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Review
. 2021 Apr 8;64(7):3546-3559.
doi: 10.1021/acs.jmedchem.0c01930. Epub 2021 Mar 25.

Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization

Affiliations
Review

Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization

Jasleen K Sodhi et al. J Med Chem. .

Abstract

Development of new chemical entities is costly, time-consuming, and has a low success rate. Accurate prediction of pharmacokinetic properties is critical to progress compounds with favorable drug-like characteristics in lead optimization. Of particular importance is the prediction of hepatic clearance, which determines drug exposure and contributes to projection of dose, half-life, and bioavailability. The most commonly employed methodology to predict hepatic clearance is termed in vitro to in vivo extrapolation (IVIVE) that involves measuring drug metabolism in vitro, scaling-up this in vitro intrinsic clearance to a prediction of in vivo intrinsic clearance by reconciling the enzymatic content between the incubation and an average human liver, and applying a model of hepatic disposition to account for limitations of protein binding and blood flow to predict in vivo clearance. This manuscript reviews common in vitro techniques used to predict hepatic clearance as well as current challenges and recent theoretical advancements in IVIVE.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1.
Figure 1.
In vitro to in vivo extrapolation (IVIVE). Abbreviations: CLH, hepatic clearance; CLint, intrinsic clearance; CLint,invitro, in vitro intrinsic clearance; CLint,invivo, in vivo intrinsic clearance; fu,B, fraction unbound in blood; IVIVE, in vitro to in vivo extrapolation; kinc,u, unbound rate of incubational drug loss; QH, hepatic blood flow; Vinc, volume of in vitro incubation.
Figure 2.
Figure 2.
Experimental methodologies employed to study drug metabolism.
Figure 3.
Figure 3.
Isolation of hepatocytes and microsomes from hepatic tissue.
Figure 4.
Figure 4.
In vitro determinations of intrinsic clearance and high throughput assay considerations. Abbreviations: CLint,invitro, in vitro intrinsic clearance; fu,inc, fraction unbound in the incubation; kinc, rate of incubational drug loss, Km, Michaelis–Menten dissociation constant; Vinc, volume of in vitro incubation; Vmax, maximal rate of enzymatic reaction velocity.
Figure 5.
Figure 5.
Hepatic disposition models. Abbreviations: CH, hepatic drug concentration; Cin, entering drug concentration; CLH, hepatic clearance; Cout, exiting drug concentration; QH, hepatic blood flow.
Figure 6.
Figure 6.
Hepatic volume of distribution and IVIVE. Abbreviations: CLH, hepatic clearance; Cin, entering drug concentration; CLint,invitro, in vitro intrinsic clearance; CLint,invivo, in vitro intrinsic clearance; Cout, exiting drug concentration; IVIVE, in vitro to in vivo extrapolation; kinc,u, unbound rate of incubational drug loss; KL→W, partition coefficient from the lipophilic to aqueous hepatic compartments; kss,u, steady-state in vivo rate of unbound drug loss; KW→L, partition coefficient from the aqueous to lipophilic hepatic compartments; QH, hepatic blood flow; SF, physiologically based scaling factors; Vd, volume of distribution; Vhep, volume of distribution of drug in the hepatocyte water at steady state; Vinc, volume of in vitro incubation; Vnonhep, volume of distribution of drug in the nonhepatocyte water (lipophilic regions) at steady state; Vss,H, volume of distribution of drug in the whole liver at steady state.

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References

    1. DiMasi JA; Grabowski HG; Hansen RW Innovation in the pharmaceutical industry: New estimates of R&D costs. J. Health Econ 2016, 47, 20–33. - PubMed
    1. Obach RS; Baxter JG; Liston TE; Silber BM; Jones BC; MacIntyre F; Rance DJ; Wastall P The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data. J. Pharmacol. Exp. Ther 1997, 283, 46–58. - PubMed
    1. Rowland M; Benet LZ; Graham GG Clearance concepts in pharmacokinetics. J. Pharmacokinet. Biopharm 1973, 1, 123–135. - PubMed
    1. Wilkinson GR; Shand DG Commentary: a physiologic approach to hepatic drug clearance. Clin. Pharmacol. Ther 1975, 18, 377–390. - PubMed
    1. Strom SC; Jirtle RL; Jones RS; Novicki DL; Rosenberg MR; Novonty A; Irons G; McLain JR; Michalopoulos G Isolation, culture, and transplantation of human hepatocytes. J. Natl. Cancer Inst 1982, 68 (50), 771–778. - PubMed

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