Statistics versus statistical science in the regulatory process

Area of Science:

• Pharmaceutical Science
• Biostatistics
• Regulatory Science

Background:

• Established practices for pharmaceutical evidence submission to regulatory authorities.
• Need to align industry conventions with scientific principles for product approval.

Purpose of the Study:

• To critically review current practices in pharmaceutical evidence generation.
• To contrast these practices with fundamental scientific concepts and principles.
• To identify key areas for improvement in the drug approval process.

Main Methods:

• Review of established conventions and procedures for pharmaceutical evidence.
• Contrast of these practices with scientific concepts and principles.
• Discussion of specific issues including subject recruitment, data handling, statistical modeling, and hypothesis testing.

Main Results:

• Identified disconnects between regulatory practices and scientific rigor.
• Highlighted challenges in managing treatment heterogeneity and missing data.
• Critiqued the reliance on single trials and P-value culture in decision-making.

Conclusions:

• Current pharmaceutical evidence practices require re-evaluation to align with scientific standards.
• Improvements in trial design, data analysis, and interpretation are crucial for robust drug approval.
• Adopting a more nuanced approach to evidence, including prior information, can enhance regulatory decision-making.