Lockwood2006 - Alzheimer's Disease PBPK model

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Short description
Lockwood2006 - AlzheimersDisease PBPK model
A mathematical model to predict the effectiveness of CI-1017 (muscarinic agonist) for Alzheimer's disease by evaluating changes in ADAS-cog score.

This model is described in the article:

Lockwood P, Ewy W, Hermann D, Holford N.
Pharm. Res. 2006 Sep; 23(9): 2050-2059

Abstract:

OBJECTIVE: Clinical trial simulation (CTS) was used to select a robust design to test the hypothesis that a new treatment was effective for Alzheimer's disease (AD). Typically, a parallel group, placebo controlled, 12-week trial in 200-400 AD patients would be used to establish drug effect relative to placebo (i.e., Ho: Drug Effect = 0). We evaluated if a crossover design would allow smaller and shorter duration trials. MATERIALS AND METHODS: A family of plausible drug and disease models describing the time course of the AD assessment scale (ADAS-Cog) was developed based on Phase I data and literature reports of other treatments for AD. The models included pharmacokinetic, pharmacodynamic, disease progression, and placebo components. Eight alternative trial designs were explored via simulation. One hundred replicates of each combination of drug and disease model and trial design were simulated. A 'positive trial' reflecting drug activity was declared considering both a dose trend test (p < 0.05) and pair-wise comparisons to placebo (p < 0.025). RESULTS: A 4 x 4 Latin Square design was predicted to have at least 80% power to detect activity across a range of drug and disease models. The trial design was subsequently implemented and the trial was completed. Based on the results of the actual trial, a conclusive decision about further development was taken. The crossover design provided enhanced power over a parallel group design due to the lower residual variability. CONCLUSION: CTS aided the decision to use a more efficient proof of concept trial design, leading to savings of up to US 4 M dollars in direct costs and a firm decision 8-12 months earlier than a 12-week parallel group trial.

This model is hosted on BioModels Database and identified by: BIOMD0000000673.

To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8.

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Format
SBML (L2V4)
Related Publication
  • Application of clinical trial simulation to compare proof-of-concept study designs for drugs with a slow onset of effect; an example in Alzheimer's disease.
  • Lockwood P, Ewy W, Hermann D, Holford NH
  • Pharmaceutical research , 9/ 2006 , Volume 23 , Issue 9 , pages: 2050-2059
  • Pfizer Global Research and Development, Ann Arbor, Michigan, USA. peter.lockwood@pfizer.com
  • Clinical trial simulation (CTS) was used to select a robust design to test the hypothesis that a new treatment was effective for Alzheimer's disease (AD). Typically, a parallel group, placebo controlled, 12-week trial in 200-400 AD patients would be used to establish drug effect relative to placebo (i.e., Ho: Drug Effect = 0). We evaluated if a crossover design would allow smaller and shorter duration trials.A family of plausible drug and disease models describing the time course of the AD assessment scale (ADAS-Cog) was developed based on Phase I data and literature reports of other treatments for AD. The models included pharmacokinetic, pharmacodynamic, disease progression, and placebo components. Eight alternative trial designs were explored via simulation. One hundred replicates of each combination of drug and disease model and trial design were simulated. A 'positive trial' reflecting drug activity was declared considering both a dose trend test (p < 0.05) and pair-wise comparisons to placebo (p < 0.025).A 4 x 4 Latin Square design was predicted to have at least 80% power to detect activity across a range of drug and disease models. The trial design was subsequently implemented and the trial was completed. Based on the results of the actual trial, a conclusive decision about further development was taken. The crossover design provided enhanced power over a parallel group design due to the lower residual variability.CTS aided the decision to use a more efficient proof of concept trial design, leading to savings of up to US 4 M dollars in direct costs and a firm decision 8-12 months earlier than a 12-week parallel group trial.
Contributors
Camille Laibe, administrator

Metadata information

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BioModels Database MODEL1006230054
BIOMD0000000673
isDescribedBy
hasPart
isVersionOf
occursIn
Curation status
Curated
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Model files

BIOMD0000000673_url.xml SBML L2V4 representation of Lockwood2006 - Alzheimer\s Disease PBPK model 63.23 KB Preview | Download

Additional files

BIOMD0000000673.pdf Auto-generated PDF file 145.98 KB Preview | Download
BIOMD0000000673_urn.xml Auto-generated SBML file with URNs 63.18 KB Preview | Download
BIOMD0000000673.vcml Auto-generated VCML file 22.17 KB Preview | Download
BIOMD0000000673.png Auto-generated Reaction graph (PNG) 4.27 KB Preview | Download
BIOMD0000000673.m Auto-generated Octave file 6.33 KB Preview | Download
MODEL1006230054_edited.sedml A parameter scan will produce a similar figure to figure 1 (Sigmoidal response model, bottom left) of the reference publication. Different response models can be implemented by changing the quantity 'MODEL_TYPE' from 0 to 4 with 0=Inactive, 1=Linear, 2=Hyperbolic, 3=Sigmoidal, 4=U-Shaped. 3.91 KB Preview | Download
BIOMD0000000673.xpp Auto-generated XPP file 5.03 KB Preview | Download
BIOMD0000000673-biopax2.owl Auto-generated BioPAX (Level 2) 3.67 KB Preview | Download
MODEL1006230054_edited.cps A parameter scan will produce similar figures to figure 1 of the reference publication. Different response models can be implemented by changing the quantity 'MODEL_TYPE' from 0 to 4 with 0=Inactive, 1=Linear, 2=Hyperbolic, 3=Sigmoidal, 4=U-Shaped. 56.42 KB Preview | Download
BIOMD0000000673.svg Auto-generated Reaction graph (SVG) 845.00 bytes Preview | Download
BIOMD0000000673.sci Auto-generated Scilab file 154.00 bytes Preview | Download
BIOMD0000000673-biopax3.owl Auto-generated BioPAX (Level 3) 3.70 KB Preview | Download

  • Model originally submitted by : Camille Laibe
  • Submitted: Jun 23, 2010 10:12:15 AM
  • Last Modified: Feb 14, 2018 3:54:56 PM
Revisions
  • Version: 3 public model Download this version
    • Submitted on: Feb 14, 2018 3:54:56 PM
    • Submitted by: administrator
    • With comment: Current curated version of Lockwood2006_PKPD_AlzheimersDisease
  • Version: 2 public model Download this version
    • Submitted on: Jun 25, 2010 2:17:54 PM
    • Submitted by: Camille Laibe
    • With comment: Current version of Lockwood2006_PKPD_AlzheimersDisease
  • Version: 1 public model Download this version
    • Submitted on: Jun 23, 2010 10:12:15 AM
    • Submitted by: Camille Laibe
    • With comment: Original import of Lockwood2006_PKPD_AlzheimersDisease
Curator's comment:
(added: 01 Mar 2018, 15:28:59, updated: 01 Mar 2018, 15:28:59)
Similar figures of figure 1 of the reference publication have been produced. Raw ADAS-cog scores have been plotted for varied CeA (CI-1017) concentration using a linear (top left), hyperbolic (top right) and signmoidal (bottom left) response model. Simulations were performed in COPASI 4.22 (Build 170) and figures were generated with MATLAB R2014. Different response models can be implemented by changing the quantity 'MODEL_TYPE' from 0 to 4 with 0=Inactive, 1=Linear, 2=Hyperbolic, 3=Sigmoidal, 4=U-Shaped. Simulations were performed using a parameter scan varying the initial value of CeA from 0 to 75 in increments of 1 with the parameter scan task set to 'time course' and plot type set to 'points'.