology and treatment data input for breast cancer forecasting.

Built-in pharma-specific modeling structures help represent real-world patient journeys, including eligible populations, diagnosed and treated patients, line-of-therapy dynamics, discontinuation, and other key commercial levers.

Icon

Compare scenarios and sensitivities

PharmaCast-AI dashboard displaying business inputs for adherence and market dynamics in incidence forecast setup.

Quickly compare base, upside, and downside cases. Pressure-test launch timing, market share, pricing, access, persistence, competitive events, and other drivers that can materially change the forecast.

Icon

Generate forecast outputs for stakeholder review

PharmaCast-AI dashboard showing AML R/R Oral Small Molecule sales forecast and sensitivity analysis chart.

Turn assumptions into clear forecast outputs that can be reviewed by BD, portfolio, commercial, finance, and investment stakeholders. The goal is not just faster modeling - it is clearer decision-making.

Icon

Export into existing workflows

PharmaCast-AI dashboard showing AML R/R Oral Small Molecule sales forecast and sensitivity analysis chart.

Use structured exports to bring PharmaCast-AI outputs into the Excel models, presentation decks, and internal templates your team already uses. PharmaCast-AI is designed to improve the workflow without forcing a full rip-and-replace.

Teams

Built for the teams that need forecasts to be defensible

PharmaCast-AI is designed for the cross-functional teams that rely on forecasting to make high-stakes decisions.

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Business development and corporate development

Screen assets, pressure-test deal assumptions, and move faster during time-sensitive diligence.

Portfolio planning and strategy

Standardize forecasting methodology across assets, indications, and geographies.

Commercial insights and new product planning

Build patient-based forecasts that reflect real market dynamics and evolving evidence.

Strategic finance

Connect commercial assumptions to revenue projections and scenario-based planning.

Healthcare investors

Evaluate asset-level opportunities with transparent assumptions, repeatable structures, and clear export paths into existing valuation workflows.