Metabolism

Clearance of a drug is a pharmacokinetic parameter that quantifies the efficiency of the body in eliminating the drug from the bloodstream. It represents the volume of plasma or blood that is completely cleared of the drug per unit time, typically expressed in units such as milliliters per minute (mL/min) or liters per hour (L/h).

Clearance is a crucial factor in determining the dosing regimen of a drug, as it influences the drug's concentration in the body over time. A higher clearance rate indicates that the drug is eliminated more rapidly, while a lower clearance rate suggests slower elimination. Clearance can occur through various routes, including renal (kidneys), hepatic (liver), and other pathways, depending on the drug's properties and metabolism.

IV Clearance

Intravenous plasma clearance obtained from empirical models can be used as systemic clearance in a PBPK model. An optional input to enter a scalar which changes the IV clearance by the given factor is also provided.

Child model only

A checkbox has been provided to specify whether the apparent clearance pertains to an adult. If the checkbox is selected, the model interprets the input as an adult value and calculates the corresponding apparent clearance for children (CLchild) using the following equation:3

CLchild=CLadult×(BWchildBWadult)0.75CL_{child} = CL_{adult} \times \left(\frac{BW_{child}}{BW_{adult}}\right)^{0.75}
[ 1 ]

Where CL adult is the apparent clearance of adult, BWchild and BWadult are body weights of a child and an average adult (70 kg) respectively.

Intrinsic

Intrinsic clearance refers to the inherent ability of an organ, typically the liver or kidneys, to metabolize or eliminate a drug independent of blood flow limitations. It represents the maximum capacity of the organ to clear the drug from the bloodstream when there are no constraints imposed by blood flow or protein binding.

Gut

The intrinsic clearance of gut (CLint,gut) is calculated for CYP3A enzymes using the following equation:4

CLint,gut(L/h)=CLint,CYP3A (in μL/min/pmol)×CYP3A Abundance (nmol)×(unit conversion)CL_{int,gut}(L/h) = CL_{int,CYP3A}\ \text{(in } \mu L/min/pmol\text{)} \times \text{CYP3A Abundance (nmol)} \times \text{(unit conversion)}
[ 2 ]

where CLint,CPY3A, CYP3A is the total intrinsic clearance of CYP3A enzymes for any given drug and the total abundance of CYP3A in the intestine is 70.5 nmol. 4,5

Hepatic

The model currently allows the user to select up to four metabolising enzymes (either CYPs or UGTs). The intrinsic clearance of an enzyme (CLint,enzyme) is scaled using abundance of protein in pmol/mg of microsomal protein, milligrams of microsomal protein per gram of liver1 (MPPGL) and liver weight as follows:

If CLint is in µL/min/pmol,

CLint,enzyme(L/h)=CLint×Enzyme Abundance (pmol/mg)×MPPGL×Liver weightCL_{int,enzyme}(L/h) = CL_{int} \times \text{Enzyme Abundance (pmol/mg)} \times MPPGL \times \text{Liver weight}
[ 3 ]

If CLint is in µL/min/mg,

CLint,enzyme(L/h)=CLint×MPPGL×Liver weightCL_{int,enzyme}(L/h) = CL_{int} \times MPPGL \times \text{Liver weight}
[ 4 ]

where,

MPPGL=101.407+0.0158×Age(years)−0.00038×Age2+0.0000024×Age3±4MPPGL = 101.407 + 0.0158 \times Age\text{(years)} - 0.00038 \times Age^2 + 0.0000024 \times Age^3 \pm 4
[ 5 ]

Apparent clearance (CLapp ) is the sum of intrinsic clearances of all metabolizing enzymes involved.

CLapp=∑CLint,enzymesCL_{app} = \sum CL_{int,enzymes}
[ 6 ]

Hepatic clearance (CLhep ) is computed using the following equation,2

CLhep=Qhv×fub×CLappQhv+fub×CLappCL_{hep} = \frac{Q_{hv} \times fu_b \times CL_{app}}{Q_{hv} + fu_b \times CL_{app}}
[ 7 ]

where Qhv is total blood flow through liver, fub is unbound fraction in blood and CLapp is sum of intrinsic clearances.

References

  1. Barter ZE, Chowdry JE, Harlow JR, Snawder JE, Lipscomb JC, Rostami-Hodjegan A. Covariation of human microsomal protein per gram of liver with age: absence of influence of operator and sample storage may justify interlaboratory data pooling. Drug Metabolism and Disposition. 2008 Dec;36(12):2405-9.https://doi.org/10.1124/dmd.108.021311
  2. Riley RJ, McGinnity DF, Austin RP. A unified model for predicting human hepatic, metabolic clearance from in vitro intrinsic clearance data in hepatocytes and microsomes. Drug Metabolism and Disposition. 2005;33(9):1304-11.https://doi.org/10.1124/dmd.105.004259
  3. Johnson TN, Rostami-Hodjegan A, Tucker GT. Prediction of the Clearance of Eleven Drugs and Associated Variability in Neonates, Infants and Children. Clinical Pharmacokinetics. 2006 2006/09/01;45(9):931-56.https://doi.org/10.2165/00003088-200645090-00005
  4. Paine MF, Khalighi M, Fisher JM, Shen DD, Kunze KL, Marsh CL, et al. Characterization of interintestinal and intraintestinal variations in human CYP3A-dependent metabolism. J Pharmacol Exp Ther. 1997;283(3):1552-62.https://www.ncbi.nlm.nih.gov/pubmed/9400033
  5. Gertz M, Harrison A, Houston JB, Galetin A. Prediction of human intestinal first-pass metabolism of 25 CYP3A substrates from in vitro clearance and permeability data. Drug Metabolism and Disposition. 2010;38(7):1147-58.https://doi.org/10.1124/dmd.110.032649
< Drug Inputs
Induction >