The scientists here used radiomic biomarkers of age-related changes in body composition to construct new biological age indices as covariates of kidney function. A population pharmacokinetic model was constructed to determine whether biological age indices improved aminoglycoside clearance estimation compared to chronological age. The best radiomic biological age model included dorsal muscle group area, bone mineral density, visceral fat area, and subcutaneous fat density. The radiomic biological age model offered a modest improvement over the chronological age model. This work offers a proof-of-concept, highlighting the potential for more precise methods for aging-related kidney function estimation to aid personalized pharmacotherapy.
