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Updated: Nov 16, 2025

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
08:46

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms

Published on: December 9, 2015

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Dosage strategies for delaying resistance emergence in heterogeneous tumors

Vahideh Vakil1, Wade Trappe1

  • 1Wireless Information Network Laboratory (WINLAB), Rutgers, The State University of New Jersey, New Brunswick, NJ, USA.

FEBS Open Bio
|February 27, 2021
PubMed

Insights

Mathematical modeling helps delay cancer drug resistance by optimizing drug dosage and scheduling. This approach targets tumor heterogeneity to prevent resistant cell growth during treatment.

Area of Science:

  • Mathematical Oncology
  • Cancer Therapeutics
  • Pharmacokinetics and Pharmacodynamics (PKPD)

Background:

  • Drug resistance is a major cause of cancer treatment failure.
  • Tumor heterogeneity drives the emergence of resistant cancer cell populations.
  • Current treatment strategies often fail to account for tumor heterogeneity.

Purpose of the Study:

  • To develop a mathematical framework for modeling clonal evolution in heterogeneous tumors.
  • To investigate strategies for delaying drug resistance emergence using a containment approach.
  • To design optimal drug dosage and scheduling strategies to control resistant subpopulations.

Main Methods:

  • Clonal evolution modeling of drug-sensitive and drug-resistant cancer cell populations.
  • Application of pharmacokinetic/pharmacodynamic (PKPD) modeling to treatment dynamics.
  • Formulation and solution of an optimal control problem for treatment strategy design.

Main Results:

  • Drug dosage and administration schedule significantly influence the dynamics of sensitive and resistant clones.
  • PKPD modeling enables the design of dosage strategies to manage resistant subpopulations.
  • The study identifies optimal dosing strategies to maximize the delay of resistance emergence.

Conclusions:

  • A mathematical framework integrating clonal evolution and PKPD modeling can effectively address drug resistance.
  • Tailored drug dosing and scheduling are crucial for containing resistant cancer cell growth.
  • Optimal control strategies can significantly postpone the rise of resistance in heterogeneous tumors.
Keywords:
clonal evolutioncontainmentdosage strategydrug resistanceoptimal control

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