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Related Concept Videos

Pharmacokinetic–Pharmacodynamic Relationship: Duration of Dose-Effect Relationship01:14

Pharmacokinetic–Pharmacodynamic Relationship: Duration of Dose-Effect Relationship

For drugs producing a quantal response, onset occurs when plasma concentration reaches a minimum effective level (Cmin). The drug's action duration depends on how long the plasma concentration remains above Cmin.Two primary factors influence this duration: dose size and the rate of drug removal from the action site. Both depend on the drug's redistribution to poorly perfused tissues and elimination processes. A larger dose promotes rapid onset and prolongs the effect's duration.Consider a...
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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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Pharmacokinetics is a vital branch of pharmacology that examines how drugs are absorbed, distributed, metabolized, and excreted by the body. Two key methodologies in pharmacokinetics are plasma drug concentration studies and urinary drug excretion analyses, both of which provide critical insights into a drug's therapeutic efficacy and bioavailability.Plasma Drug Concentration-Time StudiesPlasma drug concentration-time studies involve analyzing blood samples at specific intervals to quantify...
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Pharmacodynamics explores the relationship between drug concentration and its effect. In a quantal response drug, the duration of action better correlates with drug concentration, while for graded effect drugs, the intensity of response is more relevant. This intensity depends on the dose, drug removal rate, and the region of the concentration–response curve.The concentration–response curve can be divided into three regions. Region 3 (80–100% maximum response) demonstrates that even as drug...
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Quantitative Aspects of Drug-Receptor Interaction

The receptor occupancy theory connects a drug's response to the number of occupied receptors. With higher drug concentrations, more receptors are occupied, leading to increased responses. The formation of drug-receptor complexes involves association and dissociation rates, which reach equilibrium when the forward and backward reactions are equal. The equilibrium association constant (Ka) and its inverse, the equilibrium dissociation constant (Kd), indicate drug affinity. Higher Ka and lower Kd...
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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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Quantitative structure-retention-pharmacokinetic relationship studies.

Snezana Agatonovic-Kustrin1, Joseph V Turner, Beverley D Glass

  • 1School of Pharmacy and Molecular Sciences, James Cook University, Townsville, QLD 4811, Australia. nena.kustrin@jcu.edu.au

Drug Metabolism Letters
|April 10, 2009
PubMed
Summary

Predicting drug pharmacokinetics (PKs) using micellar liquid chromatography retention times and molecular descriptors can improve drug candidate selection. This approach accurately estimates half-life and volume of distribution, aiding drug development.

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Area of Science:

  • Pharmacokinetics and Drug Development
  • Computational Chemistry
  • Analytical Chemistry

Background:

  • Drug development faces high attrition rates due to poor human efficacy and pharmacokinetics (PKs).
  • Accurate prediction of PK properties is crucial for selecting viable drug candidates early in clinical trials.
  • Existing methods may not fully capture the complex interplay of factors influencing drug behavior in vivo.

Purpose of the Study:

  • To develop novel predictive models for key pharmacokinetic parameters: half-life (t1/2) and volume of distribution (Vd).
  • To utilize micellar liquid chromatography (MLC) retention data combined with theoretically derived molecular descriptors for PK prediction.
  • To enhance the selection process of potential drug candidates by improving in vivo behavior predictions.

Main Methods:

  • Collected retention times, t1/2, and Vd for 26 drugs from literature.
  • Generated 35 molecular descriptors (size, shape, solubility) from 3D structures using Molecular Modeling Pro.
  • Employed Artificial Neural Network (ANN) modeling to correlate descriptors and MLC retention time with t1/2 and Vd.
  • Utilized sensitivity analysis for model refinement and validated models on internal testing and external datasets.

Main Results:

  • ANN models demonstrated significant correlations for t1/2 (0.854 internal, 0.720 external) and Vd (0.855 internal, 0.827 external).
  • Predicted values showed good agreement with literature data, indicating model reliability.
  • Key descriptors identified included solubility, hydrogen bonding potential, molecular size, and shape, alongside MLC retention time.

Conclusions:

  • The developed models effectively predict human pharmacokinetic parameters, aiding in early drug candidate assessment.
  • The combination of experimental MLC data and theoretical descriptors offers a novel approach to pharmacokinetic modeling.
  • This integrated strategy holds promise for advancing drug discovery and development by reducing late-stage failures.