Translational mixed-effects PKPD modelling of recombinant human growth hormone - from hypophysectomized rat to patients

A Thorsted, P Thygesen, H Agersø, T Laursen, M Kreilgaard

    5 Citations (Scopus)

    Abstract

    Background and Purpose We aimed to develop a mechanistic mixed-effects pharmacokinetic (PK)-pharmacodynamic (PD) (PKPD) model for recombinant human growth hormone (rhGH) in hypophysectomized rats and to predict the human PKPD relationship. Experimental Approach A non-linear mixed-effects model was developed from experimental PKPD studies of rhGH and effects of long-term treatment as measured by insulin-like growth factor 1 (IGF-1) and bodyweight gain in rats. Modelled parameter values were scaled to human values using the allometric approach with fixed exponents for PKs and unscaled for PDs and validated through simulations relative to patient data. Key Results The final model described rhGH PK as a two compartmental model with parallel linear and non-linear elimination terms, parallel first-order absorption with a total s.c. bioavailability of 87% in rats. Induction of IGF-1 was described by an indirect response model with stimulation of kin and related to rhGH exposure through an Emax relationship. Increase in bodyweight was directly linked to individual concentrations of IGF-1 by a linear relation. The scaled model provided robust predictions of human systemic PK of rhGH, but exposure following s.c. administration was over predicted. After correction of the human s.c. absorption model, the induction model for IGF-1 well described the human PKPD data. Conclusions A translational mechanistic PKPD model for rhGH was successfully developed from experimental rat data. The model links a clinically relevant biomarker, IGF-1, to a primary clinical end-point, growth/bodyweight gain. Scaling of the model parameters provided robust predictions of the human PKPD in growth hormone-deficient patients including variability.

    Original languageEnglish
    JournalBritish Journal of Pharmacology
    Volume173
    Issue number11
    Pages (from-to)1742-55
    Number of pages14
    ISSN0007-1188
    DOIs
    Publication statusPublished - 1 Jun 2016

    Keywords

    • Journal Article

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