Mathematical Modeling May Help Leukemia Therapy

A study published in the open-access journal PLoS Computational
Biology demonstrates how sophisticated mathematical modeling
has encouraged the development of an optimally-timed vaccine for
chronic myelogenous
leukemia (CML).



Researchers Doron Levy (University of Maryland), Peter P. Lee (Stanford
University), and Peter S. Kim (Г‰cole SupГ©rieure
d'Г‰lectricitГ©, Gif-sur-Yvette, France) collected data over four years
from CML patients who were receiving therapy with the drug imatinib.
They then developed a mathematical model that uses a patient's natural
anti-leukemia response when treated with imatinib to improve leukemia
treatment.



"By combining novel biological data and mathematical modeling, we found
rules for designing adaptive treatments for each specific patient,"
remarked Professor Doron Levy. "Give me a thousand patients and, with
this
mathematical model, I can give you a thousand different customized
treatment plans."



Levy indicates that it is both the drug and the body's natural immune
response that are responsible for leukemia remission. "After starting
imatinib, the anti-leukemia immune response gradually
increases. However, it begins to weaken after it reaches a peak. This
typically happens well into the treatment."



When this weakening occurs, cancer cells can begin to develop
resistance to the drug, and the therapy cab become ineffective. It is
at this point that the immune system needs to be strengthened, and the
authors suggest irradiated pre-therapy blood should be introduced into
the patient. The researchers maintain that further studies are
necessary and should lead to animal models and clinical trials.



Dynamics and Potential Impact of the Immune Response to
Chronic Myelogenous Leukemia

Kim PS, Lee PP, Levy D

PLoS Computational Biology (2008). 4(6):e1000095.

doi:10.1371/journal.pcbi.1000095

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Written by: Peter M Crosta