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Related Concept Videos

Dosage Regimens: Designs and Approaches01:28

Dosage Regimens: Designs and Approaches

Designing a dosage regimen, which refers to the manner of drug administration, is a complex process involving the selection of drug dose, route, and frequency. This process is underpinned by pharmacokinetic parameters derived from tests and population averages. These parameters are then tailored to patient-specific variables such as diagnosis, demographics, and allergy status. Once therapy commences, therapeutic response monitoring is critical and achieved through clinical and physical...
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Drug response models describe how pharmacological agents interact with biological systems to produce measurable effects. Baseline responses are inherent physiological activities without a drug significantly influencing the observed pharmacological outcomes. Depending on the drug response model employed, these baseline responses may combine with the drug's effect in either an additive or proportional manner.Additive Drug Response ModelIn the additive model, the drug effect is independent of the...
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The Emax drug-concentration effect model is central to pharmacodynamics in drug discovery and development. This model is predicated on the receptor occupancy theory, which posits that the effect of a drug is directly related to the number of receptors occupied by the drug and the resultant complex formation.The model describes the reversible interaction between a drug (C) and a receptor (R) to form a drug-receptor complex (RC). The kinetics of this interaction are quantified by an equation that...
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The empirical approach to drug therapy optimization relies on correlating pharmacological response with administered dosage. Such an approach can be costly, time-consuming, and often yields poor correlation due to variables like formulation factors and drug elimination characteristics. A more precise approach correlates response with plasma drug concentration or the amount of drug in the body, rather than dosage. This is achieved through pharmacokinetic-pharmacodynamic (PK/PD) modeling, which...
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Calculating drug dosage and accumulation in multiple-dose regimens is crucial for achieving therapeutic efficacy while avoiding toxicity. This involves determining the plasma drug concentrations over time to optimize dosing schedules. The principle of superposition is fundamental in this process, allowing for the prediction of drug concentration in plasma following multiple doses based on single-dose data.The principle of superposition asserts that the plasma concentration-time curves from...
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Related Experiment Video

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Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
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Embedding evolutionary game theory into an optimal control framework for drug dosage design.

Sharon Bewick1, Ruoting Yang, Mingjun Zhang

  • 1Department of Mechanical, Aerospace and Biomedical Engineering, The University of Tennessee, Knoxville, TN, USA.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
Summary

This study integrates evolutionary game theory with optimal control to predict pathogen drug resistance strategies. The approach optimizes time-dependent drug dosages to manage evolving pathogen populations effectively.

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Area of Science:

  • Mathematical Biology
  • Evolutionary Dynamics
  • Pharmacology

Background:

  • Pathogen populations can evolve drug resistance in response to treatment.
  • Traditional optimal control models may not fully capture evolutionary dynamics.

Purpose of the Study:

  • To develop a framework combining evolutionary game theory and optimal control.
  • To predict optimal time-dependent drug dosages for evolving pathogens.

Main Methods:

  • Embedding evolutionary game theory into an optimal control framework.
  • Utilizing a simplified model of viral replication rate and drug resistance trade-offs.

Main Results:

  • Demonstrated a method for integrating evolutionary game theory with optimal control.
  • Illustrated prediction of strategies for time-dependent drug dosages.

Conclusions:

  • The integrated framework can guide drug dosage strategies against evolving pathogens.
  • The method is extendable to more complex, pathogen-specific models.