Jove
Visualize
Contact Us
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 Videos

Maximum likelihood estimation in dynamical models of HIV.

J Guedj1, R Thiébaut, D Commenges

  • 1INSERM, U875 (Biostatistique), Bordeaux, F-33076, France.

Biometrics
|May 11, 2007
PubMed
Summary

This study introduces a new statistical method for analyzing complex dynamical models of HIV infection. The approach improves understanding of HIV pathogenesis and treatment effectiveness using ordinary differential equations (ODEs).

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Assessing the impact of organ-specific lesion dynamics on survival in patients with recurrent urothelial carcinoma treated with atezolizumab or chemotherapy.

ESMO open·2021
Same author

COVA1-18 neutralizing antibody protects against SARS-CoV-2 in three preclinical models.

Research square·2021
Same author

A Randomized Placebo-Controlled Efficacy Study of a Prime Boost Therapeutic Vaccination Strategy in HIV-1-Infected Individuals: VRI02 ANRS 149 LIGHT Phase II Trial.

Journal of virology·2021
Same author

Acute bacterial or viral infection-What's the difference? A perspective from PKPD modellers.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases·2020
Same author

Exogenous acquisition of Pseudomonas aeruginosa in intensive care units: a prospective multi-centre study (DYNAPYO study).

The Journal of hospital infection·2019
Same author

Risk factors for colonization and infection by Pseudomonas aeruginosa in patients hospitalized in intensive care units in France.

PloS one·2018

Area of Science:

  • Mathematical Biology
  • Epidemiology
  • Biostatistics

Background:

  • Dynamical models using ordinary differential equations (ODEs) have advanced HIV pathogenesis understanding.
  • Early models were simplified and patient-specific; recent models use whole-sample inference for complex ODE systems.
  • Inference in complex ODE models is challenging, with Bayesian methods being the primary approach to date.

Purpose of the Study:

  • To develop and validate a full likelihood inference method for complex dynamical models of HIV infection.
  • To adapt a Newton-like algorithm for parameter estimation in these sophisticated models.
  • To address challenges including detection limits in observational data.

Main Methods:

  • Proposed a full likelihood inference approach for complex ODE models of HIV.

Related Experiment Videos

  • Adapted a Newton-like algorithm for parameter estimation.
  • Developed a model for observations accounting for detection limits.

    • Main Results:

    • The proposed full likelihood inference method was applied to a complex ODE model for HIV.
    • The approach was tested on data from the ALBI ANRS 070 antiretroviral therapy clinical trial.
    • A simulation study demonstrated the effectiveness and robustness of the developed algorithm.

    Conclusions:

    • The new full likelihood inference algorithm performs well for complex HIV dynamical models.
    • This method offers a viable alternative to Bayesian approaches for HIV model inference.
    • The approach successfully analyzes clinical trial data and handles observational complexities like detection limits.