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 Concept Videos

Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

6.3K
Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
6.3K
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

1.8K
1.8K
Cancer Therapies02:49

Cancer Therapies

10.6K
Cancer therapies are various modes of treatment, such as surgery, radiation therapy, and chemotherapy that are administered to cancer patients.
However, cancer treatments can pose several challenges, as therapies used to kill cancer cells are generally also toxic to normal cells. Moreover, cancer cells mutate rapidly and can develop resistance to chemical agents or radiation therapy. Besides, all types of cancer cells may not respond to the same therapy. Some cancer cells respond to one...
10.6K
Cancer Therapies02:49

Cancer Therapies

3.0K
3.0K
Treatment Resistant Cancers02:56

Treatment Resistant Cancers

3.9K
Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...
3.9K
Treatment Resistent Cancers02:56

Treatment Resistent Cancers

1.5K
1.5K

You might also read

Related Articles

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

Sort by
Same author

Discovery and Optimization of Pyrazine Carboxamide AZ3246, a Selective HPK1 Inhibitor.

Journal of medicinal chemistry·2025
Same author

Model-Informed Approaches and Innovative Clinical Trial Design for Adeno-Associated Viral Vector-Based Gene Therapy Product Development: A White Paper.

Clinical pharmacology and therapeutics·2023
Same author

Model-based assessment of combination therapies - ranking of radiosensitizing agents in oncology.

BMC cancer·2023
Same author

The quest for balance between capturing data and model complexity: A quantitative clinical pharmacology approach applied to monoclonal antibodies.

CPT: pharmacometrics & systems pharmacology·2023
Same author

Turn On, Tune In, Turnover! Target Biology Impacts In Vivo Potency, Efficacy, and Clearance.

Pharmacological reviews·2023
Same author

Current practices for QSP model assessment: an IQ consortium survey.

Journal of pharmacokinetics and pharmacodynamics·2022
Same journal

Antisolvent crystallization of indomethacin cocrystals: influence of coformers and solvent systems.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences·2026
Same journal

Design and Process Parameter Evaluation of Bilayer Capsule Systems for Targeted Ileal Drug Delivery.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences·2026
Same journal

iRGD-modified peptide-drug conjugate improves brain delivery and antitumor efficacy in glioblastoma.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences·2026
Same journal

A Δ‑based framework for internal release limits in plateau stability systems.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences·2026
Same journal

Innovative Peptide Formulations for Cardiovascular Diseases Using Supercritical CO<sub>2</sub>: A Comprehensive Review and Potential Applications.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences·2026
Same journal

An injectable nanoreinforced hydrogel for combined GDNF-loaded nanoparticles and mesenchymal stem cell therapy in Parkinson's disease.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences·2026
See all related articles

Related Experiment Video

Updated: Mar 23, 2026

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation
15:04

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation

Published on: January 19, 2019

12.9K

Mixture dynamics: Combination therapy in oncology.

Johan Gabrielsson1, Francis D Gibbons2, Lambertus A Peletier3

  • 1Swedish University of Agricultural Sciences, Department of Biomedical Sciences and Veterinary Public Health, Division of Pharmacology and Toxicology, Box 7028, SE-750 07 Uppsala, Sweden.

European Journal of Pharmaceutical Sciences : Official Journal of the European Federation for Pharmaceutical Sciences
|April 7, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces mathematical models to optimize combination therapies for tumor growth. It presents a graphical method for determining optimal drug combinations and dosing strategies for improved treatment outcomes.

Keywords:
Cell-growth/killCombination therapyIsobologramsOncologyTumor Static Concentration

More Related Videos

Sample Extraction and Simultaneous Chromatographic Quantitation of Doxorubicin and Mitomycin C Following Drug Combination Delivery in Nanoparticles to Tumor-bearing Mice
08:57

Sample Extraction and Simultaneous Chromatographic Quantitation of Doxorubicin and Mitomycin C Following Drug Combination Delivery in Nanoparticles to Tumor-bearing Mice

Published on: October 5, 2017

11.6K
Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

19.7K

Related Experiment Videos

Last Updated: Mar 23, 2026

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation
15:04

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation

Published on: January 19, 2019

12.9K
Sample Extraction and Simultaneous Chromatographic Quantitation of Doxorubicin and Mitomycin C Following Drug Combination Delivery in Nanoparticles to Tumor-bearing Mice
08:57

Sample Extraction and Simultaneous Chromatographic Quantitation of Doxorubicin and Mitomycin C Following Drug Combination Delivery in Nanoparticles to Tumor-bearing Mice

Published on: October 5, 2017

11.6K
Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

19.7K

Area of Science:

  • Pharmacology and Mathematical Oncology
  • Focuses on modeling tumor growth dynamics and therapeutic interventions.

Background:

  • Combination therapies are increasingly vital across therapeutic areas.
  • Optimizing these therapies presents significant challenges in modeling and application.

Purpose of the Study:

  • To develop and analyze semi-mechanistic cell-growth/kill models for tumor progression.
  • To introduce methods for optimizing single and combination drug therapies.
  • To generalize concepts like Tumor Static Concentration for dual-compound treatments.

Main Methods:

  • Utilized qualitative and quantitative approaches with simulations and mathematical analysis.
  • Developed semi-mechanistic cell-growth/kill models with multiple sites of action.
  • Introduced a graphical method for optimal combination determination, inspired by isobolograms.

Main Results:

  • Analyzed dynamic properties of single and dual compound models.
  • Generalized Tumor Static Concentration for two-compound scenarios.
  • Demonstrated a graphical approach for identifying optimal drug combinations.

Conclusions:

  • Mathematical modeling offers solutions for optimizing complex combination therapies.
  • The developed graphical method aids in determining optimal drug combinations and dosing regimens.
  • Further research into pharmacokinetics and dosing strategies is crucial for personalized cancer treatment.