From evidence to confident forecasts.
Product forecasts shape launch strategy, licensing decisions, portfolio prioritization, investment cases, and executive alignment. Yet many teams still rely on manual research, disconnected spreadsheets, fragile formulas, and model logic that is difficult to explain when evidence changes.
PharmaCast-AI gives pharma and biotech teams a faster, more governed way to build, update, stress-test, and defend product forecasts.
Primary team: BD/Corporate Development
Output: First-pass revenue forecast + scenarios
Primary team: Portfolio Strategy
Output: Standardized asset comparisons
Primary team: New Product Planning
Output: Patient-flow forecast + uptake curve
Primary team: Commercial Insights
Output: Updated assumptions + scenario impact
Primary team: Forecasting CoE
Output: Traceability, rationale, and review history
Different teams ask different questions, but they all need the same foundation: credible assumptions, transparent model logic, fast scenario testing, and outputs that can support real asset-level decisions.
Key question
Is this asset worth pursuing?
Primary users
BD, Corporate Development, Search & Evaluation, Finance
How PharmaCast-AI helps
Build a fast, defensible first-pass revenue forecast with source-backed assumptions and scenario comparisons for diligence.
Outputs
Revenue forecast
Assumption summary
Scenario pack
Key question
Which assets deserve funding?
Primary users
Portfolio Strategy, Corporate Strategy, Finance, Leadership
How PharmaCast-AI helps
Standardize forecasts across assets and indications so teams can compare opportunities with greater consistency and clarity.
Outputs
Asset comparison
Portfolio review
Scenario views
Key question
How will this market actually develop?
Primary users
New Product Planning, Commercial Insights, Forecasting, Market Access
How PharmaCast-AI helps
Translate epidemiology, patient flow, pricing, access, uptake, and competition into launch-ready market forecasts.
Outputs
Patient-flow forecast
Uptake curve
Access assumptions
Key question
How do we scale forecasting across teams?
Primary users
Forecasting CoE, Commercial Analytics, Business Operations
How PharmaCast-AI helps
Reduce manual setup, preserve methodology, capture assumption rationale, and support repeatable forecasting workflows.
Outputs
Reusable workflows
Assumption library
Review status
Model the commercial dynamics that matter in life sciences across the full patient journey and key market drivers.
Solves: Generic models that do not reflect how pharma markets actually work.
Generate structured starting assumptions with source context, rationale, ranges, and review status across all key drivers.
Solves: Blank-page analysis, manual evidence gathering, and inconsistent assumption structures.
AI accelerates the workflow, but experts remain in control. Review, edit, approve, override, and document assumptions before they flow into the forecast.
Solves: Black-box AI outputs that teams cannot explain, defend, or trust.
Test key drivers and events across scenarios and identify which assumptions have the greatest impact on outcomes.
Solves: Leadership questions that take too long to answer in manually updated models.
Keep assumptions, sources, rationale, review status, model history, and stakeholder inputs organized for transparency and repeatability.
Solves: Version-control issues, unclear rationale, inconsistent methods, and key-person dependency.
Create summaries, assumption tables, sensitivity views, scenario comparisons, and exports that plug directly into the tools and workflows your teams use.
Solves: Manual reformatting of forecast outputs into decks, valuation files, and planning materials.
Deep research from multiple
sources
Structured, source-backed and reviewed
Industry-specific logic built for pharma
Test key drivers and events with confidence
Traceable, repeatable and auditable
Export, share, and align across teams
PharmaCast-AI is designed to give commercial teams the speed of modern AI-enabled workflows without losing the transparency and expert judgment required for high-stakes pharmaceutical forecasting.
Manual evidence gathering
Scattered files and notes
Custom spreadsheet formulas
Different methods by team
Manual scenario rebuilds
Manual deck and file formatting
Faster first-pass forecast
Centralized source-traceable assumptions
Pharma-specific patient-flow logic
Repeatable methodology across assets
Fast scenario and sensitivity testing
Decision-ready exports
Reduce time spent gathering public inputs, structuring assumptions, and wiring formulas so teams can focus earlier on strategy and validation.
Make it easier for stakeholders to understand where assumptions came from, how they flow through the model, and why scenarios differ.
Give BD, commercial, portfolio, finance, and leadership teams a clearer shared view of the opportunity and its key drivers.
Reduce dependence on fragile spreadsheets, hidden logic, and single model owners.
Use PharmaCast-AI to enhance existing workflows, with structured exports that can support current models, templates, and presentation materials.
Yes. PharmaCast-AI is built to support a wide range of therapeutic areas and market structures, including rare diseases, oncology, specialty markets, and broader primary care categories.
The platform helps teams structure forecasts around the commercial drivers that matter most — patient population, diagnosis and treatment rates, line of therapy, launch timing, label assumptions, pricing, uptake, duration of therapy, market share, and competitive dynamics.
PharmaCast-AI helps BD and corporate development teams move from an asset question to a structured first-pass forecast faster.
Users can generate source-supported assumptions, review and adjust inputs, test base/upside/downside scenarios, and export outputs for valuation, diligence, and investment committee discussions. The goal is to reduce manual model-building time while giving teams a clearer view of the assumptions driving asset value.
Not necessarily. PharmaCast-AI is designed to work alongside existing forecasting and valuation workflows.
Teams can use the platform as an AI-assisted forecasting and assumption-development layer, then export outputs into Excel, CSV, PDF, PowerPoint, BI tools, or internal planning templates. This allows organizations to improve speed, structure, and transparency without immediately replacing models they already trust.
PharmaCast-AI is designed for human-in-the-loop forecasting.
The platform can help organize assumptions, structure forecast logic, and generate scenarios, but users remain in control. Your team can review, edit, approve, and document assumptions before they flow into the forecast. PharmaCast-AI provides the workflow and analytical structure; your experts provide the clinical, commercial, and strategic judgment.
PharmaCast-AI is designed for governed life sciences workflows.
Customer forecasts, assumptions, scenarios, and exports are intended to remain accessible only to authorized users within the customer environment. Role-based access, structured review processes, and enterprise onboarding options help support appropriate control over sensitive asset, pipeline, and diligence-related information.
For enterprise deployments, PharmaCast-AI can be configured to align with customer security, governance, data-handling, and onboarding requirements.
New customers receive hands-on onboarding to align PharmaCast-AI to their priority use cases, therapeutic areas, forecast structures, and reporting needs.
Onboarding can include use-case setup, asset configuration, model walkthroughs, scenario design, export review, and stakeholder training. The goal is to help teams generate value quickly while creating a repeatable forecasting workflow that can scale across assets, teams, and decision processes.
PharmaCast-AI helps BD, portfolio, strategy, commercial insights, and forecasting teams build forecasts faster, align stakeholders earlier, and support decisions with more transparent, scenario-ready outputs.
Move from manual model maintenance to faster, clearer, and more strategic pharma forecasting.
