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Journal of Hepatology
Article . 2010 . Peer-reviewed
License: CC BY NC ND
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Journal of Hepatology
Article
License: CC BY NC ND
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Journal of Hepatology
Article . 2010
License: CC BY NC ND
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Pharmacokinetic and pharmacodynamic modeling of pegylated-interferon alfa

Authors: Dimova, Rositsa B.; Talal, Andrew H.;

Pharmacokinetic and pharmacodynamic modeling of pegylated-interferon alfa

Abstract

Center for the Study of Hepatitis C and Division of Gastroenterology and Hepatology, Weill Cornell Medical College, New York, NY, USASee Article, pages 460–467Hepatitis C virus (HCV) infection affects approximately 170 mil-lion individuals worldwide [1,2]. Among those exposed to HCV,between 50% and 80% develop chronic infection that may resultin progressive liver fibrosis and consequently in cirrhosis and/or hepatocellular carcinoma. Among HIV-infected people,approximately 15–30% are co-infected with HCV, and the hepati-tis virus is a leading cause of death in these individuals [3,4].Unfortunately, therapeutic efficacy is diminished in HIV/HCVco-infected compared to HCV mono-infected patients to currentstandard therapy, which consists of pegylated-interferon (PEG-IFN) and ribavirin (RBV) [3]. Two separate formulations of PEG-IFN have been approved, alfa-2a and alfa-2b, each with differentpharmacokinetic profiles [5], and these medications are typicallyadministered for 48 weeks. They can be difficult to tolerate; con-sequently, therapy in those unlikely to respond should be limited.According to current guidelines, patients should be treated for atleast 12 weeks to determine whether a 2-log HCV RNA declinehas occurred,thereby justifying treatment continuation [6]. How-ever, the identification of parameters that could be used earlierfor therapeutic intervention would be of tremendous importance.Successful treatment outcome for HCV in PEG-IFN/RBV treatedpatients has been defined as undetectable HCV RNA in serum6 months after the end of treatment (sustained virologicalresponse [SVR]). Nonresponders (NR) are those in whom serumHCV RNA is detectable 6 months post treatment cessation. SVRoccurs in 27–40% of HIV/HCV coinfected treated patients [3].Mathematical modeling of HCV RNA decay has been used toassess the effectiveness of anti-HCV treatment [7,8]. Early viraldynamic models that used standard IFN alfa assumed constanteffectiveness, which was appropriate when IFN was administeredthrice weekly. In contrast, when patients were treated with PEG-IFN alfa-2b, time-varying IFN concentration was observed [9].Toaccount for these changes, Powers et al. incorporated pharmaco-kinetic/pharmacodynamic parameters into a viral dynamic model[10]. Pharmacokinetics (PK) establishes the connection betweendrug inflow and concentration in blood and includes parameterssuch as drug absorption, elimination, and blood volume. Pharma-codynamics (PD) establishes the connection between drug con-centration and clinical outcome. PK/PD of PEG-IFN/RBV hasbeen modeled through partial differential equations constructedto explain the drug’s mechanism of action [11]. Using mechanis-tic models, one can estimate in vivo parameters that are notdirectly measurable, such as how effective a drug (i.e., IFN) is inblocking virus production, or to make inferences about other clin-ically-useful variables, such as the duration of treatment neces-sary to eradicate the virus [12,13]. Limitations of themechanistic models include difficulty in model validation as wellas computational issues that may arise due to the approximatingand iterative nature of the algorithms used to estimate theparameters and their convergence.An important question is whether PK/PD properties of PEG-IFN/RBV can identify HCV-infected patients early in treatmentwho are unlikely to respond. To address this issue, we con-structed a dynamic model that incorporates PK/PD parametersand applied it to data obtained from 24 HIV/HCV co-infectedpatients treated with PEG-IFN alfa-2b/RBV [14]. We found thatEC

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Keywords

Hepatology, Humans, Interferon-alpha, RNA, Viral, Hepacivirus, Interferon alpha-2, Antiviral Agents, Hepatitis C, Models, Biological, Recombinant Proteins, Polyethylene Glycols

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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