Hepatobiliary Clearance Prediction: Species Scaling From Monkey, Dog, and Rat, and In Vitro–In Vivo Extrapolation of Sandwich-Cultured Human Hepatocytes Using 17 Drugs
Hepatobiliary elimination can be a major clearance pathway dictating the pharmacokinetics of drugs. Here, we first compared the dose eliminated in bile in preclinical species (monkey, dog, and rat) with that in human and further evaluated single-species scaling (SSS) to predict human hepatobiliary c...
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Veröffentlicht in: | Journal of pharmaceutical sciences 2017-09, Vol.106 (9), p.2795-2804 |
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Sprache: | eng |
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Zusammenfassung: | Hepatobiliary elimination can be a major clearance pathway dictating the pharmacokinetics of drugs. Here, we first compared the dose eliminated in bile in preclinical species (monkey, dog, and rat) with that in human and further evaluated single-species scaling (SSS) to predict human hepatobiliary clearance. Six compounds dosed in bile duct–cannulated (BDC) monkeys showed biliary excretion comparable to human; and the SSS of hepatobiliary clearance with plasma fraction unbound correction yielded reasonable predictions (within 3-fold). Although dog SSS also showed reasonable predictions, rat overpredicted hepatobiliary clearance for 13 of 24 compounds. Second, we evaluated the translatability of in vitro sandwich-cultured human hepatocytes (SCHHs) to predict human hepatobiliary clearance for 17 drugs. For drugs with no significant active uptake in SCHH studies (i.e., with or without rifamycin SV), measured intrinsic biliary clearance was directly scalable with good predictability (absolute average fold error [AAFE] = 1.6). Drugs showing significant active uptake in SCHH, however, showed improved predictability when scaled based on extended clearance term (AAFE = 2.0), which incorporated sinusoidal uptake along with a global scaling factor for active uptake and the canalicular efflux clearance. In conclusion, SCHH is a useful tool to predict human hepatobiliary clearance, whereas BDC monkey model may provide further confidence in the prospective predictions. |
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ISSN: | 0022-3549 1520-6017 |
DOI: | 10.1016/j.xphs.2017.04.043 |