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

Control-relevant modeling in drug delivery.

R S Parker1, F J Doyle

  • 1Department of Chemical and Petroleum Engineering, 1249 Benedum Hall, University of Pittsburgh, Pittsburgh, PA 15261, USA. rparker@engrng.pitt.edu

Advanced Drug Delivery Reviews
|May 23, 2001
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

Whole-genome DNA methylation status associated with clinical PTSD measures of OIF/OEF veterans.

Translational psychiatry·2017
Same author

Improvements of growth, appetite, and physical activity in helminth-infected schoolboys 6 months after single dose of albendazole.

Asia Pacific journal of clinical nutrition·2014
Same author

Note: Parameter-independent bounding of the stochastic Michaelis-Menten steady-state intrinsic noise variance.

The Journal of chemical physics·2013
Same author

Modular closed-loop control of diabetes.

IEEE transactions on bio-medical engineering·2012
Same author

Cell population modelling describes intrinsic heterogeneity: a case study for hematopoietic stem cells.

IET systems biology·2011
Same author

Development of a multi-parametric model predictive control algorithm for insulin delivery in type 1 diabetes mellitus using clinical parameters.

Journal of process control·2011

This paper reviews control-relevant models for biomedical engineering drug delivery. It examines patient models and control strategies for anesthesia, blood pressure, cancer chemotherapy, cardiac assist devices, and insulin delivery.

Area of Science:

  • Biomedical Engineering
  • Control Systems
  • Pharmacology

Background:

  • Drug delivery systems require precise control for optimal patient outcomes.
  • Developing accurate models is crucial for designing effective control strategies in medicine.

Purpose of the Study:

  • To review control-relevant models for various biomedical drug delivery problems.
  • To examine patient models and control approaches used in the literature.
  • To discuss the control-relevance of models in specific clinical applications.

Main Methods:

  • Literature review of control-relevant models in biomedical engineering.
  • Summary of control problems and relevant patient models.
  • Examination of control strategies and model relevance.

Related Experiment Videos

Main Results:

  • Identified key control challenges in anesthesia, blood pressure, cancer chemotherapy, cardiac assist devices, and insulin delivery.
  • Assessed the suitability of existing patient models for control applications.
  • Evaluated the effectiveness of various control approaches.

Conclusions:

  • Control-relevant modeling is essential for advancing drug delivery systems.
  • Further research is needed to refine patient models and control strategies for improved therapeutic outcomes.
  • This review provides a foundation for developing more sophisticated biomedical control systems.