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Related Experiment Videos

Personalized Drug Dosage - Closing the Loop.

Geoffrey T Tucker1

  • 1Department of Human Metabolism, Medical and Biological Sciences, University of Sheffield, Sheffield, UK. g.t.tucker@sheffield.ac.uk.

Pharmaceutical Research
|December 13, 2016
PubMed
Summary
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This study explores methods for personalized drug dosing, including monitoring drug levels and using computer dashboards. It also discusses creating virtual patient models for precise medication management.

Area of Science:

  • Pharmacology
  • Pharmacokinetics
  • Computational Biology

Background:

  • Individualizing drug dosage is crucial for optimizing therapeutic outcomes and minimizing adverse effects.
  • Traditional dosing strategies often fail to account for patient-specific variability.
  • Advancements in technology offer new avenues for precise medication management.

Purpose of the Study:

  • To provide an overview of current and emerging approaches for individualizing drug dosage.
  • To discuss the integration of various monitoring and computational tools for personalized medicine.
  • To highlight the potential of physiologically-based pharmacokinetic modeling in creating patient-specific simulations.

Main Methods:

  • Review of pharmacodynamic markers for treatment response assessment.
Keywords:
drug dosagepersonalized medicinepharmacogeneticsphysiologically-based pharmacokinetic modelingtherapeutic drug monitoring

Related Experiment Videos

  • Discussion of therapeutic drug monitoring (TDM) of plasma drug concentrations.
  • Exploration of genotyping for predicting drug response.
  • Examination of computer-guided dosing systems ('dashboards').
  • Overview of automatic closed-loop control systems for pharmacological action.
  • Introduction to physiologically-based pharmacokinetic (PBPK) modeling for virtual twin creation.

    • Main Results:

    • Multiple strategies exist for tailoring drug dosage to individual patients.
    • Pharmacodynamic markers and TDM provide real-time feedback on drug efficacy and safety.
    • Genotyping offers predictive insights into patient response to specific medications.
    • Computer-aided systems and closed-loop controls enhance precision and automation in dosing.
    • PBPK modeling enables the development of 'virtual twins' for in silico drug testing and optimization.

    Conclusions:

    • A multimodal approach combining various techniques is essential for effective drug dosage individualization.
    • Technological advancements, particularly PBPK modeling, hold significant promise for the future of personalized pharmacotherapy.
    • The integration of real-time data and predictive modeling will lead to more precise and safer drug treatments.