Key result
PopPK predictions match observed AUC changes in up to ~63% of drugs across renal impairment stages.
Why the study?
The concordance between exposure changes predicted by population pharmacokinetic models and observed results from dedicated renal impairment studies for new molecular entities was unclear.
Does population pharmacokinetic (PopPK) prediction accurately estimate exposure changes in patients with renal impairment compared to dedicated PK studies?
Does population pharmacokinetic (PopPK) prediction accurately estimate exposure changes in patients with renal impairment compared to dedicated PK studies?
PopPK modeling is a valuable tool for supporting labeling recommendations for subjects with renal impairment when done properly.
PopPK predictions may support labeling in mild renal impairment; leaves open accuracy for moderate-to-severe cases.
This analysis compared the results from noncompartmental analysis and population pharmacokinetic (PopPK) predictions of exposure changes in patients with renal impairment (RI) for 27 new molecular entities (NMEs) approved between 2000 and 2015. Renal function was identified as a covariate in the final PopPK model for 17 NMEs. The final PopPK model was used to simulate (n = 1000 replicates/individual) the results of a dedicated PK study in subjects with renal impairment. For the majority of NMEs, concordance between observed, and predicted area under the curve (AUC) geometric mean ratio (GMR) was observed (ie, in 17, 11, and 11 NMEs for mild, moderate, and severe renal impairment groups, respectively, the observed and predicted AUC GMR were within the same fold of change). Inclusion of colinear covariates in the PopPK model appeared to be the major driver for the NMEs for which there was discordance. PopPK, when done properly, is a valuable tool for supporting labeling recommendations for subjects with renal impairment.
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Ahmed et al. (2021) studied Renal impairment (n=27). Population pharmacokinetic (PopPK) predictions vs. Noncompartmental analysis was evaluated on Concordance between observed and predicted area under the curve (AUC) geometric mean ratio (GMR). Population pharmacokinetic predictions of exposure changes were concordant with observed AUC geometric mean ratios for 17, 11, and 11 of 27 drugs in mild, moderate, and severe renal impairment.
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