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

Population pharmacokinetics.

T M Ludden1

  • 1College of Pharmacy, University of Texas-Austin.

Journal of Clinical Pharmacology
|December 1, 1988
PubMed
Summary
This summary is machine-generated.

Population analysis of sparse data from drug development studies yields valuable pharmacokinetic-pharmacodynamic insights. This approach enhances drug safety and efficacy through improved therapeutic regimens and potential automated dosing systems.

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

Population pharmacokinetic meta-analysis with efavirenz.

International journal of clinical pharmacology and therapeutics·2003
Same author

Population pharmacokinetics and pharmacodynamics of sotalol in pediatric patients with supraventricular or ventricular tachyarrhythmia.

Journal of pharmacokinetics and pharmacodynamics·2002
Same author

Population pharmacokinetic-pharmacodynamic modeling of filgrastim (r-metHuG-CSF) in healthy volunteers.

Journal of pharmacokinetics and pharmacodynamics·2001
Same author

Time-variant increase in methylprednisolone clearance in patients with acute respiratory distress syndrome: a population pharmacokinetic study.

Journal of clinical pharmacology·2001
Same author

Analyzing rich data using different methods provided by NONMEM: pharmacokinetics of telmisartan following intravenous infusion to healthy volunteers.

Pharmaceutical research·1999
Same author

Balanced designs in longitudinal population pharmacokinetic studies.

Journal of clinical pharmacology·1998
Same journal

Human Disposition, Metabolism, and Excretion of Sevasemten (EDG-5506), a Selective Modulator of Fast Myosin in Healthy Volunteers.

Journal of clinical pharmacology·2026
Same journal

New Insights into Genetic Polymorphisms Influencing the Therapeutic Efficacy and Toxicity of Rivaroxaban.

Journal of clinical pharmacology·2026
Same journal

Physiologically Based Pharmacokinetic Modeling to Predict the Pharmacokinetics of Sacubitril/Valsartan in the Elderly with Renal or Hepatic Impairment Population.

Journal of clinical pharmacology·2026
Same journal

The Journal of Clinical Pharmacology: 65 Years of History.

Journal of clinical pharmacology·2026
Same journal

Decoupling CAR-T Expansion, Conversion, and Decay Timing: Physiologically Aligned Semi-Mechanistic Modeling With Smooth Gating and a Cauchy Likelihood Residual Model.

Journal of clinical pharmacology·2026
Same journal

Mind the Gap: Unraveling the Pharmacokinetic Variability of Δ9-Tetrahydrocannabinol (THC).

Journal of clinical pharmacology·2026
See all related articles

Area of Science:

  • Pharmacometrics
  • Drug Development
  • Clinical Pharmacology

Background:

  • Population analysis offers a method to extract meaningful data from limited samples.
  • Routine drug development studies generate safety and efficacy data suitable for population analysis.

Purpose of the Study:

  • To highlight the strengths of population analysis in drug development.
  • To illustrate how population analysis can inform clinical practice and drug administration.

Main Methods:

  • Utilizing sparse data from blood samples and pharmacologic monitoring.
  • Developing integrated pharmacokinetic-pharmacodynamic (PK/PD) models.

Main Results:

  • Information extraction from sparse data is feasible and valuable.

Related Experiment Videos

  • Integrated PK/PD models can guide therapeutic regimen adjustments.
  • Potential for developing automated drug administration control systems.
  • Conclusions:

    • Population analysis is a powerful tool in drug development.
    • This approach can significantly improve drug safety and therapeutic efficiency.
    • Future applications may include closed-loop control systems for drug delivery.