Jove
Visualize
Contact Us

Related Concept Videos

Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

285
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...
285
Pharmacodynamic Models: Linear Concentration–Effect Model01:15

Pharmacodynamic Models: Linear Concentration–Effect Model

20
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...
20
Pharmacodynamic Models: Logarithmic Concentration–Effect Model01:15

Pharmacodynamic Models: Logarithmic Concentration–Effect Model

17
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,...
17
Pharmacodynamic Models: Additive and Proportional Drug Effect Model01:09

Pharmacodynamic Models: Additive and Proportional Drug Effect Model

18
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...
18
Modeling with Differential Equations01:25

Modeling with Differential Equations

98
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
98

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Cost-effectiveness of a decentralised molecular point-of-care testing programme for sexually transmitted infections in remote primary care health services in Australia.

Sexually transmitted infections·2026
Same author

Hantavirus outbreak on a cruise ship in the South Atlantic.

Lancet (London, England)·2026
Same author

Respiratory syncytial virus (RSV) vaccination program for older Australians reduces health inequalities: a distributional cost-effectiveness analysis.

Vaccine·2026
Same author

Ensemble forecasts of COVID-19 activity to support Australia's pandemic response: 2020-22.

PLoS computational biology·2026
Same author

Estimating the cost-effectiveness of respiratory syncytial virus (RSV) vaccination program for older Australian adults.

Vaccine·2026
Same author

Capturing SARS-CoV-2 immune landscapes to inform future strategies for COVID-19 vaccination in a high-income setting: a mathematical modelling study.

BMC infectious diseases·2026
Same journal

Modeling and control of highly pathogenic avian influenza in poultry using network disease dynamics.

Infectious Disease Modelling·2026
Same journal

When hosts gather: how extreme seasonal aggregation affects epidemiological outcomes.

Infectious Disease Modelling·2026
Same journal

Predicting the spatiotemporal evolution of HIV/AIDS in Africa: A retrospective analysis of epidemiological trends.

Infectious Disease Modelling·2026
Same journal

Quantitative risk assessment of avian influenza: A scoping review.

Infectious Disease Modelling·2026
Same journal

Memory mechanisms for behavioural change in Bayesian individual-level spatial epidemic models.

Infectious Disease Modelling·2026
Same journal

Modeling two-strain competition with reinfection: Mathematical analyses and epidemiological implications.

Infectious Disease Modelling·2026
See all related articles
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Feb 17, 2026

Quantitative Examination of Antibiotic Susceptibility of Neisseria gonorrhoeae Aggregates Using ATP-utilization Commercial Assays and Live/Dead Staining
08:04

Quantitative Examination of Antibiotic Susceptibility of Neisseria gonorrhoeae Aggregates Using ATP-utilization Commercial Assays and Live/Dead Staining

Published on: February 8, 2019

9.1K

Simulating treatment effects for gonorrhoea using a within-host mathematical model.

Pavithra Jayasundara1, David G Regan2, Philip Kuchel3

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

Infectious Disease Modelling
|February 16, 2026
PubMed
Summary
This summary is machine-generated.

Antibiotic resistance in Neisseria gonorrhoeae (NG) necessitates new treatments. A mathematical model shows intracellular bacteria clearance is key for treatment success, not just extracellular drug levels. Gepotidacin and combination therapies show promise.

Keywords:
AzithromycinGentamicinGepotidacinGonorrhoeaIntracellularPharmacodynamicPharmacokinetic

More Related Videos

Using Single-Worm Data to Quantify Heterogeneity in Caenorhabditis elegans-Bacterial Interactions
09:54

Using Single-Worm Data to Quantify Heterogeneity in Caenorhabditis elegans-Bacterial Interactions

Published on: July 22, 2022

3.7K
Models of Murine Vaginal Colonization by Anaerobically Grown Bacteria
08:53

Models of Murine Vaginal Colonization by Anaerobically Grown Bacteria

Published on: May 25, 2022

4.6K

Related Experiment Videos

Last Updated: Feb 17, 2026

Quantitative Examination of Antibiotic Susceptibility of Neisseria gonorrhoeae Aggregates Using ATP-utilization Commercial Assays and Live/Dead Staining
08:04

Quantitative Examination of Antibiotic Susceptibility of Neisseria gonorrhoeae Aggregates Using ATP-utilization Commercial Assays and Live/Dead Staining

Published on: February 8, 2019

9.1K
Using Single-Worm Data to Quantify Heterogeneity in Caenorhabditis elegans-Bacterial Interactions
09:54

Using Single-Worm Data to Quantify Heterogeneity in Caenorhabditis elegans-Bacterial Interactions

Published on: July 22, 2022

3.7K
Models of Murine Vaginal Colonization by Anaerobically Grown Bacteria
08:53

Models of Murine Vaginal Colonization by Anaerobically Grown Bacteria

Published on: May 25, 2022

4.6K

Area of Science:

  • Microbiology
  • Pharmacology
  • Mathematical Modeling

Background:

  • Neisseria gonorrhoeae (NG) exhibits widespread antibiotic resistance.
  • Existing treatments for gonorrhoea are becoming less effective.
  • Mathematical modeling can predict treatment outcomes.

Purpose of the Study:

  • To extend a within-host mathematical model to include pharmacokinetic/pharmacodynamic (PK/PD) treatment dynamics.
  • To investigate gepotidacin monotherapy and gentamicin/azithromycin dual therapy for gonorrhoea.
  • To identify PK/PD indices predictive of treatment success.

Main Methods:

  • Developed an extended within-host mathematical model incorporating PK/PD features.
  • Simulated treatment regimens for gepotidacin and gentamicin/azithromycin.
  • Analyzed the relationship between PK indices (e.g., AUC/MIC) and treatment outcomes.
  • Evaluated the role of intracellular NG clearance in treatment success.

Main Results:

  • Simulated treatment success rates correlated with available clinical data.
  • Antibiotic failure linked to incomplete clearance of intracellular NG.
  • Extracellular PK indices alone could not predict treatment success/failure.
  • Intracellular gepotidacin AUC/MIC >150 predicted success.
  • Dual therapy AUC/MIC >140 also predicted success but was less informative.

Conclusions:

  • Intracellular bacterial load is a critical factor in gonorrhoea treatment outcomes.
  • PK/PD modeling, especially considering intracellular drug concentrations, is crucial for evaluating new antibiotics.
  • Further research on the killing of intracellular NG is needed to develop effective therapies against resistant strains.