• Drivers for change – sustainability, improved efficiency, increase quality
• Challenge – how to drive change in an establish business
• Leveraging combination of artificial intelligence and mechanistic modelling to enable change

Recent development of artificial intelligence and machine learning comes with a promise to reinvigorate the drug discovery and development process, enabling faster development lead time. Many of the early applications of AI/ML has been focusing on problems with ample access to data. The drug formulation space is less data rich as compared to the amount of data that is created in earlier drug discovery phase. The relative scarcity of data and variable quality of data provides an obstacle to develop AI augmented tools to accelerate drug development. In this talk Anders will discuss how they have combined molecular modelling and data analysis of historical data to overcome some these challenges. He will describe a few case studies and speculate on how a fully implemented digital lab could be used to augment key decisions points in the drug development space.

Anders Broo

Executive Director, Head of Data Science & Modelling, Pharm Sci

AstraZeneca