DDMODEL00000290: Executable_simulated_CPathAD

  public model
Short description:
Real individual clinical data is available at https://codr.c-path.org/ CODR is a unique resource for Critical Path Institute consortia members and qualified researchers to upload and work on valuable scientific data, relevant to biomarkers of drug toxicity, neurodegenerative diseases, and patient-reported outcomes. Critical Path Institute, headquartered in Tucson, Arizona, was established in 2005 as a publicly funded, nonprofit research and education institute to enable collaborations between scientists from the FDA, industry, and academia. Critical Path Institute's mission is to help implement the FDA's Critical Path Initiative by developing faster, safer and smarter pathways to new medical products. To request access: Submit an application
Original code
  • An updated Alzheimer's disease progression model: incorporating non-linearity, beta regression, and a third-level random effect in NONMEM.
  • Conrado DJ, Denney WS, Chen D, Ito K
  • Journal of pharmacokinetics and pharmacodynamics, 12/2014, Volume 41, Issue 6, pages: 581-598
  • Pharmatherapeutics Clinical Pharmacology, Pfizer Inc., Cambridge, MA, 02139, USA, Daniela.Conrado@pfizer.com.
  • Our objective was to expand our understanding of the predictors of Alzheimer's disease (AD) progression to help design a clinical trial on a novel AD medication. We utilized the Coalition Against Major Diseases AD dataset consisting of control-arm data (both placebo and stable background AD medication) from 15 randomized double-blind clinical trials in mild-to-moderate AD patients (4,495 patients; July 2013). Our ADAS-cog longitudinal model incorporates a beta-regression with between-study, -subject, and -residual variability in NONMEM; it suggests that faster AD progression is associated with younger age and higher number of apolipoprotein E type 4 alleles (APOE*4), after accounting for baseline disease severity. APOE*4, in particular, seems to be implicated in the AD pathogenesis. In addition, patients who are already on stable background AD medications appear to have a faster progression relative to those who are not receiving AD medication. The current knowledge does not support a causality relationship between use of background AD medications and higher rate of disease progression, and the correlation is potentially due to confounding covariates. Although causality has not necessarily been demonstrated, this model can inform inclusion criteria and stratification, sample size, and trial duration.
Daniela Conrado
Context of model development: Clinical end-point; Disease Progression model;
Long technical model description: See publication at PMID 25168488 ;
Model compliance with original publication: Yes;
Model implementation requiring submitter’s additional knowledge: No;
Modelling context description: An updated Alzheimer's disease progression model: incorporating non-linearity, beta regression, and a third-level random effect in NONMEM. For access to the real individual clinical trial data go to https://codr.c-path.org/;
Modelling task in scope: estimation;
Nature of research: Early clinical development (Phases I and II); Approval phase/Registration trial (Phase III);
Therapeutic/disease area: CNS;
Annotations are correct.
This model is not certified.
  • Model owner: Daniela Conrado
  • Submitted: May 30, 2018 8:44:06 PM
  • Last Modified: May 30, 2018 8:44:06 PM
Revisions
  • Version: 5 public model Download this version
    • Submitted on: May 30, 2018 8:44:06 PM
    • Submitted by: Daniela Conrado
    • With comment: Updated model annotations.
 
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