Literature DB >> 11103759

Prediction of the outcome of a phase 3 clinical trial of an antischizophrenic agent (quetiapine fumarate) by simulation with a population pharmacokinetic and pharmacodynamic model.

H C Kimko1, S S Reele, N H Holford, C C Peck.   

Abstract

A completed phase 3 trial result was simulated 100 times on the basis of a simulation model of quetiapine fumarate (Seroquel), an antischizophrenic agent. The simulation was executed by analysts who were completely blinded from results of the actual trial until after the simulations were submitted to the holder of the trial results. Data from two clinical investigations of quetiapine in patients with schizophrenia were analyzed by use of nonlinear mixed effects modeling to derive a population pharmacokinetic- and pharmacodynamic-based simulation model. The time course of quetiapine concentrations was described by use of a one-compartment open linear pharmacokinetic model with first-order absorption and elimination. The combination of an inhibitory maximum effect pharmacodynamic model for the active treatment effect and a linear function of time for the placebo effect characterized the observed time course of change in the Brief Psychiatric Rating Scale. Simulation results were compared with those in the actual trial to evaluate how well the simulations predicted the outcome. The actual trial results for all doses except the placebo group fell within the predicted Brief Psychiatric Rating Scale scores +/- 1 SE. Unlike the phase 2 trial, from which the pharmacokinetic/pharmacodynamic model was developed, the placebo group in the actual phase 3 trial showed deterioration of Brief Psychiatric Rating Scale scores with time. We conclude that variable placebo responses observed in short-term studies of schizophrenia provide an inadequate basis for the modeling and simulation of placebo subjects in clinical trials. Knowledge of the range of placebo response observed in other studies may have provided an improved basis for the placebo effect model. The model for active drug produced adequate predictions of the actual trial outcomes.

Entities:  

Mesh:

Substances:

Year:  2000        PMID: 11103759     DOI: 10.1067/mcp.2000.110975

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  23 in total

Review 1.  Economic evaluations during early (phase II) drug development: a role for clinical trial simulations?

Authors:  D A Hughes; T Walley
Journal:  Pharmacoeconomics       Date:  2001       Impact factor: 4.981

2.  Simultaneous vs. sequential analysis for population PK/PD data I: best-case performance.

Authors:  Liping Zhang; Stuart L Beal; Lewis B Sheiner
Journal:  J Pharmacokinet Pharmacodyn       Date:  2003-12       Impact factor: 2.745

Review 3.  Evidence of effectiveness: how much can we extrapolate from existing studies?

Authors:  Howard Lee; Dong-Seok Yim; Honghui Zhou; Carl C Peck
Journal:  AAPS J       Date:  2005-10-05       Impact factor: 4.009

Review 4.  Pharmacokinetics/Pharmacodynamics and the stages of drug development: role of modeling and simulation.

Authors:  Jenny Y Chien; Stuart Friedrich; Michael A Heathman; Dinesh P de Alwis; Vikram Sinha
Journal:  AAPS J       Date:  2005-10-07       Impact factor: 4.009

Review 5.  Integrated pharmacokinetics and pharmacodynamics in drug development.

Authors:  Jasper Dingemanse; Silke Appel-Dingemanse
Journal:  Clin Pharmacokinet       Date:  2007       Impact factor: 6.447

6.  Structural models describing placebo treatment effects in schizophrenia and other neuropsychiatric disorders.

Authors:  Venkatesh Pilla Reddy; Magdalena Kozielska; Martin Johnson; An Vermeulen; Rik de Greef; Jing Liu; Geny M M Groothuis; Meindert Danhof; Johannes H Proost
Journal:  Clin Pharmacokinet       Date:  2011-07       Impact factor: 6.447

7.  Need for Outcome Scenario Analysis of Clinical Trials in Diabetes.

Authors:  Rosa Garcia-Verdugo; Michael Erbach; Oliver Schnell
Journal:  J Diabetes Sci Technol       Date:  2016-10-05

8.  Modelling and simulation of the Positive and Negative Syndrome Scale (PANSS) time course and dropout hazard in placebo arms of schizophrenia clinical trials.

Authors:  Venkatesh Pilla Reddy; Magdalena Kozielska; Martin Johnson; Ahmed Abbas Suleiman; An Vermeulen; Jing Liu; Rik de Greef; Geny M M Groothuis; Meindert Danhof; Johannes H Proost
Journal:  Clin Pharmacokinet       Date:  2012-04-01       Impact factor: 6.447

9.  Dose selection using a semi-mechanistic integrated glucose-insulin-glucagon model: designing phase 2 trials for a novel oral glucokinase activator.

Authors:  Xin Zhang; Karen Schneck; Juliana Bue-Valleskey; Kwee Poo Yeo; Michael Heathman; Vikram Sinha
Journal:  J Pharmacokinet Pharmacodyn       Date:  2012-12-22       Impact factor: 2.745

10.  Development of a placebo effect model combined with a dropout model for bipolar disorder.

Authors:  Wan Sun; Thomas P Laughren; Hao Zhu; Guenther Hochhaus; Yaning Wang
Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-03-02       Impact factor: 2.745

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.