Optimal chemotherapy for Leukemia

A model-based strategy for individualized treatment

Devaraj Jayachandran, Ann E. Rundell, Robert E. Hannemann, Terry Vik, Doraiswami Ramkrishna

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Acute Lymphoblastic Leukemia, commonly known as ALL, is a predominant form of cancer during childhood. With the advent of modern healthcare support, the 5-year survival rate has been impressive in the recent past. However, long-term ALL survivors embattle several treatment-related medical and socio-economic complications due to excessive and inordinate chemotherapy doses received during treatment. In this work, we present a model-based approach to personalize 6-Mercaptopurine (6-MP) treatment for childhood ALL with a provision for incorporating the pharmacogenomic variations among patients. Semi-mechanistic mathematical models were developed and validated for i) 6-MP metabolism, ii) red blood cell mean corpuscular volume (MCV) dynamics, a surrogate marker for treatment efficacy, and iii) leukopenia, a major sideeffect. With the constraint of getting limited data from clinics, a global sensitivity analysis based model reduction technique was employed to reduce the parameter space arising from semi-mechanistic models. The reduced, sensitive parameters were used to individualize the average patient model to a specific patient so as to minimize the model uncertainty. Models fit the data well and mimic diverse behavior observed among patients with minimum parameters. The model was validated with real patient data obtained from literature and Riley Hospital for Children in Indianapolis. Patient models were used to optimize the dose for an individual patient through nonlinear model predictive control. The implementation of our approach in clinical practice is realizable with routinely measured complete blood counts (CBC) and a few additional metabolite measurements. The proposed approach promises to achieve model-based individualized treatment to a specific patient, as opposed to a standard-dose-for-all, and to prescribe an optimal dose for a desired outcome with minimum sideeffects.

Original languageEnglish
Article numbere109623
JournalPLoS One
Volume9
Issue number10
DOIs
StatePublished - Oct 13 2014

Fingerprint

Chemotherapy
leukemia
drug therapy
Leukemia
Drug Therapy
6-Mercaptopurine
mechanistic models
Therapeutics
dosage
Precursor Cell Lymphoblastic Leukemia-Lymphoma
childhood
Blood
pharmacogenomics
Medical Economics
lymphocytic leukemia
leukopenia
model uncertainty
Erythrocyte Indices
Nonlinear Dynamics
Blood Cell Count

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Jayachandran, D., Rundell, A. E., Hannemann, R. E., Vik, T., & Ramkrishna, D. (2014). Optimal chemotherapy for Leukemia: A model-based strategy for individualized treatment. PLoS One, 9(10), [e109623]. https://doi.org/10.1371/journal.pone.0109623

Optimal chemotherapy for Leukemia : A model-based strategy for individualized treatment. / Jayachandran, Devaraj; Rundell, Ann E.; Hannemann, Robert E.; Vik, Terry; Ramkrishna, Doraiswami.

In: PLoS One, Vol. 9, No. 10, e109623, 13.10.2014.

Research output: Contribution to journalArticle

Jayachandran, Devaraj ; Rundell, Ann E. ; Hannemann, Robert E. ; Vik, Terry ; Ramkrishna, Doraiswami. / Optimal chemotherapy for Leukemia : A model-based strategy for individualized treatment. In: PLoS One. 2014 ; Vol. 9, No. 10.
@article{eed2dac8b09842428b9b35bdaaf8d879,
title = "Optimal chemotherapy for Leukemia: A model-based strategy for individualized treatment",
abstract = "Acute Lymphoblastic Leukemia, commonly known as ALL, is a predominant form of cancer during childhood. With the advent of modern healthcare support, the 5-year survival rate has been impressive in the recent past. However, long-term ALL survivors embattle several treatment-related medical and socio-economic complications due to excessive and inordinate chemotherapy doses received during treatment. In this work, we present a model-based approach to personalize 6-Mercaptopurine (6-MP) treatment for childhood ALL with a provision for incorporating the pharmacogenomic variations among patients. Semi-mechanistic mathematical models were developed and validated for i) 6-MP metabolism, ii) red blood cell mean corpuscular volume (MCV) dynamics, a surrogate marker for treatment efficacy, and iii) leukopenia, a major sideeffect. With the constraint of getting limited data from clinics, a global sensitivity analysis based model reduction technique was employed to reduce the parameter space arising from semi-mechanistic models. The reduced, sensitive parameters were used to individualize the average patient model to a specific patient so as to minimize the model uncertainty. Models fit the data well and mimic diverse behavior observed among patients with minimum parameters. The model was validated with real patient data obtained from literature and Riley Hospital for Children in Indianapolis. Patient models were used to optimize the dose for an individual patient through nonlinear model predictive control. The implementation of our approach in clinical practice is realizable with routinely measured complete blood counts (CBC) and a few additional metabolite measurements. The proposed approach promises to achieve model-based individualized treatment to a specific patient, as opposed to a standard-dose-for-all, and to prescribe an optimal dose for a desired outcome with minimum sideeffects.",
author = "Devaraj Jayachandran and Rundell, {Ann E.} and Hannemann, {Robert E.} and Terry Vik and Doraiswami Ramkrishna",
year = "2014",
month = "10",
day = "13",
doi = "10.1371/journal.pone.0109623",
language = "English",
volume = "9",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "10",

}

TY - JOUR

T1 - Optimal chemotherapy for Leukemia

T2 - A model-based strategy for individualized treatment

AU - Jayachandran, Devaraj

AU - Rundell, Ann E.

AU - Hannemann, Robert E.

AU - Vik, Terry

AU - Ramkrishna, Doraiswami

PY - 2014/10/13

Y1 - 2014/10/13

N2 - Acute Lymphoblastic Leukemia, commonly known as ALL, is a predominant form of cancer during childhood. With the advent of modern healthcare support, the 5-year survival rate has been impressive in the recent past. However, long-term ALL survivors embattle several treatment-related medical and socio-economic complications due to excessive and inordinate chemotherapy doses received during treatment. In this work, we present a model-based approach to personalize 6-Mercaptopurine (6-MP) treatment for childhood ALL with a provision for incorporating the pharmacogenomic variations among patients. Semi-mechanistic mathematical models were developed and validated for i) 6-MP metabolism, ii) red blood cell mean corpuscular volume (MCV) dynamics, a surrogate marker for treatment efficacy, and iii) leukopenia, a major sideeffect. With the constraint of getting limited data from clinics, a global sensitivity analysis based model reduction technique was employed to reduce the parameter space arising from semi-mechanistic models. The reduced, sensitive parameters were used to individualize the average patient model to a specific patient so as to minimize the model uncertainty. Models fit the data well and mimic diverse behavior observed among patients with minimum parameters. The model was validated with real patient data obtained from literature and Riley Hospital for Children in Indianapolis. Patient models were used to optimize the dose for an individual patient through nonlinear model predictive control. The implementation of our approach in clinical practice is realizable with routinely measured complete blood counts (CBC) and a few additional metabolite measurements. The proposed approach promises to achieve model-based individualized treatment to a specific patient, as opposed to a standard-dose-for-all, and to prescribe an optimal dose for a desired outcome with minimum sideeffects.

AB - Acute Lymphoblastic Leukemia, commonly known as ALL, is a predominant form of cancer during childhood. With the advent of modern healthcare support, the 5-year survival rate has been impressive in the recent past. However, long-term ALL survivors embattle several treatment-related medical and socio-economic complications due to excessive and inordinate chemotherapy doses received during treatment. In this work, we present a model-based approach to personalize 6-Mercaptopurine (6-MP) treatment for childhood ALL with a provision for incorporating the pharmacogenomic variations among patients. Semi-mechanistic mathematical models were developed and validated for i) 6-MP metabolism, ii) red blood cell mean corpuscular volume (MCV) dynamics, a surrogate marker for treatment efficacy, and iii) leukopenia, a major sideeffect. With the constraint of getting limited data from clinics, a global sensitivity analysis based model reduction technique was employed to reduce the parameter space arising from semi-mechanistic models. The reduced, sensitive parameters were used to individualize the average patient model to a specific patient so as to minimize the model uncertainty. Models fit the data well and mimic diverse behavior observed among patients with minimum parameters. The model was validated with real patient data obtained from literature and Riley Hospital for Children in Indianapolis. Patient models were used to optimize the dose for an individual patient through nonlinear model predictive control. The implementation of our approach in clinical practice is realizable with routinely measured complete blood counts (CBC) and a few additional metabolite measurements. The proposed approach promises to achieve model-based individualized treatment to a specific patient, as opposed to a standard-dose-for-all, and to prescribe an optimal dose for a desired outcome with minimum sideeffects.

UR - http://www.scopus.com/inward/record.url?scp=84907943787&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84907943787&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0109623

DO - 10.1371/journal.pone.0109623

M3 - Article

VL - 9

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 10

M1 - e109623

ER -