Using simulation and optimization approach to improve outcome through warfarin precision treatment

Pac Symp Biocomput. 2018;23:412-423.

Abstract

We apply a treatment simulation and optimization approach to develop decision support guidance for warfarin precision treatment plans. Simulation include the use of ∼1,500,000 clinical avatars (simulated patients) generated by an integrated data-driven and domain-knowledge based Bayesian Network Modeling approach. Subsequently, we simulate 30-day individual patient response to warfarin treatment of five clinical and genetic treatment plans followed by both individual and subpopulation based optimization. Sub-population optimization (compared to individual optimization) provides a cost effective and realistic means of implementation of a precision-driven treatment plan in practical settings. In this project, we use the property of minimal entropy to minimize overall adverse risks for the largest possible patient sub-populations and we temper the results by considering both transparency and ease of implementation. Finally, we discuss the improved outcome of the precision treatment plan based on the sub-population optimized decision support rules.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Aged, 80 and over
  • Anticoagulants / administration & dosage
  • Anticoagulants / adverse effects
  • Anticoagulants / therapeutic use*
  • Clinical Trials as Topic / statistics & numerical data
  • Computational Biology / methods
  • Computer Simulation
  • Decision Support Techniques
  • Expert Systems
  • Female
  • Humans
  • Male
  • Middle Aged
  • Pharmacogenomic Testing / statistics & numerical data
  • Precision Medicine / statistics & numerical data
  • Risk Factors
  • Warfarin / administration & dosage
  • Warfarin / adverse effects
  • Warfarin / therapeutic use*

Substances

  • Anticoagulants
  • Warfarin