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Chetty M, Li L, Rose R, et al. Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model. Front Immunol. 2015;5:670doi: 10.3389/fimmu.2014.00670.
Chetty, M., Li, L., Rose, R., Machavaram, K., Jamei, M., Rostami-Hodjegan, A., & Gardner, I. (2014). Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model. Frontiers in immunology, 5670. https://doi.org/10.3389/fimmu.2014.00670
Chetty, Manoranjenni, et al. "Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model." Frontiers in immunology vol. 5 (2014): 670. doi: https://doi.org/10.3389/fimmu.2014.00670
Chetty M, Li L, Rose R, Machavaram K, Jamei M, Rostami-Hodjegan A, Gardner I. Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model. Front Immunol. 2015 Jan 05;5:670. doi: 10.3389/fimmu.2014.00670. eCollection 2014. PMID: 25601866; PMCID: PMC4283607.
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Front Immunol. 2015 Jan 05;5:670. doi: 10.3389/fimmu.2014.00670. eCollection 2014.

Prediction of the Pharmacokinetics, Pharmacodynamics, and Efficacy of a Monoclonal Antibody, Using a Physiologically Based Pharmacokinetic FcRn Model.

Frontiers in immunology

Manoranjenni Chetty, Linzhong Li, Rachel Rose, Krishna Machavaram, Masoud Jamei, Amin Rostami-Hodjegan, Iain Gardner

Affiliations

  1. Simcyp Limited (a Certara Company) , Sheffield , UK.
  2. Simcyp Limited (a Certara Company) , Sheffield , UK ; Manchester Pharmacy School, Manchester University , Manchester , UK.

PMID: 25601866 PMCID: PMC4283607 DOI: 10.3389/fimmu.2014.00670

Abstract

Although advantages of physiologically based pharmacokinetic models (PBPK) are now well established, PBPK models that are linked to pharmacodynamic (PD) models to predict pharmacokinetics (PK), PD, and efficacy of monoclonal antibodies (mAbs) in humans are uncommon. The aim of this study was to develop a PD model that could be linked to a physiologically based mechanistic FcRn model to predict PK, PD, and efficacy of efalizumab. The mechanistic FcRn model for mAbs with target-mediated drug disposition within the Simcyp population-based simulator was used to simulate the pharmacokinetic profiles for three different single doses and two multiple doses of efalizumab administered to virtual Caucasian healthy volunteers. The elimination of efalizumab was modeled with both a target-mediated component (specific) and catabolism in the endosome (non-specific). This model accounted for the binding between neonatal Fc receptor (FcRn) and efalizumab (protective against elimination) and for changes in CD11a target concentration. An integrated response model was then developed to predict the changes in mean Psoriasis Area and Severity Index (PASI) scores that were measured in a clinical study as an efficacy marker for efalizumab treatment. PASI scores were approximated as continuous and following a first-order asymptotic progression model. The reported steady state asymptote (Y ss) and baseline score [Y (0)] was applied and parameter estimation was used to determine the half-life of progression (T p) of psoriasis. Results suggested that simulations using this model were able to recover the changes in PASI scores (indicating efficacy) observed during clinical studies. Simulations of both single dose and multiple doses of efalizumab concentration-time profiles as well as suppression of CD11a concentrations recovered clinical data reasonably well. It can be concluded that the developed PBPK FcRn model linked to a PD model adequately predicted PK, PD, and efficacy of efalizumab.

Keywords: FcRn model; PBPK models; PBPK/PD; efalizumab; monoclonal antibodies

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