Published in:
01-06-2014 | Original Paper
Identifying the optimal dose of ritonavir in the treatment of malignancies
Author:
Emad Y. Moawad
Published in:
Metabolic Brain Disease
|
Issue 2/2014
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Abstract
Identifying the optimal dose of ritonavir therapy overcomes the chemical resistance may exhibit in some cases due to poor prognosis of imprecise staging. Dose modeling was performed by analyzing previously published data of ritonavir cancer growth inhibition in vitro and in vivo. In-vitro 3H-Thymidine-based cell proliferation assay was performed on samples of the GL15 cell line incubated with 0, 1, 10 and 100 μ M of ritonavir. Proliferation inhibition was quantified to identify energy of the used doses as described before in earlier studies. Models involving in-vivo growth of established breast cancer tumor (MDA-MB-231), KSIMM tumor and EL4-T cell thymomas in mice were used. The effects of 40 mg/kg/day for 52 days, 30 mg/kg/day for 15 days and 8.8 mg/mouse/day for about 1 week of ritonavir in those xenograft growths respectively were monitored and quantified to identify energy of those doses as described before in earlier studies. Ritonavir demonstrated an in-vitro reduction in proliferation rate in dose dependent manner. The energy of the in-vitro influences following ritonavir therapy were perfectly correlated (r = 1) with ritonavir dose, allowed to establish an efficient energy-model with a perfect fit (R2=1) describes the energy yield by ritonavir doses, enables to administer the appropriate dose. Ritonavir had also a significant influence in-vivo on all sizes of treated tumors compared to the control animals such that the energy yield by the administered drug as derived from the energy-model was 100 % identical to the induced influence in tumor energy. The in-vitro determination of inhibition to proliferation by ritonavir doses is useful to characterize the response of cancer to ritonavir therapy targeting patient-personalized cancer medicine. The molecular method of response determination by 3H-TDR incorporation and ritonavir dose-energy model are reliable to avoid chemo-resistance by identifying the optimal dosing regimens and schedules prior therapy allowing the use of much lower dose of ritonavir and thus decreases the drug side effects and risks of relapse.