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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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Drug elimination from the body primarily occurs through metabolic and excretion pathways. Hepatic metabolism transforms lipophilic drugs into hydrophilic forms for excretion, typically via enzymatic processes classified as phase I (modification) and phase II (conjugation). Renal excretion eliminates drugs and metabolites through filtration and secretion in the kidneys. Impairment in liver or kidney function can hinder these processes, delaying drug clearance and extending the drug’s...
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When drugs are administered extravascularly, a comprehensive evaluation through noncompartmental analysis becomes imperative. This analytical approach considers various parameters that play a crucial role in understanding the pharmacokinetics of these drugs.
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The linear concentration–effect model, underpinned by the principle that pharmacological effect (E) is directly proportional to plasma drug concentration (C), emerges as a pivotal simplification of the Emax model for conditions where C is significantly less than EC50. This model portrays a linear trajectory of the concentration–effect relationship when drug levels are markedly below the EC50 threshold.Despite its inherent assumption of continuous effect augmentation with increasing...
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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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Characterizing QT interval prolongation in early clinical development: a case study with methadone.

Vincent F S Dubois1, Meindert Danhof1, Oscar Della Pasqua2,3

  • 1Division of Pharmacology Leiden Academic Centre for Drug Research Leiden University Leidenthe Netherlands.

Pharmacology Research & Perspectives
|June 10, 2017
PubMed
Summary

Pharmacokinetic-pharmacodynamic (PKPD) modeling can predict QT interval prolongation. Nonclinical data on methadone suggests low risk in humans, but interspecies differences in drug metabolism are critical for accurate risk assessment.

Keywords:
Clinical trial simulationsPKPD modelingQT interval prolongationmethadonetranslational pharmacology.

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Area of Science:

  • Pharmacology
  • Drug Development
  • Cardiovascular Safety

Background:

  • Pharmacokinetic-pharmacodynamic (PKPD) modeling aids in assessing drug-induced QT interval prolongation.
  • Previous work established species correlation for drug-specific parameters, enabling prospective evaluation of nonclinical signals.
  • Methadone's dromotropic effects require careful evaluation in humans.

Purpose of the Study:

  • To illustrate the use of nonclinical methadone data for evaluating human dromotropic drug effects.
  • To prospectively assess the probability of QT interval prolongation in humans using PKPD modeling.
  • To investigate interspecies differences in drug disposition affecting QT prolongation predictions.

Main Methods:

  • Nonlinear mixed effects modeling applied to ECG and drug concentration data from a dog safety pharmacology study.
  • Extrapolation of PKPD model slope from dogs to humans.
  • Clinical trial simulations using methadone PK data and extrapolated parameters for doses ranging from 5 to 500 mg.
  • Assessment of predicted QT interval prolongation (≥5 and ≥10 ms) based on simulated human peak concentrations.

Main Results:

  • Point estimates from dog data indicated a low probability of ≥10 ms QT prolongation in humans.
  • Accounting for 90% credible intervals in dogs predicted approximately a 5 ms QT interval increase.
  • Discrepancies between predicted and observed QT effects in humans were attributed to interspecies differences in drug disposition.
  • Extrapolation of racemic methadone effects may not fully capture observed QT prolongation in patients.

Conclusions:

  • Nonclinical PKPD modeling provides a framework for predicting QT prolongation but requires careful consideration of interspecies differences.
  • Enantioselective metabolism and active metabolites of methadone are critical factors influencing QT interval prolongation.
  • Further assessment is needed to fully understand and predict methadone's cardiovascular safety profile in humans.