R: Correct the measured intrinsive hepatic clearance for...

apply_clint_adjustment {httk}

R Documentation

Correct the measured intrinsive hepatic clearance for fraction free

Description

This function uses the free fraction estimated from Kilford et al. (2008) to increase the in vitro measure intrinsic hepatic clearance. The assumption that chemical that is bound in vitro is not available to be metabolized and therefore the actual rate of clearance is actually faster. Note that in most high throughput TK models included in the package this increase is offset by the assumption of "restrictive clearance" – that is, the rate of hepatic metabolism is slowed to account for the free fraction of chemical in plasma. This adjustment was made starting in Wetmore et al. (2015) in order to better predict plasma concentrations.

Usage

apply_clint_adjustment(
  Clint,
  Fu_hep = NULL,
  Pow = NULL,
  pKa_Donor = NULL,
  pKa_Accept = NULL,
  suppress.messages = FALSE
)

Arguments

`Clint`	In vitro measured intrinsic hepatic clearance in units of (ul/min/million hepatocytes).
`Fu_hep`	Estimated fraction of chemical free for metabolism in the in vitro assay, estimated by default from the method of Kilford et al. (2008) using `calc_hep_fu`
`Pow`	The octanal:water equilibrium partition coefficient
`pKa_Donor`	A string containing hydrogen donor ionization equilibria, concatenated with commas. Can be "NA" if none exist.
`pKa_Accept`	A string containing hydrogen acceptance ionization equilibria, concatenated with commas. Can be "NA" if none exist.
`suppress.messages`	Whether or not the output message is suppressed.

Value

Intrinsic hepatic clearance increased to take into account binding in the in vitro assay

Author(s)

John Wambaugh

References

Kilford PJ, Gertz M, Houston JB, Galetin A (2008). “Hepatocellular binding of drugs: correction for unbound fraction in hepatocyte incubations using microsomal binding or drug lipophilicity data.” Drug Metabolism and Disposition, 36(7), 1194–1197. Wetmore BA, Wambaugh JF, Allen B, Ferguson SS, Sochaski MA, Setzer RW, Houck KA, Strope CL, Cantwell K, Judson RS, others (2015). “Incorporating high-throughput exposure predictions with dosimetry-adjusted in vitro bioactivity to inform chemical toxicity testing.” Toxicological Sciences, 148(1), 121–136.