Clinical research design and statistical analysis for personalized medicine

Yasunori Sato, Kengo Nagashima, Chikuma Hamada

Research output: Contribution to journalReview article

Abstract

Interindividual variation in drug response among patients is well known and poses a serious problem in medicine. The variation could be due to multiple factors including those of the host (e. g., age, genetic and environmental factors) and disease (pathophysiological phenotypes). The complex interplay of these factors may influence pharmacodynamic responses such as adverse effects and efficacy, as well as pharmacokinetic manifestations. However, at present, few biomarkers can predict responders and non-responders, and those who might experience adverse reactions for the same medication and dose. In order to realize personalized medicine, rigorous development of biomarkers is required to identify new biomarkers that may change clinical practice. In this review, we first introduce how biomarkers may be used as targets and the difference between prognostic and predictive markers. Next, we focus on confirmatory clinical trial designs for biomarker development and introduce their application in actual studies. Finally, we introduce exploratory statistical screening techniques for detecting biomarkers in phase I and pharmacokinetics studies.

Original languageEnglish
Pages (from-to)291-300
Number of pages10
JournalJapanese Journal of Clinical Pharmacology and Therapeutics
Volume41
Issue number6
DOIs
Publication statusPublished - 2010 Nov 1
Externally publishedYes

Keywords

  • Biomarker
  • Clinical trial design
  • Personalized medicine
  • Pharmacogenomics

ASJC Scopus subject areas

  • Pharmacology
  • Pharmacology (medical)

Fingerprint Dive into the research topics of 'Clinical research design and statistical analysis for personalized medicine'. Together they form a unique fingerprint.

Cite this