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

Analyzing multi-response data using forcing functions.

Liping Zhang1, Lewis B Sheiner

  • 1Program of Biological and Medical Informatics, UCSF, Zionsville, IN 46077, USA. lpzno1@yahoo.com

Journal of Pharmacokinetics and Pharmacodynamics
|November 12, 2005
PubMed
Summary
This summary is machine-generated.

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

No MERS-CoV but positive influenza viruses in returning Hajj pilgrims, China, 2013-2015.

BMC infectious diseases·2017
Same author

Pristimerin Inhibits LPS-Triggered Neurotoxicity in BV-2 Microglia Cells Through Modulating IRAK1/TRAF6/TAK1-Mediated NF-κB and AP-1 Signaling Pathways In Vitro.

Neurotoxicity research·2017
Same author

Antimicrobial activity and mechanism of Larch bark procyanidins against Staphylococcus aureus.

Acta biochimica et biophysica Sinica·2017
Same author

Knockout of OsNramp5 using the CRISPR/Cas9 system produces low Cd-accumulating indica rice without compromising yield.

Scientific reports·2017
Same author

Imprinting disorder in donor cells is detrimental to the development of cloned embryos in pigs.

Oncotarget·2017
Same author

Preoperative photocoagulation reduces corneal endothelial cell damage after vitrectomy in patients with proliferative diabetic retinopathy.

Medicine·2017
Same journal

Optimizing Subcutaneous Antibody Dosing Regimens Through Operating Space Maps: rHuPH20 Case Study.

Journal of pharmacokinetics and pharmacodynamics·2026
Same journal

Mechanistic modeling of FcRn-dependent IgG drug interactions: Clinical applications and dosing implications.

Journal of pharmacokinetics and pharmacodynamics·2026
Same journal

Comparing heavy-tailed residual error models for outlier handling in population PK modeling.

Journal of pharmacokinetics and pharmacodynamics·2026
Same journal

Personalized prophylactic therapy optimization in hemophilia A using a hybrid PK-PD-TTE model and deep RL.

Journal of pharmacokinetics and pharmacodynamics·2026
Same journal

Pediatric oral cavity physiologically based pharmacokinetic model to predict pharmacokinetics of mucoadhesive atropine gel to treat sialorrhea.

Journal of pharmacokinetics and pharmacodynamics·2026
Same journal

Exposure-safety analyses of talazoparib in combination with enzalutamide in patients with metastatic castration-resistant prostate cancer (mCRPC) in the TALAPRO-2 trial.

Journal of pharmacokinetics and pharmacodynamics·2026
See all related articles

The forcing function approach (FFA) offers advantages in identifying correct models for physiological flow models (PFM) but yields less accurate parameter estimates than simultaneous modeling (SIM). FFA

Area of Science:

  • Pharmacokinetics
  • Systems Biology
  • Mathematical Modeling

Background:

  • Multi-response data analysis can employ simultaneous modeling (SIM) or the forcing function approach (FFA).
  • Physiological flow models (PFM) are a specific type of multi-response model.

Purpose of the Study:

  • Develop an algorithm for applying FFA to multi-response PFM data.
  • Compare the performance of FFA and SIM under various conditions, including model misspecification.
  • Provide recommendations for using FFA in multi-response data analysis.

Main Methods:

  • Simulated multi-response data from a four-compartment PFM.
  • Applied both SIM and FFA using data-analytic models (DAM) that were identical or different from the data simulation model (DSM).
  • Evaluated performance based on parameter estimation error, prediction error, and model identification success.

Related Experiment Videos

Main Results:

  • FFA exhibited 2x greater parameter estimation error and 3-10x greater prediction error than SIM.
  • SIM failed to identify the correct model twice as often as FFA.
  • FFA's parameter estimates are less reliable in systems with feedback.

Conclusions:

  • FFA is advantageous for model identification in PFM analysis.
  • FFA's parameter estimates may be untrustworthy in multi-response systems with feedback.
  • The ratio of FFA residuals can indicate the trustworthiness of final FFA estimates.