68 research outputs found
Predicting Outcomes of Prostate Cancer Immunotherapy by Personalized Mathematical Models
Therapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients. We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simple mathematical models.We developed a general mathematical model encompassing the basic interactions of a vaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cell vaccine. For model validation in the absence of any other pertinent marker, we used the clinically measured changes in prostate-specific antigen (PSA) levels as a correlate of tumor burden. Up to 26 PSA levels measured per patient were divided into each patient's training set and his validation set. The training set, used for model personalization, contained the patient's initial sequence of PSA levels; the validation set contained his subsequent PSA data points. Personalized models were simulated to predict changes in tumor burden and PSA levels and predictions were compared to the validation set. The model accurately predicted PSA levels over the entire measured period in 12 of the 15 vaccination-responsive patients (the coefficient of determination between the predicted and observed PSA values was R(2) = 0.972). The model could not account for the inconsistent changes in PSA levels in 3 of the 15 responsive patients at the end of treatment. Each validated personalized model was simulated under many hypothetical immunotherapy protocols to suggest alternative vaccination regimens. Personalized regimens predicted to enhance the effects of therapy differed among the patients.Using a few initial measurements, we constructed robust patient-specific models of PCa immunotherapy, which were retrospectively validated by clinical trial results. Our results emphasize the potential value and feasibility of individualized model-suggested immunotherapy protocols
An investigation to revitalize the separation performance of hollow fibers with a thin mixed matrix composite skin for gas separation
10.1016/j.memsci.2005.09.041Journal of Membrane Science2761-2113-125JMES
The fabrication of hollow fiber membranes with double-layer mixed-matrix materials for gas separation
10.1016/j.memsci.2008.07.046Journal of Membrane Science3251326-335JMES
The effects of polymer chain rigidification, zeolite pore size and pore blockage on polyethersulfone (PES)-zeolite A mixed matrix membranes
10.1016/j.memsci.2005.03.019Journal of Membrane Science2601-245-55JMES
A novel ion exchange treatment of zeolite for the application of mixed matrix membranes in natural and hydrocarbon separation
AIChE Annual Meeting, Conference Proceedings
Mixed matrix membranes (MMMs) comprising organic polymers with dispersed inorganic fillers for gas separation
10.1016/j.progpolymsci.2007.01.008Progress in Polymer Science (Oxford)324483-507PRPS
Carbon-zeolite composite membranes for gas separation
10.1016/j.carbon.2005.03.003Carbon4392025-2027CRBN
Dual-layer polyethersulfone (PES)/BTDA-TDI/MDI co-polyimide (P84) hollow fiber membranes with a submicron PES-zeolite beta mixed matrix dense-selective layer for gas separation
10.1016/j.memsci.2005.10.008Journal of Membrane Science2771-228-37JMES
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