Toward the Future: A Race-Agnostic, Bayesian Approach to Defining Glomerular Filtration for Personalized Drug Dosing

Area of Science:

• Pharmacology
• Nephrology
• Biomarkers

Background:

• Serum creatinine-based equations approximate glomerular filtration rate (GFR) for drug dosing but lack individual accuracy.
• Recent efforts to remove race from GFR equations improved ethics but not individual precision.
• Population-based GFR estimation is insufficient for personalized drug dosing.

Purpose of the Study:

• Advocate for a paradigm shift from demographic surrogates to direct renal clearance measurement for personalized drug dosing.
• Review limitations of endogenous biomarkers for assessing renal function.
• Propose an actionable framework for individualized drug dosing using exogenously measured GFR.

Main Methods:

• Critically evaluate endogenous biomarkers like creatinine and cystatin C for GFR estimation.
• Introduce exogenously measured GFR (mGFR) using iohexol.
• Integrate iohexol-based mGFR within a Bayesian pharmacometric framework for uncertainty quantification.

Main Results:

• Demonstrate the limitations of current creatinine-based GFR estimating equations at the individual level.
• Highlight the potential of cystatin C as an alternative endogenous biomarker.
• Present a practical framework for implementing iohexol-based mGFR and Bayesian analysis for refined renal dose selection.

Conclusions:

• Personalized drug dosing necessitates a move beyond creatinine-based GFR estimates towards direct renal clearance measurement.
• Exogenously measured GFR using iohexol, analyzed within a Bayesian pharmacometric framework, offers a clinically actionable approach to individualized dosing.
• This integrated approach enhances therapeutic precision and patient safety in managing renally eliminated drugs.