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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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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 log-linear model is a pharmacological framework used to describe the relationship between drug concentration and its effect. This model is particularly relevant when the observed effects range between 20% and 80% of the drug’s maximum effect (Emax), where a near-linear relationship is observed between the log of drug concentration and the measured effect. However, the log-linear model does not predict the maximum possible effect (Emax) or the effect at zero drug concentration,...
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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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Video Experimental Relacionado

Updated: Feb 17, 2026

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Simulación de efectos del tratamiento para la gonorrea utilizando un modelo matemático dentro del huésped

Pavithra Jayasundara1, David G Regan2, Philip Kuchel3

  • 1School of Population Health, UNSW Sydney, NSW, Australia.

Infectious Disease Modelling
|February 16, 2026
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Resumen

La resistencia a los antibióticos en Neisseria gonorrhoeae (NG) requiere nuevos tratamientos. Un modelo matemático muestra que la eliminación de bacterias intracelulares es clave para el éxito del tratamiento, no solo los niveles de fármaco extracelular. Gepotidacina y las terapias combinadas son prometedoras.

Palabras clave:
AzitromicinaGentamicinaGepotidacinaGonorreaIntracelularFarmacodinámicoFarmacocinético

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Área de la Ciencia:

  • Microbiología
  • Farmacología
  • Modelización Matemática

Sus antecedentes:

  • Neisseria gonorrhoeae (NG) exhibe una resistencia antibiótica generalizada.
  • Los tratamientos existentes para la gonorrea son cada vez menos efectivos.
  • La modelización matemática puede predecir los resultados del tratamiento.

Objetivo del estudio:

  • Extender un modelo matemático dentro del huésped para incluir la dinámica del tratamiento farmacocinético/farmacodinámico (PK/PD).
  • Investigar la monoterapia con gepotidacina y la terapia dual con gentamicina/azitromicina para la gonorrea.
  • Identificar los índices PK/PD predictivos del éxito del tratamiento.

Principales métodos:

  • Desarrollo de un modelo matemático extendido dentro del huésped que incorpora características PK/PD.
  • Simulación de regímenes de tratamiento para gepotidacina y gentamicina/azitromicina.
  • Análisis de la relación entre los índices PK (por ejemplo, AUC/MIC) y los resultados del tratamiento.
  • Evaluación del papel de la eliminación de NG intracelular en el éxito del tratamiento.

Principales resultados:

  • Las tasas de éxito del tratamiento simulado se correlacionaron con los datos clínicos disponibles.
  • El fracaso antibiótico se relacionó con la eliminación incompleta de NG intracelular.
  • Los índices PK extracelulares por sí solos no pudieron predecir el éxito/fracaso del tratamiento.
  • La gepotidacina intracelular AUC/MIC >150 predijo el éxito.
  • La terapia dual AUC/MIC >140 también predijo el éxito, pero fue menos informativa.

Conclusiones:

  • La carga bacteriana intracelular es un factor crítico en los resultados del tratamiento de la gonorrea.
  • La modelización PK/PD, especialmente considerando las concentraciones intracelulares del fármaco, es crucial para evaluar nuevos antibióticos.
  • Se necesita más investigación sobre la eliminación de NG intracelular para desarrollar terapias efectivas contra cepas resistentes.