A call for principle-based acceptance of synthetic patients: establishing the AI-driven foundation for regulatory submissions.

The pharmaceutical industry stands at the precipice of an AI-driven data revolution, with synthetic patients emerging as a transformative tool to accelerate drug discovery and development while enhancing patient privacy. However, a critical regulatory gap persists: the absence of a standardized basis from leading regulatory bodies for accepting AI-generated patient populations as evidence in regulatory submissions. This manuscript addresses this void by proposing five foundational principles-Representativeness, Utility, Robustness, Privacy Preservation, and Transparency-anchored by the "Fit for Purpose" philosophy. We introduce the operational concept of a "Technical Validation Playbook" to facilitate the first wave of regulatory acceptances for synthetic patient data. We further outline actionable recommendations for regulatory agencies and pharmaceutical sponsors to advance the acceptance of synthetic patient populations through existing qualification and scientific advice mechanisms. By establishing a proactive, principle-based approach, this framework aims to catalyze regulatory-industry alignment and unlock the transformative potential of synthetic patients, particularly for populations with unmet medical needs such as rare diseases where traditional placebo-controlled trials face insurmountable ethical and recruitment challenges.