Data-Driven Decision Making Through Synthetic Advisory Boards

This white paper discusses the implementation of synthetic advisory boards (S-ABs) in the pharmaceutical industry to enhance decision-making processes. It outlines the challenges faced by pharma teams in accessing timely insights due to the operational complexity of traditional advisory boards. S-ABs are introduced as AI-enabled digital twins that can simulate advisory environments, allowing teams to rapidly test multiple hypotheses and scenarios. The paper details the critical success factors for S-ABs, including the necessity for high-quality healthcare data, advanced AI agents, and thoughtful integration into existing workflows. It emphasizes that S-ABs are not a replacement for conventional advisory boards but rather a complementary tool that can improve the quality of discussions and decision-making. The document also describes the structured workflow of S-ABs, highlighting how they can generate decision-ready insights and support various activities throughout the product lifecycle, ultimately leading to more informed and efficient strategic planning.