AI-Digital-Physical Convergence in Drug Discovery

This white paper discusses the integration of artificial intelligence (AI) and digitalization in the drug discovery and development process, particularly focusing on the Design-Make-Test-Analyze (DMTA) cycle. It outlines the challenges faced by pharmaceutical organizations that are not fully digitalized, where manual data transfer leads to inefficiencies and increased risks. The paper presents the concept of a digital-physical virtuous cycle, where digital tools enhance physical processes, thereby improving operational productivity and innovation. It details the distinct activities involved in the DMTA cycle, including design, make, test, and analyze, emphasizing the importance of effective transitions between these stages. The document also highlights the role of AI in optimizing drug design and the necessity for seamless communication across different domains to mitigate productivity loss and transcription errors. By addressing these issues, organizations can enhance their regulatory compliance and bring therapies to patients more efficiently.