A new model for prediction of drug distribution in tumor and normal tissues: pharmacokinetics of temozolomide in glioma patients.
Authors
Rosso, LulaBrock, Cathryn S
Gallo, James M
Saleem, Azeem
Price, Patricia M
Turkheimer, Federico E
Aboagye, E O
Affiliation
Clinical Sciences Centre, Imperial College, Faculty of Medicine, Hammersmith Hospital Campus, London, UK.Issue Date
2009-01-01
Metadata
Show full item recordAbstract
Difficulties in direct measurement of drug concentrations in human tissues have hampered the understanding of drug accumulation in tumors and normal tissues. We propose a new system analysis modeling approach to characterize drug distribution in tissues based on human positron emission tomography (PET) data. The PET system analysis method was applied to temozolomide, an important alkylating agent used in the treatment of brain tumors, as part of standard temozolomide treatment regimens in patients. The system analysis technique, embodied in the convolution integral, generated an impulse response function that, when convolved with temozolomide plasma concentration input functions, yielded predicted normal brain and brain tumor temozolomide concentration profiles for different temozolomide dosing regimens (75-200 mg/m(2)/d). Predicted peak concentrations of temozolomide ranged from 2.9 to 6.7 microg/mL in human glioma tumors and from 1.8 to 3.7 microg/mL in normal brain, with the total drug exposure, as indicated by the tissue/plasma area under the curve ratio, being about 1.3 in tumor compared with 0.9 in normal brain. The higher temozolomide exposures in brain tumor relative to normal brain were attributed to breakdown of the blood-brain barrier and possibly secondary to increased intratumoral angiogenesis. Overall, the method is considered a robust tool to analyze and predict tissue drug concentrations to help select the most rational dosing schedules.Citation
A new model for prediction of drug distribution in tumor and normal tissues: pharmacokinetics of temozolomide in glioma patients. 2009, 69 (1):120-7 Cancer Res.Journal
Cancer ResearchDOI
10.1158/0008-5472.CAN-08-2356PubMed ID
19117994Type
ArticleLanguage
enISSN
1538-7445ae974a485f413a2113503eed53cd6c53
10.1158/0008-5472.CAN-08-2356
Scopus Count
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