Disease Progression Modeling: Key Concepts and Recent Developments

Sarah F. Cook, Robert R. Bies

Research output: Contribution to journalReview article

9 Scopus citations


Disease modeling involves the use of mathematical functions to describe quantitatively the time course of disease progression. In order to characterize the natural progression of disease, these models generally incorporate longitudinal data for some biomarker(s) of disease severity or can incorporate more direct measures of disease severity. Disease models are also often linked to pharmacokinetic–pharmacodynamic models so that the influence of drug treatment on disease progression can be quantified and evaluated. Regulatory agencies have embraced disease progression models as powerful tools that can be used to improve drug development productivity. This article provides a brief overview of key concepts in disease progression modeling followed by illustrative examples from models for Alzheimer’s disease. Finally, recent novel applications in which disease progression models have been linked to cost-effectiveness analysis and genomic analysis are described.

Original languageEnglish (US)
Pages (from-to)221-230
Number of pages10
JournalCurrent Pharmacology Reports
Issue number5
StatePublished - Oct 1 2016
Externally publishedYes


  • Clinical pharmacology
  • Disease progression
  • Drug development
  • Modeling and simulation
  • Pharmacometrics

ASJC Scopus subject areas

  • Biochemistry
  • Genetics
  • Pharmacology
  • Drug Discovery

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