Literature DB >> 23001587

Population pharmacokinetic/pharmacodynamic modelling of the anti-TNF-α polyclonal fragment antibody AZD9773 in patients with severe sepsis.

James W T Yates1, Shampa Das, Guy Mainwaring, John Kemp.   

Abstract

AZD9773 is an ovine-derived, polyclonal, anti-tumour necrosis factor-alpha (TNF-α) antibody fragment. Using data from an AZD9773 Phase IIa study in patients with severe sepsis (clinicaltrials.gov: NCT00615017), a population pharmacokinetic/pharmacodynamic (PK/PD) model was developed. The model assessed the influence of various covariates on the PK of AZD9773 and the relationship between AZD9773 exposure and serological TNF-α concentration. A linear two-compartment model was used to describe AZD9773 concentration-time data. A stepwise covariate analysis was performed on the PK parameters. Subsequently, the serological TNF-α concentrations and drug effect were captured using an indirect response model, with a variable production rate of TNF-α described by a quadratic function. Creatinine clearance (CrCL) was the only covariate with a significant effect on the PK of AZD9773. A typical patient's drug clearance varied with CrCL; the relationship was non-linear. Diagnostic analysis of the PK/PD model showed that the fit was good, both across cohorts and in AZD9773-treated versus placebo patients. Serological TNF-α concentrations and the reduction of measurable serum TNF-α by AZD9773 were well characterized across all the cohorts evaluated in the Phase IIa study. This population PK/PD model was subsequently used to simulate alternative dosing options for a Phase IIb study (clinicaltrials.gov: NCT01145560).

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Year:  2012        PMID: 23001587     DOI: 10.1007/s10928-012-9270-4

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


  12 in total

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2.  Prediction of creatinine clearance from serum creatinine.

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Review 6.  Sepsis and cytokines: current status.

Authors:  T S Blackwell; J W Christman
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Authors:  L B Hinshaw; T E Emerson; F B Taylor; A C Chang; M Duerr; G T Peer; D J Flournoy; G L White; S D Kosanke; C K Murray
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8.  Long-term survival and function after suspected gram-negative sepsis.

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