Translational systems biology and voice pathophysiology

Nicole Y.K. Li, Katherine Verdolini Abbott, Clark Rosen, Gary An, Patricia A. Hebda, Yoram Vodovotz

Research output: Contribution to journalReview articlepeer-review

14 Scopus citations

Abstract

Objectives/Hypothesis: Personalized medicine has been called upon to tailor healthcare to an individual's needs. Evidence-based medicine (EBM) has advocated using randomized clinical trials with large populations to evaluate treatment effects. However, due to large variations across patients, the results are likely not to apply to an individual patient. We suggest that a complementary, systems biology approach using computational modeling may help tackle biological complexity in order to improve ultimate patient care. The purpose of the article is: 1) to review the pros and cons of EBM, and 2) to discuss the alternative systems biology method and present its utility in clinical voice research. Study Design: Tutorial. Methods: Literature review and discussion. Results: We propose that translational systems biology can address many of the limitations of EBM pertinent to voice and other health care domains, and thus complement current health research models. In particular, recent work using mathematical modeling suggests that systems biology has the ability to quantify the highly complex biologic processes underlying voice pathophysiology. Recent data support the premise that this approach can be applied specifically in the case of phonotrauma and surgically induced vocal fold trauma, and may have particular power to address personalized medicine. Conclusions: We propose that evidence around vocal health and disease be expanded beyond a population-based method to consider more fully issues of complexity and systems interactions, especially in implementing personalized medicine in voice care and beyond.

Original languageEnglish
Pages (from-to)511-515
Number of pages5
JournalLaryngoscope
Volume120
Issue number3
DOIs
StatePublished - Mar 2010
Externally publishedYes

Keywords

  • Modeling
  • Systems biology
  • Vocal folds
  • Wound healing

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