Lockwood2006 - Alzheimer's Disease PBPK model

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Model Identifier
BIOMD0000000673
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.

To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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 , PubMed ID: 16906456
  • 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
Submitter of the first revision: Camille Laibe
Submitter of this revision: administrator
Modellers: administrator, Camille Laibe

Metadata information

is (2 statements)
BioModels Database MODEL1006230054
BioModels Database BIOMD0000000673

isDescribedBy (2 statements)
hasPart (1 statement)
isVersionOf (1 statement)
Mathematical Modelling Ontology pharmacodynamics model

occursIn (1 statement)
Human Phenotype Ontology Alzheimer disease


Curation status
Curated

Modelling approach(es)

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Model files

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

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BIOMD0000000673-biopax2.owl Auto-generated BioPAX (Level 2) 3.67 KB Preview | Download
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BIOMD0000000673.sci Auto-generated Scilab file 154.00 Bytes Preview | Download
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BIOMD0000000673_urn.xml Auto-generated SBML file with URNs 63.18 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
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

  • 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

(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions unpublished model revision of this model will only be shown to the submitter and their collaborators.

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'.