Optimized Treatment Schedules for Chronic Myeloid Leukemia

Qie He, Junfeng Zhu, David M Dingli, Jasmine Foo, Kevin Zox Leder

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Over the past decade, several targeted therapies (e.g. imatinib, dasatinib, nilotinib) have been developed to treat Chronic Myeloid Leukemia (CML). Despite an initial response to therapy, drug resistance remains a problem for some CML patients. Recent studies have shown that resistance mutations that preexist treatment can be detected in a substantial number of patients, and that this may be associated with eventual treatment failure. One proposed method to extend treatment efficacy is to use a combination of multiple targeted therapies. However, the design of such combination therapies (timing, sequence, etc.) remains an open challenge. In this work we mathematically model the dynamics of CML response to combination therapy and analyze the impact of combination treatment schedules on treatment efficacy in patients with preexisting resistance. We then propose an optimization problem to find the best schedule of multiple therapies based on the evolution of CML according to our ordinary differential equation model. This resulting optimization problem is nontrivial due to the presence of ordinary different equation constraints and integer variables. Our model also incorporates drug toxicity constraints by tracking the dynamics of patient neutrophil counts in response to therapy. We determine optimal combination strategies that maximize time until treatment failure on hypothetical patients, using parameters estimated from clinical data in the literature.

Original languageEnglish (US)
Article numbere1005129
JournalPLoS Computational Biology
Volume12
Issue number10
DOIs
StatePublished - Oct 1 2016

Fingerprint

myeloid leukemia
Leukemia
Leukemia, Myelogenous, Chronic, BCR-ABL Positive
Therapy
Appointments and Schedules
Schedule
therapeutics
Drug therapy
Ordinary differential equations
system optimization
Toxicity
Therapeutics
Efficacy
Treatment Failure
Optimization Problem
drug toxicity
Neutrophils
drug resistance
Drug Resistance
Patient Identification Systems

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

Cite this

Optimized Treatment Schedules for Chronic Myeloid Leukemia. / He, Qie; Zhu, Junfeng; Dingli, David M; Foo, Jasmine; Leder, Kevin Zox.

In: PLoS Computational Biology, Vol. 12, No. 10, e1005129, 01.10.2016.

Research output: Contribution to journalArticle

He, Qie ; Zhu, Junfeng ; Dingli, David M ; Foo, Jasmine ; Leder, Kevin Zox. / Optimized Treatment Schedules for Chronic Myeloid Leukemia. In: PLoS Computational Biology. 2016 ; Vol. 12, No. 10.
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