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Assessing the Impact of Liver or Kidney Disease on Pharmacokinetics

Impaired hepatic or renal function can have a major impact on pharmacokinetics. There is a high risk of adverse events in patients with these conditions. Major pharmaceutical companies and drug regulatory agencies use physiologically-based pharmacokinetic (PBPK) modeling in virtual populations to investigate the impact of hepatic or renal impairment on drug exposure as a supplement to clinical investigation. PBPK modeling also helps guide dosage adjustments in these patient groups.

The challenge of determining optimal dosing in patients with organ impairment

Thorough investigation of all the potential risks of drug therapy has to be carefully balanced with the ethical concerns of conducting studies in vulnerable subjects. The Simcyp® Consortium of pharmaceutical companies identified the need to extend PBPK modeling to special populations to assist in decision making as to whether, when and how to conduct clinical trials.

Using modeling to predict changes in drug exposure for patients with liver disease

Hepatic impairment models within the Simcyp Simulator incorporate relevant information on demographics, changes in hepatic blood flow, liver size, cytochrome P450 enzymes, plasma protein binding and renal function. They represent three subpopulations with varying disease severity corresponding to Child-Pugh scores A (mild), B (moderate) and C (severe) for liver cirrhosis. An evaluation study looking at systemic and oral clearance and associated variability found good agreement between the simulated results and observed values for a range of drugs.1

Surprisingly, patients with cirrhosis may also have reduced intestinal CYP3A4 expression and catalytic activity.2 Other intestinal CYPs are assumed to change proportionately and in parallel to CYP3A4/5 with the severity of cirrhosis. The Simcyp Simulator v15 has been updated to quantify intestinal CYPs using enzyme activity rather than protein expression. This is a more accurate approach because it accounts for relevant co-factors such as B5. Other updates to cirrhosis models include:

  • Update to CYP2C9 genotype abundance with Child-Pugh score in liver and intestine
  • Update to demographics
  • Male/female CYP3A4/5 correlation in cirrhosis

In its application to the US FDA for regulatory approval of the hepatitis C drug OlysioTM (simeprevir), Janssen Pharmaceuticals® used the Simcyp mild hepatic impairment model to represent a population of patients with hepatitis C due to the similar characteristics in relation to the numbers of functional hepatocytes and the expression of CYP enzymes. The simulated increase in drug exposure was 2.8-fold that of healthy subjects, mirroring the approximate 2.5- fold increase observed in clinical trials in patients3, providing a surrogate disease population for PBPK modeling.

Scientists at Pfizer® have also used the Simcyp models to predict changes in axitinib plasma exposures in subjects with mild or moderate hepatic impairment. This assisted in the development of a Phase I clinical study, “providing confidence” in dose selection.4

Using modeling to predict changes in drug exposure for patients with kidney disease

Simcyp renal impairment models have also been developed and evaluated for a range of drugs including those with complex kinetics (that undergo auto-inhibition, have metabolites that are potent inhibitors and are taken up by liver transporters) as well as those that undergo extensive metabolism in the liver and have negligible renal clearance.5

A retrograde approach was used to derive CYP3A4 abundance values in renal impairment. The latest version of the Simulator includes updated values for CYP3A4 for mild, moderate, and severe renal impairment scenarios.

Simulations allow complex scenarios to be investigated without trials

Early prediction of the potential effects of liver or kidney disease on PK can have significant time and cost saving benefits in drug development through avoidance of unnecessary trials and optimization of trial design. Simulations, which are increasingly being accepted in regulatory review, allow complex scenarios—which may never be encountered in the clinic—to be safely investigated.

PBPK modeling and simulation in virtual populations has been used strategically in support of the regulatory submission for a new hepatitis C therapy as well as guiding decision making prior to Phase I clinical trials.


[1] Johnson TN, Boussery K, Rowland-Yeo K, Tucker GT, Rostami-Hodjegan A. A semi-mechanistic model to predict the effects of liver cirrhosis on drug clearance. Clinical Pharmacokinetics. 2010;49(3):189-206. (Web link >)

[2] McConn DJ, Lin YS, Mathisen TL, Blough DK, Xu Y, Hashizume T, Taylor SL, Thummel KE, Shuhart MC. Reduced duodenal cytochrome P450 3A protein expression and catalytic activity in patients with cirrhosis. Clinical Pharmacology & Therapeutics. 2009 Apr;85(4):387-93. (Web link >)

[3] US FDA Clinical Pharmacology and Biopharmaceutics Review—Simeprevir (Web link >)

[4] Tortorici MA, Toh M, Rahavendran SV, Labadie RR, Alvey CW, Marbury T, Fuentes E, Green M, Ni G, Hee B, Pithavala YK. Influence of mild and moderate hepatic impairment on axitinib pharmacokinetics. Investigational New Drugs. 2011; 29(6):1370-80. (Web link >)

[5] Rowland Yeo K, Aarabi M, Jamei M, Rostami-Hodjegan A. Modeling and predicting drug pharmacokinetics in patients with renal impairment. Expert Reviews in Clinical Pharmacology. 2011;4(2):261-74. (Web link >)

All information presented derive from public source materials.

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By: Trevor Johnson

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