Literature DB >> 22773164

From in vitro EC₅₀ to in vivo dose-response for antiretrovirals using an HIV disease model. Part II: application to drug development.

Jing Fang1, Pravin R Jadhav.   

Abstract

The purpose of this research was to qualify a previously derived quantitative model-based framework that proposed an in vitro-in vivo linkage to predict the dose-response relationship of an antiretroviral (ARV) new molecular entity (NME) in a monotherapy trial. Human immunodeficiency virus (HIV)-1 ribonucleic acid (RNA) data from monotherapy trials in ARV naïve/experienced HIV-infected subjects for eight drugs (i.e. application case, a representative drug for a given class used for external validation) across four distinct classes of ARV agents (co-receptor antagonists; non-nucleoside reverse transcriptase inhibitors; nucleotide reverse transcriptase inhibitors; and integrase strand transfer inhibitors) were obtained. Using the in vitro EC₅₀ (protein binding corrected) and a class-specific scaling factor (SF), the in vivo IC₅₀ was calculated for each drug. The integrated pharmacokinetic (PK)-pharmacodynamic (PD) disease model used the predicted in vivo IC₅₀ to simulate the HIV-1 RNA-time profiles for dosing regimens that were studied in the monotherapy trials for each drug. The simulated HIV-1 RNA time profiles were then compared to the observed data. The simulated HIV-1 RNA-time profiles matched well with those observed in the monotherapy trials except for one drug in the INSTIs class. The derived SF represents a useful in vitro-in vivo linkage to predict the dose-response relationship for a NME using in vitro data. The mechanistic PK-PD disease model-based framework is useful to assist the dose selection for monotherapy trials and comparator modeling approaches.

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Year:  2012        PMID: 22773164     DOI: 10.1007/s10928-012-9257-1

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  31 in total

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  2 in total

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Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-07-11       Impact factor: 2.745

2.  Characterizing Class-Specific Exposure-Viral Load Suppression Response of HIV Antiretrovirals Using A Model-Based Meta-Analysis.

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Journal:  Clin Transl Sci       Date:  2016-05-12       Impact factor: 4.689

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