Using AI and Competitive Intelligence for portfolio prioritization and evaluating external assets

Ian Greenberg
Executive Director, Corporate & Business Development
Ketan Patel
Product Director – Portfolio, Licensing and Clinical

The use of Artificial Intelligence (AI) across the pharmaceutical value chain was once theory. But it is quickly becoming the new reality for the industry. Across the drug development process, AI is being used to uncover hidden insights, manage complex data, drive efficiencies and reduce growing costs. While we are hearing an increasing number of use cases across the R&D and clinical space, we’ve yet to hear comprehensive insight into how other core functions can benefit from this innovative technology.

The volume of information business development teams need to monitor is increasing. This is a problem as accurate and timely decisions are becoming even more critical for success. In this session, we will explore how AI can help you and your organization to:

  • Utilize historical data to create models to identify paths and time to approval for drug development programs
  • Use statistical modelling and data-driven evidence to value an internal portfolio, evaluate external assets and make comparisons
  • Create forecast predictions for each aspect of drug development projects
  • Speed up business development decision making using statistical models
  • Understand the importance of early communication with Regulatory and other key functions to increase drug and program success