DocumentCode :
48778
Title :
Chemotherapy Drug Scheduling for the Induction Treatment of Patients With Acute Myeloid Leukemia
Author :
Pefani, E. ; Panoskaltsis, Nicki ; Mantalaris, Athanasios ; Georgiadis, Michael C. ; Pistikopoulos, Efstratios N.
Author_Institution :
Dept. of Chem. Eng., Imperial Coll. London, London, UK
Volume :
61
Issue :
7
fYear :
2014
fDate :
Jul-14
Firstpage :
2049
Lastpage :
2056
Abstract :
Leukemia is an immediately life-threatening cancer wherein immature blood cells are overproduced, accumulate in the bone marrow (BM) and blood and causes immune and blood system failure. Treatment with chemotherapy can be intensive or nonintensive and can also be life-threatening since only relatively few patient-specific and leukemia-specific factors are considered in current protocols. We have already presented a mathematical model for one intensive chemotherapy cycle with intravenous (IV) daunorubicin (DNR), and cytarabine (Ara-C) [1]. This model is now extended to nonintensive subcutaneous (SC) Ara-C and for a standard intensive chemotherapy course (four cycles), consistent with clinical practice. Model parameters mainly consist of physiological patient data, indicators of tumor burden and characteristics of cell cycle kinetics. A sensitivity analysis problem is solved and cell cycle parameters are identified to control treatment outcome. Simulation results using published cell cycle data from two acute myeloid leukemia patients [2] are presented for a course of standard treatment using intensive and nonintensive protocols. The aim of remission-induction therapy is to debulk the tumor and achieve normal BM function; by treatment completion, the total leukemic population should be reduced to at most 10$^{9}$ cells, at which point BM hypoplasia is achieved. The normal cell number should be higher than that of the leukemic, and a 3-log reduction is the maximum permissible level of population reduction. This optimization problem is formulated and solved for the two patient case studies. The results clearly present the benefits from the use of optimization as an advisory tool for treatment design.
Keywords :
blood; bone; cancer; cellular biophysics; drugs; patient treatment; physiological models; tumours; BM hypoplasia; acute myeloid leukemia; bone marrow; cell cycle kinetics; cell cycle parameters; chemotherapy drug scheduling; cytarabine; immature blood cells; intensive chemotherapy course; intravenous daunorubicin; leukemia-specific factors; life-threatening cancer; mathematical model; nonintensive protocols; nonintensive subcutaneous Ara-C; normal BM function; patient treatment; patient-specific factors; physiological patient data; remission-induction therapy; sensitivity analysis; tumor burden; Blood; Chemotherapy; Drugs; Mathematical model; Protocols; Sociology; Statistics; Cell cycle models; chemotherapy optimization; mathematical modelling; pharmacodynamics; pharmacokinetics;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2014.2313226
Filename :
6777541
Link To Document :
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