Commercial analytics and forecasting underpin strategic decision-making and business planning across the pharmaceutical and life science sectors. Inaccurate risk assessments and poor strategic decision making cost the industry billions of dollars in wasted R&D spend every year and result in a gap in pharmaceutical intelligence to inform decision making in the clinical development space.

But what’s the alternative? How can you forecast the commercial potential of early-stage assets more effectively?

The short answer is intelligent forecasting. Essentially, a blend of machine learning and human ingenuity that considers the past, present and future drivers of commercial and clinical success in real time.

In this white paper we shed light on the “black box” that is machine learning, bust some myths about what it is (and what it isn’t) and show how it can add huge value across the pharmaceutical value chain.