Beyond Body Weight: A Comprehensive Review of Allometric Scaling in Drug Development for Human Dose Predictions

Area of Science:

• Pharmacokinetics and Drug Development
• Translational Science
• Biomedical Modeling

Background:

• Allometric scaling is a common method for predicting human pharmacokinetic (PK) parameters from animal data using power-law equations.
• Its application in first-in-human (FIH) dose selection is widespread but limited by interspecies differences in ADME processes.

Purpose of the Study:

• To review the principles, applications, and limitations of allometric scaling in predicting human PK parameters.
• To critically examine the successes and failures of allometry and discuss complementary methods for improved translation.

Main Methods:

• Review of mathematical foundations, workflows, and diagnostics of allometric scaling.
• Discussion of core concepts like clearance, volume of distribution, and correction factors.
• Integration of complementary methods including IVIVE, PBPK modeling, and AI/ML approaches.

Main Results:

• Allometric scaling's predictive performance is constrained by species-specific ADME variations.
• Historical clinical failures highlight the risks of relying solely on allometry.
• Modern advancements offer enhanced frameworks for more reliable human translation.

Conclusions:

• Allometric scaling serves as a foundational hypothesis but requires triangulation with mechanistic, experimental, and regulatory data.
• A comprehensive approach integrating multiple methods is crucial for safer and more effective human drug translation.
• Addressing species-specific differences is key to overcoming allometry's limitations.