Drug development has been undergoing a transformational shift from the classical sequence of randomized control trials (RCT) to a more agile process capitalizing better and faster from past trials and real-world data. This shift has been accelerated and reinforced by the COVID pandemic which highlighted the critical need for robust real-world data platforms and fit-for-purpose analytical tools.

The purpose of this talk is to propose a regulatory-grade, data-integrative and disease-centric approach to accelerate and de-risk trials while maximizing the real-world value of the products in development. This relies on:

• A Paradigm Shift: from power-based to RW value based designs, as promoted by regulators and payers over the past decade
• A real-world disease modeling approach meant to simulate, at patient level, and jointly the disease progression and the care pathway in the real life practice
• A mix of real-world data science, Bayesian modeling, interpretable machine learning, advanced statistical and predictive modeling to capture the efficacy-to-effectiveness bridging, the short term to long term extrapolations and the integration of evidence from various and heterogeneous data sources
• An IT, data, and legal infrastructure to industrialize and "platformize" the integration of all the above
  Both the general approach and concrete examples (e.g. in MS, cardiovascular, oncology and rare diseases) will be presented to demonstrate the current value and the upcoming transformational benefit to pharma companies, care providers and health systems overall.