An Introduction to Strategic Forecasting in the Pharmaceutical Industry
A 2-day, in-person, interactive, case-study based training
@Leonardo Royal Hotel, St. Pauls, London from 12–13th June, 2025
Strategy and Value Optimisation meets Forecasting in this course. Rather than viewing forecasts as static figures, you’ll learn to use forecasting models as dynamic, strategic tools.
This includes assessing a range of potential indications at very early stages of development, and creating a variety of competitor, TPP, market or other scenarios, with the objective of optimizing the value of an asset within its life cycle.
In the very early clinical stages of an asset, essential questions need to be asked, such as:
When Go/No Go decisions are being made, managing risk and prioritising resources involves asking questions such as:
Market pressures such as increased competition, LoE, the US IRA and lately geopolitical factors such as US tariffs require not only faster development and decision making, but also more certainty and robust analysis supporting key development decisions.
Understanding the disease area and market dynamics shapes your forecasting model, which becomes the central tool for quantifying strategies and guiding decisions. Without this, there’s no foundation for sound decision-making. Strategy and forecasting increasingly merge into a single, critical role across cross-functional teams and in BD and investment environments.
Today, it’s not just forecasters, insights teams, or value leads who drive value optimisation. Business development, licensing teams, investors, market research, and competitive intelligence professionals all play key roles in this integrated approach. This combined institutional knowledge and experience translates into competitive advantage in busy markets.
Over two in-person days, this course will show you how strategic forecasting can unlock greater value for your organisation – whether you’re in biotech, a small or medium-sized enterprise (SME), big pharma, or in an investment firm.
Note: Basic Excel and forecasting knowledge is helpful, but advanced expertise is not required.