Literature DB >> 20170207

A semi-mechanistic model to predict the effects of liver cirrhosis on drug clearance.

Trevor N Johnson1, Koen Boussery, Karen Rowland-Yeo, Geoffrey T Tucker, Amin Rostami-Hodjegan.   

Abstract

BACKGROUND AND
OBJECTIVE: Liver cirrhosis is characterized by a decrease in functional hepatocytes, lowered circulating levels of plasma proteins and alterations in blood flow due to the development of portacaval shunts. Depending on the interplay between these parameters and the characteristics of an administered drug, varying degrees of impaired systemic clearance and first-pass metabolism are anticipated. The Simcyp Population-based ADME Simulator has already been used successfully to incorporate genetic, physiological and demographic attributes of certain subgroups within healthy populations into in vitro-in vivo extrapolation (IVIVE) of xenobiotic clearance. The objective of this study was to extend population models to predict systemic and oral drug clearance in relation to the severity of liver cirrhosis.
METHODS: Information on demographics, changes in hepatic blood flow, cytochrome P450 enzymes, liver size, plasma protein binding and renal function was incorporated into three separate population libraries. The latter corresponded to Child-Pugh scores A (mild), B (moderate) and C (severe) liver cirrhosis. These libraries, together with mechanistic IVIVE within the Simcyp Simulator, were used to predict the clearance of intravenous and oral midazolam, oral caffeine, intravenous and oral theophylline, intravenous and oral metoprolol, oral nifedipine, oral quinidine, oral diclofenac, oral sildenafil, and intravenous and oral omeprazole. The simulated patients matched the clinical studies as closely as possible with regard to demographics and Child-Pugh scores. Predicted clearance values in both healthy control and liver cirrhosis populations were compared with observed values, as were the fold increases in clearance values between these populations.
RESULTS: There was good agreement (lack of statistically significant difference, two-tailed paired t-test) between observed and predicted clearance ratios, with the exception of those for two studies of intravenous omeprazole. Predicted clearance ratios were within 0.8- to 1.25-fold of observed ratios in 65% of cases (range 0.34- to 2.5-fold).
CONCLUSION: The various drugs that were studied showed different changes in clearance in relation to disease severity, and a 'one size fits all' solution does not exist without considering the multiple sources of the changes. Predictions of the effects of liver cirrhosis on drug clearance are of potential value in the design of clinical studies during drug development and, clinically, in the assessment of likely dosage adjustment.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20170207     DOI: 10.2165/11318160-000000000-00000

Source DB:  PubMed          Journal:  Clin Pharmacokinet        ISSN: 0312-5963            Impact factor:   6.447


  107 in total

1.  Reduced duodenal cytochrome P450 3A protein expression and catalytic activity in patients with cirrhosis.

Authors:  D J McConn; Y S Lin; T L Mathisen; D K Blough; Y Xu; T Hashizume; S L Taylor; K E Thummel; M C Shuhart
Journal:  Clin Pharmacol Ther       Date:  2009-02-11       Impact factor: 6.875

2.  Glomerular filtration rate measurement in cirrhotic patients with renal failure.

Authors:  L Roy; L Legault; G Pomier-Layrargues
Journal:  Clin Nephrol       Date:  1998-12       Impact factor: 0.975

3.  Pharmacokinetics of chlormethiazole in healthy volunteers and patients with cirrhosis of the liver.

Authors:  P J Pentikäinen; P J Neuvonen; K G Jostell
Journal:  Eur J Clin Pharmacol       Date:  1980-04       Impact factor: 2.953

4.  Hepatic artery hemodynamic responsiveness to altered portal blood flow in normal and cirrhotic livers.

Authors:  T Iwao; A Toyonaga; H Shigemori; K Oho; T Sakai; C Tayama; H Masumoto; M Sato; K Tanikawa
Journal:  Radiology       Date:  1996-09       Impact factor: 11.105

5.  Creatinine clearance: an inadequate marker of renal filtration in patients with early posthepatitic cirrhosis (Child A) without fluid retention and muscle wasting.

Authors:  N G DeSanto; P Anastasio; C Loguercio; L Spitali; C Del Vecchio Blanco; M Corvinelli; M Cirillo
Journal:  Nephron       Date:  1995       Impact factor: 2.847

6.  Different alterations of cytochrome P450 3A4 isoform and its gene expression in livers of patients with chronic liver diseases.

Authors:  Li-Qun Yang; Shen-Jing Li; Yun-Fei Cao; Xiao-Bo Man; Wei-Feng Yu; Hong-Yang Wang; Meng-Chao Wu
Journal:  World J Gastroenterol       Date:  2003-02       Impact factor: 5.742

7.  Pharmacokinetics of midazolam following intravenous and oral administration in patients with chronic liver disease and in healthy subjects.

Authors:  P J Pentikäinen; L Välisalmi; J J Himberg; C Crevoisier
Journal:  J Clin Pharmacol       Date:  1989-03       Impact factor: 3.126

8.  Pharmacokinetics of omeprazole in cirrhotic patients.

Authors:  M Rinetti; M B Regazzi; P Villani; M Tizzoni; R Sivelli
Journal:  Arzneimittelforschung       Date:  1991-04

9.  Liver volume in patients with or without chronic liver diseases.

Authors:  X Z Lin; Y N Sun; Y H Liu; B S Sheu; B N Cheng; C Y Chen; H M Tsai; C L Shen
Journal:  Hepatogastroenterology       Date:  1998 Jul-Aug

10.  Quinidine pharmacokinetics in patients with cirrhosis or receiving propranolol.

Authors:  K M Kessler; W C Humphries; M Black; J F Spann
Journal:  Am Heart J       Date:  1978-11       Impact factor: 4.749

View more
  65 in total

1.  Prediction of drug clearance in a smoking population: modeling the impact of variable cigarette consumption on the induction of CYP1A2.

Authors:  David R Plowchalk; Karen Rowland Yeo
Journal:  Eur J Clin Pharmacol       Date:  2012-01-19       Impact factor: 2.953

2.  Comment on: "A Physiologically Based Pharmacokinetic Drug-Disease Model to Predict Carvedilol Exposure in Adult and Paediatric Heart Failure Patients by Incorporating Pathophysiological Changes in Hepatic and Renal Blood".

Authors:  Guo-Fu Li; Xiao Gu; Guo Yu; Shui-Yu Zhao; Qing-Shan Zheng
Journal:  Clin Pharmacokinet       Date:  2016-01       Impact factor: 6.447

3.  Development of a Physiologically Based Pharmacokinetic Model for Sinogliatin, a First-in-Class Glucokinase Activator, by Integrating Allometric Scaling, In Vitro to In Vivo Exploration and Steady-State Concentration-Mean Residence Time Methods: Mechanistic Understanding of its Pharmacokinetics.

Authors:  Ling Song; Yi Zhang; Ji Jiang; Shuang Ren; Li Chen; Dongyang Liu; Xijing Chen; Pei Hu
Journal:  Clin Pharmacokinet       Date:  2018-10       Impact factor: 6.447

4.  Caffeine, a common active adulterant of cocaine, enhances the reinforcing effect of cocaine and its motivational value.

Authors:  José Pedro Prieto; Cecilia Scorza; Gian Pietro Serra; Valentina Perra; Martín Galvalisi; Juan Andrés Abin-Carriquiry; Giovanna Piras; Valentina Valentini
Journal:  Psychopharmacology (Berl)       Date:  2016-06-07       Impact factor: 4.530

Review 5.  Asunaprevir: A Review of Preclinical and Clinical Pharmacokinetics and Drug-Drug Interactions.

Authors:  Timothy Eley; Tushar Garimella; Wenying Li; Richard J Bertz
Journal:  Clin Pharmacokinet       Date:  2015-12       Impact factor: 6.447

Review 6.  Pharmacokinetic of antiepileptic drugs in patients with hepatic or renal impairment.

Authors:  Gail D Anderson; Shahin Hakimian
Journal:  Clin Pharmacokinet       Date:  2014-01       Impact factor: 6.447

7.  Expression of P450 and nuclear receptors in normal and end-stage Chinese livers.

Authors:  Hong Chen; Zhong-Yang Shen; Wang Xu; Tie-Yan Fan; Jun Li; Yuan-Fu Lu; Ming-Liang Cheng; Jie Liu
Journal:  World J Gastroenterol       Date:  2014-07-14       Impact factor: 5.742

Review 8.  Dose selection based on physiologically based pharmacokinetic (PBPK) approaches.

Authors:  Hannah M Jones; Kapil Mayawala; Patrick Poulin
Journal:  AAPS J       Date:  2012-12-27       Impact factor: 4.009

9.  Physiologically Based Pharmacokinetic Model of the CYP2D6 Probe Atomoxetine: Extrapolation to Special Populations and Drug-Drug Interactions.

Authors:  Weize Huang; Mariko Nakano; Jennifer Sager; Isabelle Ragueneau-Majlessi; Nina Isoherranen
Journal:  Drug Metab Dispos       Date:  2017-08-31       Impact factor: 3.922

10.  Physiologically Based Pharmacokinetic Modeling for Predicting the Effect of Intrinsic and Extrinsic Factors on Darunavir or Lopinavir Exposure Coadministered With Ritonavir.

Authors:  Christian Wagner; Ping Zhao; Vikram Arya; Charu Mullick; Kimberly Struble; Stanley Au
Journal:  J Clin Pharmacol       Date:  2017-06-01       Impact factor: 3.126

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.