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Towards improved predictions of pharmacokinetics of transported drugs in hepatic impairment: insights from the extended clearance model.

Flavia StorelliMayur K LadumorXiaomin LiangYurong LaiParesh P ChotheOsatohanmwen J EnogieruRaymond EversJashvant D Unadkat
Published in: CPT: pharmacometrics & systems pharmacology (2023)
Hepatic impairment (HI) moderately (< 5-fold) affects the systemic exposure (i.e. area under the plasma concentration-time curve, AUC) of drugs that are substrates of the hepatic sinusoidal organic anion transporting polypeptide (OATP) transporters and are excreted unchanged in the bile and/or urine. However, the effect of HI on their AUC is much greater (> 10-fold) for drugs that are also substrates of cytochrome P450 (CYP) 3A enzymes. Using the extended clearance model, through simulations, we identified the ratio of sinusoidal efflux clearance (CL) and the sum of metabolic and biliary CLs as important in predicting the impact of HI on the AUC of dual OATP/CYP3A substrates. Because HI may reduce hepatic CYP3A-mediated CL to a greater extent than biliary efflux CL, the greater the contribution of the former vs. the latter, the greater the impact of HI on drug AUC (AUCR HI ). Using physiologically based pharmacokinetic modeling and simulation, we predicted relatively well the AUCR HI of OATP substrates that are not significantly metabolized (pitavastatin, rosuvastatin, valsartan and gadoxetic acid). However, there was a trend towards underprediction of the AUCR HI of the dual OATP/CYP3A4 substrates fimasartan and atorvastatin. These predictions improved when the sinusoidal efflux CL of these two drugs was increased in healthy volunteers (i.e., before incorporating the effect of HI), and by modifying the directionality of its modulation by HI (i.e., increase or decrease). To accurately predict the effect of HI on AUC of hepatobiliary cleared drugs it is important to accurately predict all hepatobiliary pathways, including sinusoidal efflux CL.
Keyphrases
  • drug induced
  • emergency department
  • computed tomography
  • electronic health record